Department of Homeland Security
Science & Technology Directorate
TECHNOLOGY CENTERS
RESEARCH AGENDA
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
i
TABLE OF CONTENTS
Table of Contents ....................................................................................................... i
Introduction .............................................................................................................. 1
Advanced Sensing .................................................................................................... 4
Artificial Intelligence (AI) and Autonomous Systems (AS) .......................................... 7
Biotechnology ......................................................................................................... 11
Communications and Cyber Resiliency .................................................................... 13
Data, Modeling, and Simulation Sciences ............................................................... 18
Digital Identity and Trust ......................................................................................... 22
Earth Systems Sciences .......................................................................................... 25
Emerging Computing Paradigms .............................................................................. 28
Novel Materials and Secure Manufacturing ............................................................. 31
Social Sciences ...................................................................................................... 33
Appendix A: Priorities and Focus Areas ......................................................................ii
Appendix B: Acronym List ..........................................................................................iv
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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INTRODUCTION
The Department of Homeland Security (DHS) Science and Technology Directorate
(S&T) Technology Centers (Tech Centers) conduct basic and applied research into
emerging and future science and technology to ensure science and technology
advancements can be harnessed for cutting-edge solutions to DHS operational
challenges. In general, our research looks to build knowledge and understanding of:
•
Evolving S&T Threats, Hazards & Risks – characterizing the misuses of
science and technology, as well as the consequences and intervention and/
or countermeasure options
•
Current & Emerging Technologies, Scientific Advancements – new science
and technology applications, potential technology vulnerabilities, and
security measures for use in homeland security operations
Our research is driven by strategic and long-term needs of the Department and
Homeland Security Enterprise (HSE) and provides an avenue for S&T to be forward-
leaning, looking five to ten years out to understand and anticipate what science-
based or technology-related issues may impact the Department in the future and
ideally avoid technology surprise and reduce overall risk to the Department.
S&T Tech Centers’ research priorities are designed to leverage science and technology
advancements to enable key Departmental missions, including the priority mission
advancements articulated by Homeland Security Secretary Alejandro Mayorkas in
2022
1
1
Priorities | Homeland Security (dhs.gov)
:
•
Combat all forms of terrorism and
targeted violence
•
Increase cybersecurity of our
nation’s networks and critical
infrastructure, including election
infrastructure
•
Secure our borders and modernize
ports of entry
•
Build a fair, orderly, and humane
immigration system
•
Ready the nation to respond to and
recover from disasters and combat
the climate crisis
•
Combat human trafficking, labor
exploitation, and child exploitation
INTRODUCTION
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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-
STRATEGIC INTENT
Given the speed at which technology is evolving, coupled with the convergence of
technologies where advances in some emerging technologies can have significant
impacts on others, our ability to foresight
2
and monitor emerging technologies from
the perspective of the Department is critical to reducing future risks.
2
Foresighting explores the confluence of societal, technological, environmental, economic, political issues with science and technology
innovations to inform what solutions or what type of solution options are most viable. Foresighting deepens the understanding of the driving
forces behind this confluence, identifies gaps in knowledge; suggests areas of new research required to better understand driving forces,
builds consensus among a range of stakeholders about the issues and how to tackle them, identifies and makes explicit some of the difficult
policy choices and tradeoffs in the future, creates a new strategy that is resilient because it is adaptable to changing external conditions, and
mobilizes stakeholders to action.
The Tech Centers’ research portfolio is inherently rooted in the principles of evidence
building and scientific integrity. Our goal is to identify and fill critical data and
information gaps and to drive innovation and continuous learning so DHS can keep
pace with the evolving threat landscape.
3
Responding to the nation’s most pressing
challenges and executing the Department’s core missions requires using the best
science and evidence available that are based on facts resulting from rigorous and
systematic analysis. These charges are established through “The Foundations for
Evidence-Based Policymaking Act of 2018”
4
(Evidence Act) and reflect the mission
and values of S&T. Ensuring scientific integrity
5,6
is also critical to all aspects of the
Tech Centers’ work to guarantee the research and science we produce is objective,
clear, unbiased, transparent, reproducible, and accurately represented. Strict
adherence to professional values and practices will ensure robust science and lead to
trust and confidence in our research.
3
Evidence is broadly defined as information that aids in the generation of a conclusion through foundational fact finding, synthesizing the
existing body of knowledge, evaluating current or emerging practices, approaches or interventions, filling knowledge and data gaps, and
bridging the nexus between research and policy and best position S&T to support the Department. The Government Accountability Office
describes evidence building “as a cycle of activities that can help decision makers obtain the evidence they need to address policy questions
or identify the questions they should address.”
4
Foundations for Evidence-Based Policy Making Act of 2018 was signed into law in January 2019. The law incorporates many of the recom
mendations of the U.S. Commission on Evidence-Based Policymaking (2017) to improve the use of evidence and data to generate policies
and inform programs in the federal government.
5
National Science and Technology Council. 2022. “Protecting the Integrity of Government in Science.”
https://www.whitehouse.gov/wp-content/uploads/2022/01/01-22-Protecting_the_Integrity_of_Government_Science.pdf
6
Department of Homeland Security. 2012. “DHS Directive 026-07: Scientific Integrity.”
https://www.dhs.gov/xlibrary/assets/foia/dhs-directive-026-07-scientific-integrity.pdf
INTRODUCTION
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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S&T TECH CENTERS RESEARCH PRIORITIES
S&T Tech Centers’ Research Agenda is intended to provide the strategic framework
against which we align and focus our research portfolio, and it communicates our
priorities and objectives over the next three years. This Research Agenda identifies
the most critical and impactful advances and developments in science and
technology from the perspective of where the emerging technology and science
trends are headed and their potential impact or implications to the Department.
Our Overarching Research Priority Areas Are:
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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ADVANCED SENSING
MISSION IMPACTS:
Enhance threat sensing and
detection capabilities across
multitude of threats and DHS
operational environments
Sensors are vital to almost every mission of DHS. The ability to identify manmade
and natural threats and maintain situational awareness during both daily operations
and during catastrophic incidents is critical to protecting the homeland. The variety
of threats and hazards that we look to detect is broad, and the types of sensors
required to detect those threats and hazards are complex and can span several
emerging technology areas. From tracking and identifying
the movement of goods and people across borders and
in maritime environments; monitoring the environment for
wildfires, floods and other natural and manmade disasters;
and securing buildings, aircraft, and other venues from
malicious actors, the DHS mission space is ripe with needs
and opportunities for advanced sensing capabilities.
As the science and technology landscape continues to
evolve and converge, DHS also encounters new challenges
that we must address. Such challenges include the need
to detect counterfeit microelectronics or to counter new
types and nefarious uses of unmanned aerial systems. Research and development
(R&D) into advanced sensor technologies may allow us to address those challenges.
Emerging technology areas that show promise for advanced sensor capability are
quantum sensors and nanotechnology. Quantum sensors are predicted to be many
more times sensitive than current systems, supporting the development of magnetic,
acoustic and gravity sensors with increased capabilities; low-power, high-sensitivity
airborne and space-based sensors; remote sensing; precision timing, etc. These
sensors may allow us to alleviate our reliance on potentially vulnerable position,
navigation, and timing systems. They may also enhance our ability to sense in more
remote environments that are too dangerous to have officers and operators physically
in, as well as increase the resiliency of our communications systems. Advances in
nanotechnology that reduce the size, weight, power consumption, and cost of sensors
could make it possible to deploy sensor networks over large areas in urban or remote
environments and better integrate sensors in environments with limited space, such
as checkpoints.
ADVANCED SENSING
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Advanced Sensing Focus Areas and Technical Objectives
Focus Area 1. Signature Exploitation and Detection – We aim to understand how
emerging sensor technologies and existing detection capabilities can be applied in
new ways to detect, track, and identify objects, threats, hazards, physical, and cyber
conditions.
•
Technical Objective 1: Identify advancements in sensor technology to
detect materials of interest such as chemical, biological and agriculture
agents, explosive materials, contraband, as well as monitor environmental
conditions for fire and flood.
•
Technical Objective 2: Identify and evaluate signatures and capabilities
not currently being exploited by DHS to understand their potential uses
in homeland security applications. Examples include medical, safety, and
environmental monitoring where innovation of sensor development is driven
by commercial use.
•
Technical Objective 3: Identify cutting-edge advancements and capabilities
for transformative improvements in robustness and suitability of sensing
technology within DHS’s operational environments, such as remote and
maritime environments that require low-power consumption, portability, and
resistance to environmental conditions such as extreme temperatures, salt,
and humidity.
Focus Area 2: Sensor Integration – As novel sensors become available for use, S&T
must develop appropriate sensor system architectures, integrate multiple sensors,
and evaluate novel sensor effectiveness.
•
Technical Objective 1: Assess new sensor integration concepts and
approaches to understand their potential impact to DHS missions and to
enable DHS to remain agile enough to incorporate new technologies as they
are developed while maintaining high standards of operational efficiency
and readiness.
•
Technical Objective 2: Understand how to maintain high cybersecurity
standards in integrated sensor environments to forecast possible
technology advances and threats with an impact on deployed sensors. This
will be vital to maintaining the security and effectiveness of current and
future integrated sensor environments.
