In the era of big data, novel tools and methods need to be developed to protect our homeland against threats and vulnerabilities.

The CAOE focuses on generating predictive methods, systems and tools that can be tactically used by Homeland Security for more effective real-time decision-making, risk assessment and economic evaluations.

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COVID-19 impacts on health, behavior, resilience and trade

The future economic effects of COVID-19 are highly uncertain. Early predictions showed COVID-19 may plunge the U.S. into an economic recession. However, current conditions make it difficult to predict the length and severity of the pandemic and identify any long-term economic repercussions.

Assessing threat landscapes through red teaming

The risk of chemical warfare (CW) has increased in recent years. The Homeland Security Enterprise (HSE) has a need to identify state and non-state actors likely to pursue the development of CW as well determining the factors that identify the use of CW. These factors include the states overall strategic orientation to CW, the types of CW agents likely to be pursued and the other activities that would accompany CW development.

Overhead view of people going through a TSA checkpoint.

Improving airport checkpoint efficiency

The combination of current airport space constraints and limited Transportation Security Officers coupled with projected increases in air travelers and rising number of security threats will put more pressure on TSA staff and resources.

Protecting privacy with deep-learning tools

n the era of big data, the unprecedented speed and volume of data collection poses benefits as well as risks. The large amount of collected data contains critical information for daily homeland security operations as well as potential usage to enhance analytical capabilities for better decision-making.

Creating new methods to preserve data privacy

Data sharing within DHS agencies and across components is challenging because of both privacy and security concerns. Many agencies remove sensitive but critical information from reports or documents to preserve privacy while others refrain from sharing data that could be useful to homeland security efforts due to the challenges of meeting and maintaining privacy requirements.

Guarding sensitive data with secure computations

The use of personal information is essential for homeland security efforts, but it is also a balancing act securing this information and protecting individual privacy concerns that exist in the sharing and use of sensitive information such as surveillance images/videos, biometrics, and other individual-identifying data that is collected and generated from multiple sources across the Homeland Security Enterprise.

Modeling disruptions to the Marine Transportation System (MTS)

The Marine Transportation System (MTS) is a vital part of the nation’s supply chain. The vast majority of U.S. overseas trade is carried by the MTS and its operation plays a major role in the nation’s GDP and overall prosperity. An efficient MTS reduces congestion in ports, railways, and roadways, reduces costs to consumers and business owners, and promotes homeland and national security.

Assessing trustworthiness of AI-enabled systems

The advancement of artificial intelligence (AI), including machine learning (ML) and increasingly autonomous systems, has resulted in a push for technical standards that can assess the trustworthiness of these technologies. Developing standards have the potential to drive the design and development of trustworthy systems, and to more cost-effectively evaluate AI-enabled systems during technology acquisition or regulation.

Four people looking over a document who are all gathered around a table with open laptops

Improving effectiveness of procurement processes

Properly managed contractor/supplier management systems include a robust performance monitoring and improvement mechanism. The Department of Homeland Security (DHS) is beginning to invest artificial intelligence/machine learning (AIML) technology into the Contractor Performance Assessment Reporting System (CPARS).

Fire truck and ambulance at an accident cene

Optimization for disaster response including COVID-19

The risk of natural disasters and national emergencies drives the need for real-time decision-making to guide the allocation of critical resources and the design of resilient and effective supply chains to respond effectively to these events.

Silhouettes of people, with backpacks, walking in a line to the right, led by children

Predicting cross-border migration patterns

The challenge of securing the safe, orderly, and humane processing of migrants who arrive at our Southwest border is renderedincreasingly complicated due to the growing volume and substantial variations of this influx of migrants.

Hand of a person holding a carry-on bag in an terminal.

Validating risk models

Efforts for homeland security face constantly evolving adversary tactics, rapid technological advances and changes in the overall environment. The challenge of preparing for new tactics is a very real risk for homeland security. 

View of pickup truck driving toward viewer on a gravel road in the Sonoran Desert with saguaros and creosote bush.

Improving detection of threats at border operations

Securing the border between Ports-of-Entry (POEs) uses a variety of both physical and virtual infrastructure to detect, deter and disrupt pathways. The U.S. government is making substantial investments in both types of infrastructure to improve their capacity to prevent illegal smuggling and trafficking.

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Identifying biological weapons threats post COVID-19

The COVID-19 pandemic has raised concerns on the state of biological warfare (BW) defense strategies. This includes identifying countries most likely to pursue the development of these BW capabilities, including the development of viable BW programs.

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People wearing masks waiting in line with spacing between them

COVID-19 impacts on health, behavior, resilience and trade

The future economic effects of COVID-19 are highly uncertain. Early predictions showed COVID-19 may plunge the U.S. into an economic recession. However, current conditions make it difficult to predict the length and severity of the pandemic and identify any long-term economic repercussions.

Assessing threat landscapes through red teaming

The risk of chemical warfare (CW) has increased in recent years. The Homeland Security Enterprise (HSE) has a need to identify state and non-state actors likely to pursue the development of CW as well determining the factors that identify the use of CW. These factors include the states overall strategic orientation to CW, the types of CW agents likely to be pursued and the other activities that would accompany CW development.

Overhead view of people going through a TSA checkpoint.

Improving airport checkpoint efficiency

The combination of current airport space constraints and limited Transportation Security Officers coupled with projected increases in air travelers and rising number of security threats will put more pressure on TSA staff and resources.

Protecting privacy with deep-learning tools

n the era of big data, the unprecedented speed and volume of data collection poses benefits as well as risks. The large amount of collected data contains critical information for daily homeland security operations as well as potential usage to enhance analytical capabilities for better decision-making.

Creating new methods to preserve data privacy

Data sharing within DHS agencies and across components is challenging because of both privacy and security concerns. Many agencies remove sensitive but critical information from reports or documents to preserve privacy while others refrain from sharing data that could be useful to homeland security efforts due to the challenges of meeting and maintaining privacy requirements.

Guarding sensitive data with secure computations

The use of personal information is essential for homeland security efforts, but it is also a balancing act securing this information and protecting individual privacy concerns that exist in the sharing and use of sensitive information such as surveillance images/videos, biometrics, and other individual-identifying data that is collected and generated from multiple sources across the Homeland Security Enterprise.

Modeling disruptions to the Marine Transportation System (MTS)

The Marine Transportation System (MTS) is a vital part of the nation’s supply chain. The vast majority of U.S. overseas trade is carried by the MTS and its operation plays a major role in the nation’s GDP and overall prosperity. An efficient MTS reduces congestion in ports, railways, and roadways, reduces costs to consumers and business owners, and promotes homeland and national security.

Assessing trustworthiness of AI-enabled systems

The advancement of artificial intelligence (AI), including machine learning (ML) and increasingly autonomous systems, has resulted in a push for technical standards that can assess the trustworthiness of these technologies. Developing standards have the potential to drive the design and development of trustworthy systems, and to more cost-effectively evaluate AI-enabled systems during technology acquisition or regulation.

Four people looking over a document who are all gathered around a table with open laptops

Improving effectiveness of procurement processes

Properly managed contractor/supplier management systems include a robust performance monitoring and improvement mechanism. The Department of Homeland Security (DHS) is beginning to invest artificial intelligence/machine learning (AIML) technology into the Contractor Performance Assessment Reporting System (CPARS).

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Education initiatives

We’re creating programs for both future and current Homeland Security professionals. Our focus is diverse student engagement, DHS career pathways, and ongoing training.