Biometric systems are widely used for authentication and identification. The False Match Rate (FMR) quantifies the probability of matching a biometric template to a non-corresponding template and serves as an indicato...
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ISBN:
(纸本)9798400714764
Biometric systems are widely used for authentication and identification. The False Match Rate (FMR) quantifies the probability of matching a biometric template to a non-corresponding template and serves as an indicator of the system robustness against security threats. We analyze biometric systems through two main contributions. First, we study untargeted attacks, where an adversary aims to impersonate any user in the database. We compute the number of trials needed for a successful impersonation and derive the critical population size ( i.e., the maximum database size) and critical (FMR) required to maintain security against untargeted attacks as the database grows. Second, we address the biometric birthday problem, which quantifies the probability that there exists two distinct users that collide ( i.e., can impersonate each other). We compute approximate and exact probabilities of collision and derive the associated critical population size and critical (FMR) to bound the risk of biometric collisions, particularly in large-scale databases. These thresholds provide actionable insights for designing biometric systems that mitigate the risks of impersonation and biometric collisions, particularly in large-scale databases. Nevertheless, our findings show that current systems fail to meet the required security level against untargeted attacks, even in small databases, and face significant challenges with the biometric birthday problem as databases grow.
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