•
Technical Objective 3: Create novel sensor integration methods,
architectures, and interfaces to better leverage new and emerging
technologies such as edge computing and advanced analytics, the
internet of things, quantum computing, 6G communications, human-
machine teaming, immersive visualization, and other advances. These new
technologies may provide opportunities to integrate and advance sensor
capabilities and address challenges in DHS systems and operations, while
maintaining awareness of possible security implications.
ADVANCED SENSING
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Focus Area 3: Emerging Sensing Technologies – S&T aims to collaborate with leading
researchers and innovators in quantum sensing and nanotechnology to support initial
transitions of early development into successful prototypes of novel tools for DHS
missions and use cases.
•
Technical Objective 1: Develop a framework for benchmarking quantum
sensing capabilities to enable assessment and analysis of capabilities for
DHS missions and use cases.
•
Technical Objective 2: Identify and test promising quantum technology
prototypes relevant to DHS and critical infrastructure missions (such
as high-stability inertial sensors for unmanned aircraft systems, or
UAS, missions in urban canyons or low-cost atomic clocks for critical
infrastructure timing applications).
•
Technical Objective 3: Track nanotechnology sensor advances that
are applicable to DHS use cases. Examples include nanofluidics,
nanomaterials, nanoelectronics and other aspects of nanotechnology that
could impact sensing threats of interest in DHS environments.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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ARTIFICIAL INTELLIGENCE (AI)
AND AUTONOMOUS SYSTEMS (AS)
MISSION IMPACTS:
Transform screening capabilities
at ports of entry; defend against
advanced AI/AS attacks on critical
infrastructure
Both the “U.S. Department of Homeland Security Artificial Intelligence Strategy”
7
and
the “S&T Artificial Intelligence and Machine Learning Strategic Plan”
8
refer to “Artificial
Intelligence” as:
“…automated, machine-based technologies with at least
some capacity for self-governance that can, for a given
set of human-defined objectives, make predictions,
recommendations, or decisions influencing real or virtual
environments.”
7
Department of Homeland Security. “Artificial Intelligence Strategy.” 2020.
https://www.dhs.gov/sites/default/files/publications/dhs_ai_strategy.pdf
8
Department of Homeland Security Science and Technology Directorate. “S&T Artificial Intelligence and Machine Learning Strategic Plan.”
2021. https://www.dhs.gov/sites/default/files/publications/21_0730_st_ai_ml_strategic_plan_2021.pdf
Artificial Intelligence (AI) is the most prevalent topic across
multiple strategic drivers for R&D within S&T and has the
potential both to significantly impact the Department across
many missions and to spawn new inventions and additional
advances in numerous other domains (e.g., autonomous
systems
9
, intelligent sensors, etc.).
9
AI is typically embedded in either analytic process or some kind of (semi or fully) autonomous system process. In semi or fully autonomous
systems, AI receives input (e.g., through sensors), produces an output internal to the system (decision), and then acts on that output (action)
to affect the external world state. It is well understood that to achieve full autonomy capable of operating in any kind of non-trivial environ
ment, an autonomous system, particularly fully autonomous, will require AI in both the sensing and deciding cycles.
As AI and AS become mainstream, it is critical that we understand the landscape,
the evolution of the various aspects of the technology, the supporting science,
and the needs of the Department. Key areas of AI R&D include computer vision for
applications such as surveillance and screening systems and biometrics, and natural
language processing for applications such as law enforcement and immigration
services. Key use cases for AS include transportation (automotive, aerospace,
maritime, and rail), utilities (water and wastewater, oil and gas, electric power, and
telecommunications), facility operations (security, energy management, environmental
control, and safety). Importantly, and as recognized by the North Atlantic Treaty
Organization (NATO)
10
, “The need for new algorithmic approaches and a better
understanding of human-machine teaming has probably never been stronger.” It
is imperative that operators in the homeland security enterprise are comfortable/
engaged with the capabilities possible from these technology advances. As these
capabilities quickly evolve, we must look ahead in this space, understand capabilities,
identify, and push through limitations to meet Departmental needs and anticipate
potential threats.
10
Reding, D.F. and Eaton, J. NATO Science & Technology Organization. 2020. Science & Technology Trends 2020-2040 – Exploring the S&T
Edge. p. 54. https://www.sto.nato.int/publications/Management%20Reports/2020_TTR_Public_release_final.pdf
Advances in and accessibility to AI also come with the potential for new and
increased threats when capabilities are use with bad intent. “Adversarial AI”
11
11
“Adversarial AI” can also be referred to as Adversarial AI Attacks, AI-Based Attacks, AI Adversarial Attacks, Adversarial Attacks in Age of AI,
Adversarial Attacks on Machine Learning, Adversarial Attacks on Neural Networks, Adversarial Attacks, etc.
is
one of the risks/threats at the forefront of the AI research community. Because
ARTIFICIAL INTELLIGENCE (AI)
AND AUTONOMOUS SYSTEMS (AS)
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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security of AI is a relatively immature sub-discipline,
there is some range of interpretation in exactly what
space the term covers. For S&T purposes, we define
Adversarial AI as the spaces represented in green and
blue, as shown in Figure 3.
12
As AI becomes more
prevalent in IT, threat actors are finding new ways to
use AI to deny, degrade, and disrupt missions (e.g.,
improved social engineering, deepfakes, improved way
of hiding malware, etc.). These attacks can include
data poisoning, reverse engineering machine learning
data sets, among others attack vectors. The design of
attacks can focus on attacks executed in both digital
and non-digital spaces, such as electromagnetic
spectrum. The point at which an AI-based attack can
be detected/thwarted through cyber defenders and
the point at which AI-expertise is required to detect,
identify, and thwart AI-based attacks remains an
open question. Figure 4
13
provides a useful visualization for appreciating the overlap
between the two. DHS must understand, not only the underlying technology, but also
how to organize and prepare to defend against these types of attacks.
12
We assume that “Attack” can be either design or execute or both, and that AI Attacks can be directed at non-digital infrastructure.
13
Borrowed from Gupta, K.D. and Dasgupta, D. (2021). “Who is Responsible for Adversarial Defense?”, Proceedings of the 38th International
Conference on Machine Learning PMLR 39, 2021.
Use of AI
to Attack a
System
Use of AI to
Attack an
AI-Based
System
Attack an
AI-Based
System
Figure 3. Adversarial AI. Described as the Use of
AI to Attack an AI-based System
Figure 4. Generalized Adversarial Attach Points on Machine Learning Model
ARTIFICIAL INTELLIGENCE (AI)
AND AUTONOMOUS SYSTEMS (AS)
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
9
Artificial Intelligence and Autonomous Systems Focus Areas and Technical
Objectives:
Focus Area 1: Trustworthy AI/AS – DHS needs to be able to assess the performance
of AI/AS for potential operational use in order to maintain the integrity of DHS
missions and to ensure the appropriate systems are employed. In general, this focus
area aims to:
•
Effectively assess the performance of AI/AS systems against technical
and mission metrics.
•
Provide operators making critical decisions an appropriate level of trust
and confidence in the AI/AS system.
•
Inspire trust in the general public towards AI/AS systems deployed by
DHS.
•
Technical Objective 1: Understand when explainability
14
is important in AI
applications and assess the effectiveness of explainability in DHS missions
that depend on AI.
14
Because AI is a relatively immature discipline, terms like “explainability” or “robustness” are terms of art and subject to interpretation.
“Explainability” generally addresses the extent to which human users can comprehend the results of an AI/AS. “Robustness” generally
addresses the degree to which the AI/AS is stable despite noisy data or perturbations in the data.
•
Technical Objective 2: Assess and advance AI/AS robustness
14
to ensure
the reliability of AI implementations in the DHS mission spaces.
Focus Area 2: Adversarial AI – Across all the layers in the communications and tech
stacks (data, software, hardware, networks, and communications), we must guard
against sophisticated adversaries employing AI attacks.
•
Technical Objective 1: Identify, characterize, and classify known adversarial
attacks, both in the academic community and in the intelligence
community, to increase understanding an awareness across the broader
DHS and federal interagency community.
•
Technical Objective 2: Understand the effectiveness of attacks against
digital and non-digital infrastructure (e.g., physical devices and
electromagnetic spectrum) and their potential impacts to HSE missions.
•
Technical Objective 3: Understand what will be required to deter, protect
against, detect, and respond to adversarial AI attacks against digital
and non-digital assets in zero trust architecture environments including
traditional information technologies, operational technologies, and
electromagnetic spectrum.
ARTIFICIAL INTELLIGENCE (AI)
AND AUTONOMOUS SYSTEMS (AS)
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Focus Area 3: Advanced Applications of AI/AS for Unique DHS Missions – This
focus area aims to advance AI/AS capabilities in various subfields (such as
computer visioning, natural language processing, predictive modeling, etc.) to
drive application of AI/AS across specific DHS missions and needs (e.g., biometric
capabilities, media, and analytics for mis/dis/mal information, digital forensics,
etc.).
