The Intelligence Advanced Research Projects Activity (IARPA) Odin Program has awarded research and engineering firm SRI International a four-year, $12.5 million contract to research and develop “dynamic biometrics”. IARPA has said the “dynamic biometrics” should be able to better detect attempts to evade or deceive biometric security systems, such as fingerprint, iris, and face scanners.The body says the innovation needs to focus on critical weaknesses in current generation biometric security systems, and that boosting detection would expand biometric use cases beyond low-risk applications.”While governments and businesses across the world have taken steps to adopt fingerprint, iris, and face biometrics systems for a broad range of uses such as travel checkpoints, facility access points, and identity verification and cyberauthentication, their use has been hampered by the low confidence these systems provide for so-called presentation attacks.”Under the terms of the agreement, SRI International will forge and deliver a prototype Multi-physiological Joint Optimization and Liveness Nuances for Identity Ratification system (MJÖLNIR) to defeat known and unknown presentation attacks. SRI's multidisciplinary team for the project includes experts in human physiology; dynamic 3-D imaging; 3-D shape and behavioral dynamics modeling; and system development, evaluation, and deployment.Under the Odin Program, the SRI team is researching dynamic biometrics systems and techniques to dramatically improve the presentation attack detection capabilities of biometric systems by imaging, measuring, and analyzing real-time physiological responses of living tissue to external and internal stimuli. By analyzing such factors as changes in heart rate, perspiration, and blood flow both within tissues being used for biometric identification and across other body regions, the hope is that an improved system will reliably detect whether these biometric tissues are real or being faked. The SRI team's approach in the Odin program is to scan tissue below the skin surface to detect dynamic physiological information that conventional scanners — which rely on static surface images of human tissue — do not detect.