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This paper discusses the challenges and approaches for privacy-preserving multibiometric authentication in cloud-based applications. The authors propose a user-specific performance-dependent fusion strategy and secure multiparty computation protocols to address security and privacy threats. The results show that the proposed approach ensures privacy while achieving accurate authentication.
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FACULTY OF ENGINEERING COSIC Privacy-Preserving Multibiometric Authentication in Cloud Authors: Christina-Angeliki Toli, Abdelrahaman Aly and Bart Preneel KU Leuven, ESAT/COSIC and imec Euro S&P 2017 2nd IEEE European Symposium on Security and Privacy Paris, France 27 April 2017
Motivation • Cloud-based biometric applications • Privacy-by-design approaches • Link the pattern recognition area with applied crypto • Biometrics integration is still an “open problem” • Addressing the topic from a multimodal perspective, taking into account impacts on performance • Secure Multiparty Computation (MPC)
Layout Figure: Multimodal Biometric Authentication in Cloud Environment
Contribution • Re-use the prior stored unimodal templates, avoiding the auxiliary temporary or permanent storage • A user-specific performance-dependent weighted score level fusion strategy • MPC protocols for cloud in a privacy-preserving decentralized manner • Threats from parties with competing interest, collusion models, security and privacy perspectives • Entity learns only the {0,1} value of the final result
Resutls • Authentication/identification by setting up a FAR or FRR-dependent fusion • The operation is dynamic • Stored templates, matching, normalized and fusion scores are inaccessible • Privacy of user's information from the output party • Limitation: Identification is time-consuming processes • Future work: Fusion accuracy, computational and communication complexity and efficiency
Contact : Thank you for your attention ! http://www.esat.kuleuven.be/cosic/ Christina-Angeliki Toli ctoli@esat.kuleuven.be