•
Technical Objective 1: Understand how humans and AI/AS can most
effectively collaborate to successfully carry out homeland security
missions. Investigate human supervision and interaction with AI/AS to
optimize human-machine systems and performance in DHS’s operational
settings.
•
Technical Objective 2: Identify and develop use cases based on DHS
missions that will benefit from application of AI/AS, considering AI/AS
sub-components such as:
•
Natural language processing and generation and machine translation,
including transformer architectures, social listening, automated
strategic communication, and media and analytics.
•
Anomaly detection in events, images, texts, video, speech, and other
sources.
•
Technical Objective 3: Identify challenges in operationalizing AI within
DHS. (Examples include embedding AI components in real time,
feedback situations including deep reinforcement learning, secure AI
edge applications including distributed sensors, and actuators and
computation.)
•
Technical Objective 4: Assess the efficacy of adopting high-end AI chips
for homeland security big computing use cases.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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BIOTECHNOLOGY
MISSION IMPACTS:
Detect and defend against new
biothreats and new pathways for
bio and agroterrorism
Biotechnology is generally defined as the integration of the life sciences and
engineering with the goal of harnessing the power of biological molecules, cells,
and/or even whole organisms for industrial, commercial, or other purposes. More
specifically, biotechnology comprises genetic, metabolic, tissue, and microbial
community engineering, biopharmaceutical development, catalysis, bioleaching and
bioremediation, selective plant and animal breeding, and
other applications. Scientists have many biotechnological
tools at their disposal, including: polymerase chain reaction
(PCR), nucleotide (e.g., DNA) synthesizers and sequencers,
DNA-cutting and pasting enzymes, genome editors,
bioinformatics databases and analytics, cloning and gene
delivery vectors, bioreactors, cell-based assays, genetically
tractable molecular chasses, antibodies, nanoparticles,
and a vast array of other proteins that can perform specific
functions including chemical sensing and transformation.
Global research activity in biotechnology is intense and driven largely by its
applications to public health, agriculture, other industrial products (e.g., biofuels),
manufacturing, and the demands of basic science; however, biotechnological
tools are inherently dual-use and have been recognized as “critical and emerging
technologies” by the National Science and Technology Council (NSTC)
15
. DHS must
therefore fully understand their associated risks and opportunities.
15
National Science and Technology Council. “Critical and Emerging Technologies List Update” 2022.
https://www.whitehouse.gov/ostp/news-updates/2022/02/07/technologies-for-american-innovation-and-national-security
To counter the threats of bioterrorism, DHS must address issues such as the
misappropriation of biotechnological tools
by state or non-state actors for offensive
use, how DHS can deter or prevent
attempts by state or non-state actors to
misappropriate biotechnological tools for
offensive use, and whether DHS can harvest
any biotechnological tools to augment the
defensive posture of the United States. Close
and continuous evaluation and research into
these issues will enable DHS to make sound
tactical and strategic decisions and inform
policy, strategy, and investments to ensure
that the United States not only continues to
lead the innovation in biotechnology but does
so with a full understanding and preemptive
mitigation of foreseeable downside risks—
thus enhancing public safety.
BIOTECHNOLOGY
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Biotechnology Focus Areas and Technical Objectives:
Focus Area 1: Worldwide Developments in Biotechnology – DHS must continuously
monitor worldwide developments in biotechnology—and the life sciences
more broadly—to fully understand new opportunities for U.S. adversaries to
misappropriate those developments for offensive use and to enable the United
States to harvest them for defensive use.
•
Technical Objective 1: Identify topics and trends in biotechnological
research and assess how new research results could expand and/or
impact an actor’s options along a potential biological attack pathway to
prevent technological surprise.
•
Technical Objective 2: Identify approaches to counter emerging material
threats.
•
Technical Objective 3: Identify and harvest emerging opportunities to
bolster the bio-defensive posture of the United States.
Focus Area 2: Existing and Emerging Biological Agent Detection – DHS must
support homeland resiliency by developing capabilities that can quickly detect and
identify any potentially hazardous materials in environmental aerosol samples.
•
Technical Objective 1: Continuously assess machine learning-enabled
analytic methods for DNA/RNA sequencing, proteomics/protein
sequencing, spectroscopy, mass spectrometry, and other computational
approaches that can be used to identify biological and biochemical
hazards.
•
Technical Objective 2: Develop computational capabilities to quickly
identify and tentatively characterize any potential nucleotide-based (i.e.,
DNA/RNA) biological hazard. This includes further development of models
of gene function and organization and deep learning to identify patterns
within genomes.
•
Technical Objective 3: Identify approaches and capabilities for high-
sensitivity and high-specificity real-time identification of components of
environmental aerosol samples.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
13
COMMUNICATIONS AND
CYBER RESILIENCY
MISSION IMPACTS:
Enhance resiliency to cyberattacks
& communication disruptions;
enable 24/7 interoperable
emergency communications
Operational assurance in an increasingly digitally integrated environment requires
resiliency across data, software, hardware, and communications networks.
DHS operations are often conducted in challenging, congested, and contested
environments across cyber and electromagnetic domains. While technologies
continue to evolve independently in both domains, it will be critical to integrate
multi-domain solutions that are able to prevent, detect, and
respond to threats holistically at speed and scale to secure
operations across the homeland security enterprise.
DHS is the national lead for protecting and enhancing
the security and resilience of the nation’s civilian cyber
and communications systems and critical infrastructure.
Furthermore, DHS relies on and employs a broad set of
communications and computing technologies to accomplish
its many missions to include securing our digital and physical
borders, protecting the transportation system, responding
to natural disasters and emergencies, and safeguarding
our financial systems. As part of this mission, it is essential
to assess and counter evolving cybersecurity threats that may materialize as
malicious activity and cybercrime. In addition, law enforcement will need increasingly
sophisticated cyber tools to prevent, identify, investigate, disrupt, and dismantle
criminal enterprises that are increasingly reliant on digital technologies.
The need for and importance of cybersecurity is well recognized by the government
and industry. Recent events such as SolarWinds
16
and the Colonial Pipeline
17
attacks
highlight the need for continued investments and advancements in this domain,
as the threats remain persistent and evolving as technologies and capabilities
continue to advance. Under the DHS 2020 – 2024 Strategic Plan,
18
Goal 3 is to
“Secure Cyberspace and Critical Infrastructure” with objectives focused on securing
federal civilian networks, assessing and countering evolving cybersecurity risks,
and combating cybercrime. Executive Order (EO) 14028 “Improving the Nation’s
Cybersecurity”
19
further outlines specific areas of focus for bold changes and
investments to protect the nation from malicious cyber actors while recognizing
that government and industry must work hand in hand to foster a more secure
cyberspace. The EO states “…that the prevention, detection, assessment, and
remediation of cyber incidents is a top priority and essential to national and
economic security.”
20
16
Cybersecurity and Infrastructure Security Agency. “Emergency Directive 21-01 - Mitigate SolarWinds Orion Code Compromise.” 2020.
https://www.cisa.gov/emergency-directive-21-01
17
Congressional Research Service. “Colonial Pipeline: The DarkSide Strikes.” 2021.
https://crsreports.congress.gov/product/pdf/IN/IN11667
18
Department of Homeland Security. “The DHS Strategic Plan – Fiscal Years 2020-2024.” 2019. p. 26-35.
https://www.dhs.gov/publication/department-homeland-securitys-strategic-plan-fiscal-years-2020-2024
19
Executive Office of the President. “E.O. 14028 – Improving the Nation’s Cybersecurity.” 2021.
https://www.federalregister.gov/documents/2021/05/17/2021-10460/improving-the-nations-cybersecurity
20
Executive Office of the President. “E.O. 14028 – Improving the Nation’s Cybersecurity.” 2021. p. 26633
https://www.federalregister.gov/documents/2021/05/17/2021-10460/improving-the-nations-cybersecurity
COMMUNICATIONS AND
CYBER RESILIENCY
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
14
Cybersecurity is not a stand-alone field, nor is it limited to traditional IT applications.
As more and more digital capabilities are realized and interconnected, cybersecurity
plays a role in ensuring those technologies, such as AI, IoT and other sensors, space-
based applications, and countless more, are securely leveraged and protected
against things like ransomware attacks.
21
As the EO states, “the trust we place in our
digital infrastructure should be proportional to how trustworthy and transparent that
infrastructure is, and to the consequences we will incur if that trust is misplaced.”
22
As new, digitally based technologies evolve, cybersecurity plays a key role in reducing
or eliminating potential new exposures and vulnerabilities.
21
As stated in Reding, D. F. and J. Eaton’s 2020 NATO Science & Technology Trends 2020-2040 - Exploring the S&T Edge, “Cyber-attacks
against BLUE (commercial or military) space control centres open up additional areas of vulnerability and the possibility of ransomware.”
22
Executive Office of the President. “E.O. 14028 – Improving the Nation’s Cybersecurity.” 2021. p. 26633
https://www.federalregister.gov/documents/2021/05/17/2021-10460/improving-the-nations-cybersecurity
While AI will give us unprecedented ability to protect against, detect, and respond
to cybersecurity threats at a greater scale, so too will this technology be used to
generate and deploy new and novel attacks at speeds and sophistication levels
unseen in today’s networks. Furthermore, increasingly robust communications
capabilities will enable more effective information sharing and collaboration between
humans and technologies but will also provide an expanded attack surface for
adversaries to detect and affect the resilience of our operations.
