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Content Assessment: Accelerating Biometric Recognition? Artificial Intelligence, Machine Learning, and Biometric Data Fusion
Information - 90%
Insight - 94%
Relevance - 85%
Objectivity - 90%
Authority - 92%
90%
Excellent
A short percentage-based assessment of the qualitative benefit of the recent HDIAC report highlighting advancements in biometric recognition.
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Background Note: The Homeland Defense & Security Information Analysis Center (HDIAC) serves as the U.S. national clearinghouse for worldwide scientific and technical information in eight technical focus areas including biometrics. State-of-the-Art Reports from the HDIAC provide in-depth analyses of current technologies within its technical focus areas. The following report highlights recent advances in biometric recognition technologies and the application of AI and ML to recognition tasks in multimodal identification systems. Introduced through the lens of governmental application, the dense descriptions and details in the report may be beneficial for cybersecurity, information governance, and legal discovery professionals as they seek to better understand advances in the field of biometrics.
Homeland Defense & Security Information Analysis Center Report*
Artificial Intelligence (AI) and Machine Learning (ML) in Biometric Data Fusion
By Dr. Abdul Rahman, Dr. Steven R. Knudsen, Deanna Milonas, Daniel Fleming, and John Clements
Abstract
This State-of-the-Art Report focuses on recent advances in biometric recognition technologies and the application of artificial intelligence and machine learning to recognition tasks in multimodal identification systems. Multimodal systems use “feature-level” data fusion (e.g., periocular and gait recognition), which provides faster reference set retrieval across identity templates and significantly improves recognition accuracy over a unimodal system. Specifically, the recent field of biometric data fusion holds promise to deliver improved biometric data sample capture and analysis to the warfighter regardless of disguised, altered, or occluded facial characteristics. The use of convolutional neural networks, deep neural networks, and recurrent neural networks in biometric data fusion is also explained in this report. In addition, topics in leading-edge biometric recognition research are also presented.
Introduction Extract
Biometric recognition and identification technologies are used widely across the federal government, primarily by the Department of Defense (DoD), Department of Homeland Security (DHS), Department of Justice (typically but not exclusively by the Federal Bureau of Investigation), and the Department of Commerce. In the Department of Commerce, research by the National Institute of Standards and Technology (NIST) supports the security and interoperability of federal and military biometric programs. Across the national security enterprise, biometric systems are a critical resource for forward-deployed U.S. forces as well as homeland defense operations. Biometrics support the detection and prevention of illegal border entry; help secure access to sensitive DoD and federal government networks and facilities; and aid civilian law enforcement in identifying, tracking, and detaining criminal suspects.
Artificial Intelligence AI and Machine Learning ML in Biometric Data Fusion
About HDIAC
The Homeland Defense & Security Information Analysis Center (HDIAC) is a U.S. Department of Defense (DoD) IAC sponsored by the Defense Technical Information Center (DTIC). HDIAC is operated by SURVICE Engineering Company under contract FA8075-21-D-0001 and is one of the three next-generation IACs transforming the DoD IAC program: HDIAC, Defense Systems Information Analysis Center (DSIAC), and Cybersecurity and Information Systems Information Analysis Center (CSIAC).
HDIAC serves as the U.S. national clearinghouse for worldwide scientific and technical information in 8 technical focus areas: alternative energy, biometrics, CBRN defense, critical infrastructure protection, cultural studies, homeland defense & security, medical, and weapons of mass destruction. As such, HDIAC collects, analyzes, synthesizes, and disseminates related technical information and data for each of these focus areas. These efforts facilitate a collaboration between scientists and engineers in the homeland defense and security systems community while promoting improved productivity by fully leveraging this same community’s respective knowledge base. HDIAC also uses information obtained to generate scientific and technical products, including databases, technology assessments, training materials, and various technical reports.
State-of-the-Art Reports (SOARs)—one of HDIAC’s information products—provide in-depth analysis of current technologies, evaluate and synthesize the latest technical information available, and provide a comprehensive assessment of technologies related to HDIAC’s technical focus areas. Specific topic areas are established from collaboration with the greater defense systems community and vetted with DTIC to ensure the value-added contributions to Warfighter needs.
Additional Reading
- Defining Cyber Discovery? A Definition and Framework
- A Global AI Superpower? The United Kingdom’s National Artificial Intelligence Strategy
Source: ComplexDiscovery