Anonymity in Video Surveillance System
نویسندگان
چکیده
The widespread deployment of surveillance cameras has raised serious privacy concerns and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. To identify these individuals for protection, the most reliable approach is to use biometric signals such as iris scans as they are immutable and highly discriminative. If misused, these characteristics of biometrics can seriously defeat the goal of privacy protection. In this chapter, we propose an anonymous subject identification procedure based on iris scans for privacy-aware video surveillance. The anonymous subject identification procedure uses Homomorphic Encryption (HE) based protocols to verify membership of an incoming individual without knowing his/her true identity. To make HE-based protocols scalable to large biometric databases, we introduce the k-Anonymous Quantization (kAQ) framework to provide an effective and secure tradeoff of privacy and complexity. kAQ limits system’s knowledge of the incoming individual to k maximally dissimilar candidates in the database, where k is a design parameter that controls the amount of complexity-privacy tradeoff. The relationship between iris similarity and privacy is experimentally validated using a twin iris database. The effectiveness of the entire system is demonstrated based on a public iris biometric database. Ying Luo Center for Visualization & Virtual Environments, University of Kentucky e-mail: [email protected] Sen-ching S. Cheung Center for Visualization & Virtual Environments, University of Kentucky e-mail: [email protected] Shuiming Ye Center for Visualization & Virtual Environments, University of Kentucky e-mail: [email protected]
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