Increasing assurance of the data, as well as the software and hardware that store
and process that data, is only part of the solution. For humans and machines to
make effective use of the data for automated decision-making and action-taking,
it is essential to increase the resilience of the wired and wireless communications
networks that are used to share data between these technology systems. Similar to
cybersecurity, communications is also a well-documented area of continued need
and importance for the HSE.
23, 24, 25
The communications ecosystem includes both
terrestrial (e.g., narrowband, broadband, High Frequency (HF), undersea, aerial)
and non-terrestrial (e.g., celestial, space) solutions. Advanced communication
networks are a key element of tomorrow’s digital infrastructure and are an enabler
of technology such as AI, internet of things (IoT), and augmented reality/virtual
reality (AR/VR). The promises of advances in technologies such as 5G/XG and the
proliferation of low Earth orbit satellite constellations (LEO) are anticipated to be
revolutionary. 5G is expected to facilitate fundamentally new classes of applications,
from real-time remote operations and enhanced situational awareness, to self-driving
cars, smart buildings, AR, and more.
23
The Office of Science and Technology Policy FY22 Research Priorities calls out advanced communications networks and encourages in-
vestment in “the development of applications that leverage 5G and advanced networks that incorporate security and privacy as fundamental
values” as well as the application of AI/ML to communications and cybersecurity with the goal of secure and trusted applications.
24
The Cybersecurity and Infrastructure Security Agency’s National Emergency Communications Plan, the nation’s strategic plan to strengthen
and enhance emergency communications capabilities, includes national strategic objectives centered around building resilient and secure
emergency communications systems to reduce cybersecurity threats and vulnerabilities.
25
The U.S. Coast Guard’s (USCG) first line of effort in the 2019 Arctic Strategic Outlook is to “Enhance Capability to Operate Effectively in a
Dynamic Arctic” and the sub-objective “Close the Critical Communications Gap in the Arctic” is one of three sub-objectives through which the
USCG seeks to operate effectively, maintain maritime domain awareness, and share information across a harsh and unforgiving environment.
COMMUNICATIONS AND
CYBER RESILIENCY
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
15
-
-
Quantum-based technology is another area that provides both threats and
opportunities in terms of resilience of our computer and communications networks
for the future. The race for quantum supremacy is spawning research investments by
nation-states as well as industry and pushing the science and technology forward at
a pace not seen before.
26,27
With these technical advances, however, come emerging
threats as well. The Administration’s FY22 R&D budget priorities
28
highlight Quantum
Information Science (QIS) as one of its top five research priorities to “enable next-
generation quantum devices, and expansion of efforts exploring and piloting uses
of quantum technology to help support agency missions.” The field of QIS and its
applications is broad but offers significant technical advances in speed, precision, or
functionality
29
primarily applied in areas such as cryptography, computation, sensing
and imaging, communications and materials.
30
26
Office of the Deputy Assistant Secretary of the Army (Research & Technology). 2019. Emerging Science and Technology Trends: A Synthesis
of Leading Forecasts. https://apps.dtic.mil/dtic/tr/fulltext/u2/1078879.pdf
27
China has invested heavily in quantum computing, spending upwards of $10B on the country’s National Laboratory for Quantum Informa
tion Sciences. Is China leading the quantum computing race? - Tech Wire Asia
28
Office of Science and Technology Policy. “Fiscal Year (FY) 2022 Administration Research and Development Budget Priorities and Cross-cut-
ting Actions.” 2020. P.4. <https://www.whitehouse.gov/wp-content/uploads/2020/08/M-20-29.pdf>
29
National Quantum Coordination Office. 2021. About QIS. About - National Quantum Initiative.
30
Reding, D. F. and J. Eaton. Brussels: NATO Science & Technology Organization. “Science & Technology Trends 2020-2040 - Exploring the
S&T Edge.” 2020.
Within the quantum computing domain, the most well-known and immediate concern
is the ability of a quantum computer to crack current encryption schemes used
today. Although the timelines on when such a quantum computer will be achieved are
varied, the cybersecurity impacts are significant and will likely affect sensitive data
that is being generated now and in the near future.
31
Informed planning can help the Department protect its
equities, and thus, staying abreast of developments
is critical in order to help advise and inform the
Department as it develops guidance.
31
i.e. technical developments that can impact timelines and capabilities such as qubit capabilities, cold quantum, quantum storage, quan
tum networks, error rates, etc.
Additionally, quantum-based communications and
networking offers the ability to maintain secure
communications worldwide and eavesdropping detection,
but again these capabilities are likely 10 years
32
or
more away. However, nearer term applications of
quantum technologies such as Rydberg atom sensing
can provide opportunities to increase the resilience of
communications systems in congested and contested
electromagnetic environments.
32
Reding, D. F. and J. Eaton. Brussels: NATO Science & Technology Organization. “Science & Technology Trends 2020-2040 - Exploring the
S&T Edge.” 2020.
COMMUNICATIONS AND
CYBER RESILIENCY
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Communications and Cyber Resiliency Focus Areas and Technical Objectives:
Focus Area 1: Data-centric Security – This focus area aims to increase the reliability
and employability of data for homeland security missions.
•
Technical Objective 1: Identify and evaluate new and emerging
technological applications, such as post-quantum cryptography and
homomorphic encryption, to ensure the confidentiality, integrity, and
availability of data at rest, in process, and in transit.
•
Technical Objective 2: Identify and evaluate new resilient machine learning
approaches, explainable AI (XAI) and human-machine teaming capabilities,
and generative adversarial attack identification and mitigation approaches
to increase trustworthiness of advanced data science and analytics.
Focus Area 2: Software and Hardware Assurance – This focus area aims to ensure
the resilience of the data, software, and hardware used to execute homeland security
mission functions.
•
Technical Objective 1: Ensure the confidentiality, integrity, and availability
of data at rest, in process, and in transit across software and hardware
platforms by researching and evaluating new and emerging applications
such as post-quantum cryptography and homomorphic encryption.
•
Technical Objective 2: Ensure advanced computing software and hardware
applications are designed to rapidly adapt to the evolving security
environment and future technologies. Example applications include but are
not limited to sensors and IoT, operational technologies (OT), cyber physical
systems (CPS); high performance computers (HPC); microelectronics, edge,
cloud, fog, mobile, and quantum computing and civil space systems.
•
Technical Objective 3: Leverage advances in emerging technologies
such as memory-safe programming languages, zero trust architectures;
infrastructure as code/pilot light (IaC/PL); augmented, virtual, and cross
reality (AR/VR/XR) and adaptive secure-by-design architectures to increase
cybersecurity across operations.
•
Technical Objective 4: Increase assurance across the supply chain and
lifecycle of key software and hardware employed in cybersecurity functions
and critical infrastructure such as security orchestration and automated
response (SOAR), software bill of materials (SBOM), and federated identity,
credential, and access management (ICAM).
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
COMMUNICATIONS AND
CYBER RESILIENCY
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
17
Focus Area 3: Communications and Network Resiliency – This focus area aims
to protect and enhance the networks that transport the voice and data between
devices/humans and the interconnected software and hardware systems (e.g., V2X).
•
Technical Objective 1: Identify and understand new and emerging
communications concepts and technologies such as spectrum agility,
broadband virtualization, and software defined networking to enable
communications resilience in the face of increasingly congested and
contested operational environments (spectrum scarcity, intentional
interference).
•
Technical Objective 2: Investigate advanced communications technologies
(i.e., 5G/XG mobile networks, optical interlinks across proliferated low-
Earth orbit satellite (LEO) networks, and quantum sensing receivers) to
identify and assess new risks and potential attack surfaces as well as
enable new use cases to dramatically enhance capabilities and create
efficiencies for DHS missions.
•
Technical Objective 3: Create techniques to maintain security and
communications in an environment where new complex architectures
(everything-as-a-service) present more attack surfaces for adversarial
exploitation.
•
Technical Objective 4: Identify gaps in existing standards that result in non-
interoperable, proprietary, or inefficient solutions, to inform and accelerate
the development of new standards resulting in improved techniques to test
and verify conformance to standards.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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DATA, MODELING, AND
SIMULATION SCIENCES
MISSION IMPACTS:
Advance training via virtual reality;
enable greater data analytics
capabilities across DHS missions
We are shifting from a world where data were rare, precious, and expensive to a
world where data are ubiquitous, commonplace, and inexpensive. In this data-rich
environment, we can leverage data science developments across multiple homeland
security missions to find signals, patterns, or structure within high-dimensional,
noisy, uncertain input data and simulation sciences conduct experiments to
predict different operational outcomes. Figure 5 shows the
interconnectedness between the two. Such research has the
potential to impact a range of homeland security operations,
such as improving phenomenology of crowd models,
improving tool sets available in cyber analytics platforms,
decreasing time to develop training data annotations in
law enforcement missions, improving air interdiction of
drug trafficking, adapting training according to the trainee’s
strengths and weaknesses. In all cases, this requires an
improved data ecosystem. This work plays a critical role in
informing, evaluating, and advising the Department on the
cutting-edge capabilities and envisioning and prototyping use cases that benefit from
a best of breed approach as technology drives us to a smart, connected world.
