I-Corps: Many-Core Computing for Biometrics Liveness Detection

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Biometric recognition (for example, fingerprint recognition) offers many advantages over traditional methods (such as passwords or security cards) for identification and verification required for secure access. The algorithms enabling biometric recognition can be computationally intensive, but users of biometrics systems require identification and authentication processes to be rapid, convenient, and accurate. In this proposal, the team?s specific focus is on creating a fingerprint liveness algorithm (which detects if a fingerprint presented is live skin or a spoof) to improve accuracy and security of fingerprint detection. By enabling this algorithm to be calculated on the cloud, the team will be able to improve speed of execution and/or accuracy of scans and make the overall authentication system more feasible for use in different contexts.In this proposal, the team proposes to undertake a project involving the transfer of parallelization of biometric applications on many-core platforms from research to industry. The benefits and uses of many-core computing are well studied already, as are advanced biometrics algorithms. The work being proposed will apply research related to many-core computing and parallelization to the field of biometrics in order to demonstrate performance improvements for a viable product. Specifically, the team will focus on a fingerprint liveness detection algorithm that can be used in conjunction with identification or verification. The work will help improve the security offered by such systems, and will demonstrate that established methods and concepts in many-core and cloud computing can be applied to this field.