Additionally, both data and simulation sciences are increasingly combined with
machine learning approaches.
33
Science-based simulations are increasingly relying
on embedded ML models not only to interpret results from massive data outputs
but also to steer computations. Science-based models (e.g., provides a more easily
communicated and understood digital representation of a system that enables
experimentation) are being combined with data-driven
models (e.g., finding signals, patterns, or structure
within high-dimensional, noisy, uncertain input data)
to represent complex systems and phenomena. This
recognition of “models” is significant as models
are another common component to both data and
simulation sciences. As such, this category of the
research area also represents modeling areas of
importance to DHS that do not fall in classic science-
based simulations discussed thus far. These include
technologies such as virtualization, game engines,
and virtual/augmented reality. Example applications
of these modeling technologies include enhanced
situational awareness in operations through AR and
digital twinning, improvements in training through
VR and game engines, and improvements in testing
through virtualization and digital twinning.
33
As described in Section H. Emerging Computing Paradigms, machine learning is also driving convergence at the hardware level as high-per-
formance computing elements are being introduced into both simulation and data-centric systems to support its application.
Data
Analytics
Data to
Simulation
Data to Data
Analytics
Hybrid
Simulation
Figure 5. Complementary Nature of Data
Analytics and Simulation
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
DATA, MODELING, AND
SIMULATION SCIENCES
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Finally, as massive stores and streams of digital data are driving an increasing
emphasis on more sophistication at the application level (e.g., on-demand
computation, rapid data processing, comparisons between simulations and
observations, machine learning, etc.), the importance of an effective data ecosystem
is increasingly apparent. It must consist
of multiple integrated resources and
software services, including resources
for managing data, processing data,
analyzing data, exploring data,
collaborating with data, and sharing
data. Data need to be discoverable,
accessible, reproducible, secure, trusted,
and reusable. Data management and
lifecycle policies (e.g., curation, storage,
retention and deletion, I/O requirements,
etc.) are key concerns. And, in contrast
to traditional scientific computing
infrastructure, the data ecosystem must
place greater emphasis on establishing
a workable system for users providing
access to systems, managing files,
and connecting with data collection
instruments.
Data, Modeling, and Simulation Sciences
Focus Areas and Technical Objectives:
Focus Area 1: Advance Data Analytics Capabilities – This focus area aims to improve
existing data analytics capabilities and invent/adapt new and emerging capabilities
for DHS use.
•
Technical Objective 1: Assess the performance of data science capabilities
against DHS use cases involving data, such as survey and scientific data,
text, speech, audio, images, video, and live streams, and determine
methods to leverage for DHS use.
•
Technical Objective 2: Identify and adopt emerging data analytics concepts
and technologies and characterize their ability to scale to support DHS
operations.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
DATA, MODELING, AND
SIMULATION SCIENCES
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
20
Focus Area 2: Advance Modeling and Simulation Capabilities – This focus area aims
to improve existing modeling and simulation capabilities and adapt new and emerging
capabilities for DHS use.
•
Technical Objective 1: Identify key classes of models of significant impact
to the homeland security enterprise that do not yet have consensus across
theoretical underpinnings (e.g., crowd modeling, cyber traffic modeling,
etc.) and document the breadth of approaches to enable developers,
practitioners, and accreditors across the homeland security enterprise can
benefit from this collection.
•
Technical Objective 2: Assess, leverage, and advance the use of scientific
ML (e.g., hybrid algorithms and models for predictive scientific computing,
ML-enabled adaptive algorithms, parameter tuning and multiscale surrogate
models, etc.) for homeland security applications.
Focus Area 3: Combine Data Analytics and Simulation Capabilities
•
Technical Objective 1: Experiment with stream processing and in-
memory processing techniques for analyzing high-rate, real-world data
on a digital twinning application, linking a simulation of a system with the
real-world data collected from that system. Example includes maintaining
synchronization between a digital twin of the southern border and sensor
platforms at the southern border in near real time.
•
Technical Objective 2: Understand the limitations of learning models from
simulated environments and explore how simulation and other apps, such
as video games, can collect data that can later be used for experimentation
or predictive analytics.
•
Technical Objective 3: Explore Model-Test-Model paradigms, augmenting
test and evaluation with simulation-based capabilities, and develop the
automation, analytics and algorithms necessary to update the simulation
model with live data collected from the test.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
DATA, MODELING, AND
SIMULATION SCIENCES
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
21
Focus Area 4: Data Ecosystem – This focus area aims to increase knowledge and
inform best practices for data ecosystems that serve all modeling communities and
enable data analytics, simulation, and AI applications.
•
Technical Objective 1: Evaluate automated methods to assist in data
set maturation (e.g., data annotation mechanisms to characterize data
sets, synthetic data generation methods to thicken data sets, automated
synchronization of object models across heterogeneous data sets, etc.)
to better enable machine learning applications and to find better, faster,
cheaper ways of engineering data needed across DHS operations and
oversight.
•
Technical Objective 2: Determine how to characterize infrastructure and
tech stacks needed for efficient and secure data collection and data
engineering to streamline data-analytics workflow automations to find
better, faster, cheaper ways of creating value to the operational community
from the data it collects.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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DIGITAL IDENTITY AND TRUST
MISSION IMPACTS:
Adapt to and assess emerging
identity paradigms while
maintaining security & privacy
Trust is a key issue for being able to transact electronically with natural persons and
non-person entities, such as organizations and machines, across different systems.
Ensuring the provenance, confidentiality, integrity, and availability of data is critical
to transact with trust and maintain privacy across interconnected services, devices,
and users. The proliferation of online services and cloud
computing are enabling new operational efficiencies while
simultaneously creating novel risks. Digital trust enabled
by new capabilities such as digital credentials (e.g., mobile
driver licenses) and zero trust architecture are critical to DHS
successfully deploying and operating 5G communication
systems, critical infrastructure, government services, and
many other Department missions.
The ability to establish and verify an individual’s identity
enables the Department to perform risk-based decision
making that is tailored to the individual. Such decision
making may involve determining whether an individual is eligible to receive specific
services or benefits or ascertaining if an individual is a known or suspected threat.
For example, as the Transportation Security Administration begins to accept mobile
driver’s licenses at airport checkpoints and U.S. Customs and Border Protection
examines travelers’ documents (e.g., passports) through customs checkpoints, we
must be able to detect whether those documents are compromised in some way. In
addition, as DHS develops and scales different identity verification technologies to
meet evolving needs, we must ensure approaches include effective privacy and civil
rights and liberties safeguards for U.S. citizens consistent with U.S. laws, regulations,
and DHS authorities as they are developed.
The Office of Science and Technology Policy FY22 priorities
34
state that “Departments
and agencies should also prioritize R&D aimed at improving data accessibility and
security, including fundamental research into efficient privacy and security preserving
techniques and building and/or strengthening infrastructure, platforms, and tools that
facilitate responsible data use.” Advancements in U.S infrastructure and security will
also require the development of robust privacy protections and controls. The evolution
of privacy enhancing technologies, processing, and correlation necessitate investing
in research to conduct thoughtful tradeoffs of risks, performance, and mission needs.
34
Office of Science & Technology Policy. “Fiscal Year (FY) 2022 Administration Research and Development Budget Priorities and Cross-cut-
ting Actions.” 2020. p.9. <https://www.whitehouse.gov/wp-content/uploads/2020/08/M-20-29.pdf>
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
DIGITAL IDENTITY AND TRUST
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
23
Digital Identity and Trust Focus Areas and Technical Objectives:
1. Focus Area 1: Digital Identity – This focus area aims to assess and manage risks
associated with new, emerging, and disruptive technologies that may affect DHS’s
ability to establish and verify identity of entities (natural person, non-person) to
strengthen and manage risks across a diverse range of DHS missions.
•
Technical Objective 1: Organize, characterize, and prioritize risks to in-
person and online activities to establish or verify asserted identity and
biometric information.
•
Technical Objective 2: Assess and manage risks and verify the uniqueness,
integrity, validity, and provenance of identity and biometric information.
•
Technical Objective 3: Establish appropriate datasets and assess
capabilities to enable experimentation and minimize risks associated with
use of personally identifiable information.
•
Technical Objective 4: Facilitate the development of standards, best
practices, test tools, and certification criteria to enable identity issuing
authorities and relying parties to implement secure infrastructure and use
of trustworthy identity information.
Focus Area 2: Privacy Enhancing Technologies – This focus area aims to understand
effective and performant ways to meaningfully exchange data while respecting the
confidentially and use of entities information
•
Technical Objective 1: Develop and assess data anonymization and
minimization techniques for effectiveness, performance, and fit for DHS use
cases.
•
Technical Objective 2: Develop methods for evaluating the effectiveness,
performance, and fit of privacy enhancing technologies for DHS use cases.
•
Technical Objective 3: Identify and assess methods for DHS’s investigative
and protection mission to lawfully investigate bad actors while minimizing
access others data.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
DIGITAL IDENTITY AND TRUST
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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Focus Area 3: Trust and Safety – This focus area aims to understand how trust can
be gained, lost, and enhanced between entities on digital platforms.
•
Technical Objective 1: Characterize threats in which bad actors can
obfuscate, misattribute, and manipulate their identity.
•
Technical Objective 2: Characterize threats in which bad actors can access,
obfuscate, misattribute, and manipulate their data and communication
channels.
•
Technical Objective 3: Understand the governance and efficacy of emerging
technology and trust frameworks, including zero trust architecture,
cryptographic agility, omni-channel experiences and service design, and
trust and safety of online communities.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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25
-
EARTH SYSTEMS SCIENCES
MISSION IMPACTS:
Counter new threats to climate
change initiatives, such as
exploiting social inequality;
enhance critical infrastructure
resilience to climate-related
disasters
Earth Systems Science (ESS) is the transdisciplinary analysis of the structure and
functioning of the Earth as an adaptive, integrated system and the interactions
between environmental (including geophysical), human, and technological systems.
ESS is a recently new field of science, emerging over the last two decades. Its
goal is to produce unified sets of concepts and analytical
frameworks that can address facets of ongoing global
change holistically. Global research in the Earth systems
science domain has grown exponentially and is driven
largely by the need to better understand how Earth systems
are reacting to human, technological, and climate change;
consequences for life on Earth; and implications to safety
and security with potential influences on emerging risks and
threat vectors toward enabling prediction, adaptation, and
mitigation of undesirable consequences.
The Biden Administration placed climate change at the top
levels of its international and domestic agendas, with a
$2 trillion whole-of-government climate plan that will have
far-reaching effects on the U.S. economy.
35
The need for
investment in Earth systems science to better understand global change is amplified
by the 2021 Annual Threat Assessment issued by the Director of National Intelligence,
which identifies climate change as a major transnational security threat,
36
as does the
National Intelligence Council
37
and Department of Defense.
38
Disasters from all-hazards and climate change will continue to challenge DHS across
a range of missions and frontline operations exacerbating known and unknown risks
to public safety and national security. Physical impacts of extreme weather and
changing climatic conditions such as environmental degradation will increasingly
intersect with human impacts of population growth, economic development, and
technological innovation (geo-engineering and digitization). DHS will be affected
in the short- and long-term with rising disaster costs and losses, worsening risks
35
In the January 27, 2021, Executive Order on Tackling the Climate Crisis at Home and Abroad, the President calls for a wide range of unilat-
eral and bilateral measures to ensure the nation fully engages in both a domestic and international response to this crisis. This includes es-
tablishing a White House Office of Domestic Climate Policy. <https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/
executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/>
36
On April 9, 2021, in the 2021 Annual Threat Assessment, the Office of the Director of National Intelligence said, “We assess that the
effects of a changing climate and environmental degradation will create a mix of direct and indirect threats, including risks to the economy,
heightened political volatility, human displacement, and new venues for geopolitical competition that will play out during the next decade and
beyond.” p.18. <https://www.dni.gov/files/ODNI/documents/assessments/ATA-2021-Unclassified-Report.pdf>
37
On October 21, 2021, in the National Intelligence Estimate on Climate Change, the National Intelligence Council said, “We assess that
climate change will increasingly exacerbate risks to U.S. national security interests as the physical impacts increase and geopolitical tensions
mount about how to respond to the challenge… Countries are arguing about who should act sooner and competing to control the growing
clean energy transition. Intensifying physical effects will exacerbate geopolitical flashpoints, particularly after 2030, and key countries and
regions will face increasing risks of instability and need for humanitarian assistance.” p.i.
< https://www.dni.gov/files/ODNI/documents/assessments/NIE_Climate_Change_and_National_Security.pdf>
38
In the Department of Defense’s Climate Risk Analysis, published in October 2021, the DoD says, “Climate change is reshaping the geostra
tegic, operational, and tactical environments with significant implications for U.S. national security and defense. Increasing temperatures;
changing precipitation patterns; and more frequent, intense, and unpredictable extreme weather conditions caused by climate change
are exacerbating existing risks and creating new security challenges for U.S. interests… To train, fight, and win in this increasingly complex
environment, DoD will consider the effects of climate change at every level of the DoD enterprise.” p.2.
< https://media.defense.gov/2021/Oct/21/2002877353/-1/-1/0/DOD-CLIMATE-RISK-ANALYSIS-FINAL.PDF>
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
EARTH SYSTEMS SCIENCES
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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of environmental degradation, critical infrastructure and supply chain disruptions,
civil unrest, and social instability. Adversarial threats from climate terrorism and
extremism will continue to emerge as malign actors seek to exploit these risks for
advantage and tensions mount with particular effects on the most vulnerable.
In response, DHS issued a strategic framework for addressing the climate crisis and
incorporated climate change as a priority in its strategic and long-term planning.
DHS also seeks to optimize climate risk management for safety and security and
understands the key decisions, data, and information requirements for effective
action. DHS must therefore fully understand these associated risks and opportunities
through the application of Earth systems
science. Close and continuous research
into the key areas outlined below will
enable DHS to make sound tactical and
strategic decisions and inform key policy
and investments decisions to enhance
U.S. resilience to the impacts of climate
change, ensure U.S. leadership in climate
adaption, resilience, and sustainability
innovation, and best positioned to
address emerging security challenges and
future risks.
S&T’s ongoing efforts in this research
area align with the Department’s priority
mission to prepare the nation to respond
to and recover from disasters and combat
the climate crisis. We seek to understand
the impacts of climate change to DHS
missions along the lines of safety and
security. Issues that DHS will address
include emerging security challenges associated with a changing climate, effects of
climate change on DHS missions and operations, and the potential for malign actors
to exploit climate risks and/or climate technology innovation.
Earth Systems Sciences Focus Areas and Technical Objectives:
Focus Area 1: Worldwide Developments in Earth System Science and Climate
Innovations – DHS must continuously monitor worldwide developments in Earth
system science—and climate technologies and innovations more broadly—to
fully understand new opportunities for U.S. adversaries to misappropriate those
developments for offensive use and to enable the United States to harvest them for
strategic use.
•
Technical Objective 1: Identify topics and trends in Earth systems science
(i.e., geoengineering and technology innovations) and assess how new
research results could expand and/or impact an actor’s options along a
potential climate resilience pathway to prevent adversarial surprise.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
EARTH SYSTEMS SCIENCES
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•
Technical Objective 2: Identify approaches to counter malign use of
emerging climate interventions (i.e., geoengineering) and adversarial
threats (i.e., exploit civil grievances and social inequality).
•
Technical Objective 3: Identify and harvest emerging opportunities to
bolster the climate security posture of the United States.
Focus Area 2: Earth System Monitoring and Detection Capabilities – DHS must
support homeland resiliency by identifying, leveraging, and developing capabilities
that can quickly detect and identify any potential first-, second-, and third-order
effects of climate change and extreme weather risks.
•
Technical Objective 1: Continuously assess scientific methods, remote
sensing technologies, and other computational approaches (including AI)
that can be used to identify, monitor, and track climate change-driven
effects (e.g., wildfires, permafrost melt, extreme heat, invasive species, and
pathogens).
•
Technical Objective 2: Advance computational capabilities to quickly
identify and tentatively characterize large-scale changes coupled to human-
environmental systems. This includes furthering approaches to in situ,
aerial, and space-based observation and detection.
•
Technical Objective 3: Identify opportunities to develop capabilities for
high-sensitivity and high-specificity real-time detection and monitoring of
climate impacts in harsh operating environments (e.g., Arctic).
Focus Area 3: Disaster Adaptation and Resilience Capabilities – DHS must support
homeland resiliency by identifying, leveraging, and developing capabilities for
enhanced adaptation to and resilience from disasters.
•
Technical Objective 1: Continuously assess Earth system science to
understand the interplay between geophysical and anthropogenic
forcing and model transition waypoint, recognizing a need for adaptive
management strategies to address future unknowns.
•
Technical Objective 2: Advance computational capabilities to optimize
climate change investments, translate the benefits into policies and
incentives, and measure the effectiveness of these climate interventions.
•
Technical Objective 3: Develop capabilities to model upsides, downsides,
potential barriers and/or, reaction of society or regulators to new public
policy or technology solutions for climate change and gamify climate now-
and future-casting.
TECHNOLOGY CENTERS | HOMELAND SECURITY (DHS.GOV)
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EMERGING COMPUTING PARADIGMS
MISSION IMPACTS:
Increase data processing speed
for faster, real-time analysis and
decision making
The Von Neumann architecture implemented on a silicon chip is the engine of
the present-day information technology revolution. It is the basis for exploring
derivatives, such as parallel and distributed computing, and continues to produce
significant capability in the conventional computing space. While the U.S. continues
to invest in and advance digital computing, trends suggest
that current technology is expected to fall short of meeting
requirements of future computing needs. Big data centric
applications, like simulation and AI, demand improved
performance, and the need for them is growing at the same
time as Moore’s Law is breaking down in silicon-based
computing. Data heavy applications like extreme sensor
data streams and embedded Internet of Things (IoT) require
low energy consumption and efficiency in computationally
intensive algorithms. The needs of these kinds of innovations
are increasingly mismatched to current forms of general-
purpose chips, which suffer from memory bandwidth due to
the physical separation between processing and memory units.
There are, however, a number of emerging computing architecture platforms (e.g.,
quantum, neuromorphic, optical, etc.) on the horizon, better aligned with emerging
application needs, that have the potential to significantly accelerate performance,
efficiency, cost, while reducing power consumption. These next-generation computing
paradigms are deserving of our vigilant attention.
Most AI applications run in a Cloud. The learning phase, for which large datasets
are necessary, is done in the Cloud, and inference tasks are performed on the same
assets. Given the increasing demand for intelligent devices, such a scheme is not
sustainable in the long run. The data centers will not be able to sustain the load
and part of that load will need to be allocated to the edge devices themselves.
This is the current challenge that research teams are taking on: to enable running
inference tasks at the edge, thanks to dedicated hardware accelerators. However,
having accelerators dedicated to inference tasks at the edge is only the first step.
The future challenge will be to perform the learning phase
locally as well. This will require advances in performance,
efficiency, cost and power consumption, only envisioned
available in next-generation computing architectures and
technologies.
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The need to improve current-generation conventional computing paradigms while
preparing for next-generation computing paradigms, provides two classes of research
activities under the Emerging Computing Paradigms topic:
(1) Engineering and architectural analysis of specialized digital computing
derivatives (e.g., parallel, distributed, edge, etc.) and special purpose
chips (e.g., AI accelerators, graphics processing units, tensor processing
units, etc.).
(2) Understanding the likely trajectory of relevant hardware and software
technologies in next generation computing paradigms (e.g., quantum,
neuromorphic, extreme parallelism, etc.), as well as preparing for
experiments with these technologies.
Emerging Computing Paradigms Focus Areas and Technical Objectives:
Focus Area 1: Ubiquitous Computing – This focus area aims to enable tasks with
aggressive performance requirements (e.g., simulation, AI, real-time control systems,
etc.) to be performed anywhere – in the cloud, locally (on Prem), or at the operational
edge. We also aim to understand computing architectures and supercomputing
advances that will enable DHS to leverage data for enhanced real-time decision
making.
•
Technical Objective 1: Identify key research challenges for DHS missions
using multiple networked devices on multi-cloud, inter-cloud, edge,
supercomputing, and visualization of capabilities and multi-modal
interfaces.
•
Technical Objective 2: Identify key research challenges for scaling data-
driven applications deployed in a distributed networked environment and
that require efficient compute over high loads of streaming data, some of
which may belong to different parties.
•
Technical Objective 3: Understand how DHS use cases centered on
“Big Compute” may be further enhanced by next-generation computing
capabilities, such as leading-edge industry AI accelerator chip capabilities.
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Focus Area 2: Next-generation Computing Capabilities – This focus area aims to
examine developments in post-Moore computing and potential applications for DHS
use cases.
•
Technical Objective 1: Demonstrate a quantum[-inspired] use case on
commercial capabilities (e.g., Azure, D-Wave). For example, investigate
optimization using quantum computers for DHS specific problems such as
simulation, searching, or AI.
•
Technical Objective 2: Understand the scope and magnitude of long-term
threats that may emerge if large-scale quantum computing or neuromorphic
computing are fully realized and, in particular, monitor post-quantum
encryption advances.
•
Technical Objective 3: Investigate the state of neuromorphic technology,
articulate the challenges and opportunities in major areas of neuromorphic
technology (e.g., materials, devices, neuromorphic circuits, neuromorphic
algorithms, and applications), and project the potential dual-use
capabilities/threats of combining quantum and neuromorphic computing.
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NOVEL MATERIALS AND
SECURE MANUFACTURING
MISSION IMPACTS:
Identify new security concerns
from novel materials; develop
self-healing materials to increase
resilience to disasters
The future impacts of novel materials and manufacturing are quickly gaining
interest in the United States and abroad due to the projected impact of these
areas on innovation and the ability to adapt technologies at an accelerated pace.
Advanced materials are artificial materials with unique and novel properties
of interest, and advanced manufacturing is the use of
innovative technologies and methodologies for improved
competitiveness in the manufacturing sectors.
39
Advanced
manufacturing is comprised of techniques that can
produce highly customized products at lower cost, greater
efficiency, and less waste, which holds the promise to have
broad-reaching impacts to lowering cost and availability of
technologies for DHS use. S&T is interested in harnessing
the potential of advanced materials that could help drive
down cost and improve suitability of these materials for
use in DHS operational environments. As advances are
discovered, applying these to DHS mission spaces will be
vital to providing improved capability to screen, interdict, and
protect against threats.
Novel materials and advanced manufacturing capabilities, however, can create new
threats, such as 3-D printed weapons and new attack vectors like backdoor entry points
in embedded electronics.
40
Other forces, such as limited supply chains can also impact
the threat space. The microelectronics or the semiconductor-based integrated circuit
safety and supply chain has garnered much national attention in the last decade. This is
due to the migration of the manufacturing base from the United States to other countries
along with the uptick in malicious actors threatening to cause havoc on U.S. infrastructure.
A recent Executive Order 14017 on “America’s Supply Chains”
41
assigns DHS the
responsibility of building resilient supply chains and securing microelectronics while
combatting trafficking in counterfeit, fake, and maliciously affected chips and preventing
their entrance into the country.
42
Novel materials and advanced manufacturing have the potential to reduce cost and
provide enhanced capabilities and benefits, such as self-healing materials and 3-D printed
critical parts across multiple DHS mission spaces. At the same time, these advances in
materials and manufacturing can also pose new threats or attack vectors. A report from
the Homeland Security Advisory Council indicates that future advancements in 3-D printing
39
Reding, D.F. and Eaton, J. NATO Science & Technology Organization. 2020. Science & Technology Trends 2020-2040 – Exploring the S&T
Edge. p. 104. <https://www.sto.nato.int/publications/Management%20Reports/2020_TTR_Public_release_final.pdf>
40
Department of Homeland Security Homeland Security Advisory Council. 2020. “Final Report of the Emerging Technologies Subcommittee:
3D-Printing.” <https://www.dhs.gov/sites/default/files/publications/final_report_hsac_emerging_technology_subcommittee_3dprint-
ing_508_compliant.pdf>
41
Executive Office of the President. 2021. E.O. 14017 – America’s Supply Chains. <https://www.federalregister.gov/docu-
ments/2021/03/01/2021-04280/americas-supply-chains>
42
U.S. federal statute enacted by the 117th U.S. Congress – <
https://democrats-science.house.gov/chipsandscienceact
>
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can pose a threat to the security of the U.S. in the next three to 10 years
43
across
multiple different domains such as embedded electronics, safety critical parts, and
biological tissue engineering. These advances can pose challenges to DHS mission
spaces due to the potential ease of sabotaging critical parts, concealing illicit objects,
creating untraceable weapons, spoofing biometrics, etc.
Novel Materials and Secure Manufacturing
Focus Areas and Technical Objectives:
Focus Area 1: Novel Materials Applications – This focus area aims to adapt to
understand and assess application of novel materials in multiple DHS mission spaces.
•
Technical Objective 1: Develop use-case scenarios to help further explore
the application of novel materials within DHS mission spaces. For example,
self-healing materials have multiple, potential applications in the DHS mission
space for blast mitigation and recovery, fire, and water resistance, etc.
•
Technical Objective 2: Identify, track, and assess the development and
applicability of “smart” materials for use in homeland security environments
to meet the need for cost-effective, multi-use materials. Examples are
materials that could be components of wearable sensors to monitor the
health and safety of DHS personnel.
•
Technical Objective 3: Identify areas of security concern and consequences
from novel materials to homeland security missions with a focus on strategic
hazards and threat vectors, such as easier dispersion of threats such as a
chemical, biological, radiological, nuclear, and explosive, or CBRNE, agent.
Focus Area 2: Advanced Manufacturing Security and Threats – As manufacturing
technologies evolve, we must understand the security impacts to both supply chains
and the goods that are used by the American people, as well as the potential ways
these processes can be misused.
•
Technical Objective 1: Assess the threats, potential unintended
consequences, and impact of 3-D printing on security and DHS missions.
Three-dimensional printing has advanced to a stage where objects can be
printed directly from a wide variety of materials, including materials used for
explosives, making it more complex to fully characterize the integrity of, or
discern them from commodity products.
•
Technical Objective 2: Identify approaches to detect, mitigate and prevent
the threat of semiconductor-based integrated circuit safety and the supply
chain. The continuous emergence of new vulnerabilities in microelectronics
design, fabrication, test, and lifecycle necessitates innovative research into
technologies that will efficiently detect these vulnerabilities, provide end-
to-end lifecycle assurance and authentication, and improve supply chain
resiliency.
43
Department of Homeland Security Homeland Security Advisory Council. 2020. “Final Report of the Emerging Technologies Subcommittee:
3D-Printing.” p. 11. <https://www.dhs.gov/sites/default/files/publications/final_report_hsac_emerging_technology_subcommittee_3d-
printing_508_compliant.pdf>
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SOCIAL SCIENCES
MISSION IMPACTS:
Gain understanding of
motivations behind human-
based threats; enable the
acceptance of new technologies
into DHS missions
Developing a scientific understanding of how individuals, small groups, and
organizations affect threats, prevention, deterrence, resilience, security, and recovery
activities related to the homeland security mission is a massive but vitally important
undertaking. Social sciences focus on the root causes of behavior at individual,
organizational, and institutional levels and represent numerous fields including
sociology, economics, psychology, criminology, or political
science to name a few. Many of the challenges faced by
DHS are not easily or appropriately solved by technology,
or, at least not discoverable by the implementation of
technology. Social sciences share an analytic focus on the
behavior, attitudes, beliefs, and practices of people and
their organizations, communities, and institutions. Social
scientists employ the scientific method using mixed research
approaches based on systematic use of evidence to enable
better understanding of the motivations, actions, and
potential risks or threats posed by individuals, institutional
or group actors. Finally, by examining past successes and
failures of DHS mission related programs, policies, actions,
or decisions, social and behavioral scientists can systematically determine what led
to these results and how they can be replicated, avoided, or improved.
Social sciences are important to DHS – we must understand the nature of threats
and risks, as well as how the Department’s responses to these threats and risks
can be most effective. In this area, combatting terrorism, human trafficking, child
exploitation, and targeted violence, and helping to build a fair, orderly, and humane
immigration system, are among the Department’s priority missions and an integral
part of S&T Tech Centers’ work in social sciences.
To enable mission success, we must build knowledge and deepen our understanding
of the unique human, social, societal, and behavioral drivers of these unique crimes,
risks, and threats. To uncover the nature, causes, and correlation of these issues
also enhances DHS mission capabilities and leads to more informed and successful
methods, processes, policies, etc. to combat and prevent crimes and threats to the
United States.
Additionally, understanding individual and organizational decisions that explain
responses to these threats is equally important. Whether technologies are
accepted and adopted by public workforces is critical for successful integration of
technology into our missions and those of other federal, state, and local government
organizations. Private industry has used behavioral economics, particularly in
manufacturing, to study this problem for many years, but no body of knowledge has
previously attempted to address this problem in the public sector. Finally, measuring
the effectiveness of mitigating threats through systematic evaluation and evidence is
vital to the future success of DHS responses and activities.
Understanding and mapping the causes and consequences of social structures and
processes is critical, as is understanding the continuously evolving social landscapes
and their implications on DHS missions. Using these insights to produce the
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knowledge and tools necessary will enable the
Department to help manage risk, find remedies
for ills, and prepare for change in future. These
challenges not only necessitate complex,
interdisciplinary efforts, but they also require
the specialized techniques and knowledge that
social sciences bring to bear on issues of this
scale.
Additionally, as technical, societal, and
geopolitical landscapes continue to evolve and
reshape our world, understanding the human
reactions/responses/aspects and the social
and societal implications of these changes
will enable us to be better prepared and
provide evidence to inform policy and strategy
decision-makers on a host of issues whether it is for our workforce, the integration of
technology advances in our missions, or the responses to new or emerging threats.
Social Sciences Focus Areas and Technical Objectives:
Focus Area 1: Motivations and Drivers – This focus area aims to increase our
understanding of the underlying motivations and drivers of specific human-centric
DHS missions and produce the knowledge, fundamental understanding, and tools
necessary to manage risk, find remedies for ills, and prepare for change in the future
of DHS missions.
•
Technical Objective 1: Analyze, describe, and explain continuously evolving
human-centric threat landscapes and their implications on DHS missions,
and map the causes and consequences of social structures and processes.
Homeland security challenges require specialized techniques and
knowledge such as knowledge on “ultra-rare” events where occurrences are
too low to employ traditional statistical techniques as applied to strategic
communication or terrorism events.
•
Technical Objective 2: Uncover and explain the motivations underpinning
key DHS mission areas and solutions. Human behavior and social
phenomena are central to DHS missions such as terrorism and targeted
violence, human trafficking, cybersecurity incidents, or illegal immigration.
•
Technical Objective 3: Investigate and develop new social science
methods, data, and analysis techniques that allow DHS to describe and
examine mission area problems consistently, quantitatively, and objectively.
This allows DHS to systematically address problems, determine cause
and effect, and understand emerging themes and threats in detail while
creating conditions for future scientific inquiry and growth of a broader
homeland security corpus of knowledge that is transparent and based in
empirical data.
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Focus Area 2: Changing Behavioral and Social Implications – This focus area aims
to improve our awareness and understanding of how changes in the technology
landscape (particularly as science and technology continues to evolve) impact social
interactions, behaviors, and threat vectors.
•
Technical Objective 1: Describe the digital landscape of environments/
platforms of social engagement, to include evolving technologies and
ecosystems around social media, metaverse / gamification / immersive
technologies.
•
Technical Objective 2: Identify and analyze how potential changes in
human behavior and the confluence of social change across physical and
cyber space (i.e., changes in human behavior when one is online, online in
a group, anonymous, etc.) may exacerbate existing and create new threat
vectors, as well as the potential impacts to DHS missions.
•
Technical Objective 3: Ascertain the differences in early warning signs/
indicators given these environments/platforms and social interfaces and
identify DHS capabilities to address current and emerging threats and
risks.
Focus Area 3: Technology Acceptance and Limitations – This focus area aims to
advance the acceptance of new technologies into DHS missions.
•
Technical Objective 1: Understand why and how the public, organizations,
and workforces, including government programs, accept or reject new
technology.
•
Technical Objective 2: Identify ways humans best utilize new technologies,
including how they interact with digital interfaces, and create methods for
incorporating lessons learned into DHS operations.
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APPENDIX A: PRIORITIES
AND FOCUS AREAS
Advanced Sensing
•
Signature Exploitation and Detection
•
Sensor Integration
•
Emerging Sensing Technologies
Artificial Intelligence (AI) & Autonomous Systems (AS)
•
Trustworthy AI/AS
•
Adversarial AI
•
Advanced Applications of AI/AS
Biotechnology
•
Worldwide Developments in Biotechnology
•
Existing and Emerging Biological Agent Detection
Communications & Cyber Resiliency
•
Data-Centric Security
•
Software and Hardware Assurance
•
Communications and Network Resiliency
Data, Modeling, and Simulation Sciences
•
Advanced Data Analytics Capabilities
•
Advanced Modeling and Simulation Capabilities
•
Combined Data Analytics and Simulation Capabilities
•
Data Ecosystem
APPENDIX A: PRIORITIES
AND FOCUS AREAS
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Digital Identity & Trust
•
Digital Identity
•
Privacy Enhancing Technologies
•
Trust and Safety
Earth Systems Sciences
•
Worldwide Developments in Earth System Science and Climate Innovations
•
Earth System Monitoring and Detection Capabilities
•
Disaster Adaptation and Resilience Capabilities
Emerging Computing Paradigms
•
Ubiquitous Computing
•
Next-Generation Computing Capabilities
Novel Materials & Secure Manufacturing
•
Novel Materials Applications
•
Advanced Manufacturing Security and Threats
Social Sciences
•
Motivations and Drivers
•
Changing Behavior and Social Implications
•
Technology Acceptance & Limitations
iv
APPENDIX B: ACRONYM LIST
5G = Fifth-generation Technology
6G = Sixth-generation Technology
AI = Artificial Intelligence
AR = Augmented Reality
AS = Autonomous Systems
CBP = Customs and Border Protection
CBRNE = Chemical, Biological, Radiological, Nuclear and Explosives
CHIPS Act = Creating Helpful Incentives to Produce Semiconductors for America Act
CPS = Cyber Physical Systems
C-UAS = Counter-Unmanned Aircraft System
DHS = Department of Homeland Security
DL = Deep Learning
DNA = Deoxyribonucleic Acid
EO = Executive Order
ESS = Earth Systems Science
HF = High Frequency
HPC = High Performance Computing
HSE = Homeland Security Enterprise
IaC/PL = Infrastructure as Code/Pilot Light
ICAM = Identity, Credential, and Access Management
I/O = Input-output Requirements
IoT = Internet of Things
ML = Machine Learning
NATO = North Atlantic Treaty Organization
OMB = Office of Management and Budget
OSTP = Office of Science and Technology Policy
OT = Operational Technologies
PCR = Polymerase Chain Reaction
PLEO = Proliferated Low Earth Orbit Satellite
QIS = Quantum Information Science
R&D = Research and Development
RNA = Ribonucleic Acid
S&T = Science and Technology Directorate
SBOM = Software Bill of Materials
SME = Subject Matter Expert
SOAR = Security Orchestration and Automated Response
TCD = Technology Centers Division
TRL = Technology Readiness Level
TSA = Transportation Security Administration
UAS = Unmanned Aircraft System
VR = Virtual Reality
V2X = Vehicle-to-Everything
XAI = Explainable Artificial Intelligence
XG = Next-Generation Technologies: 6G, 7G, etc.
XR = Cross Reality
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