An evaluation of indirect attacks and countermeasures in fingerprint verification systems

Biometric recognition systems are vulnerable to numerous security threats. These include direct attacks to the sensor or indirect attacks, which represent the ones aimed towards internal system modules. In this work, indirect attacks against fingerprint verification systems are analyzed in order to better understand how harmful they can be. Software attacks via hill climbing algorithms are implemented and their success rate is studied under different conditions. In a hill climbing attack, a randomly generated synthetic template is presented to the matcher, and is iteratively modified based on the score output until it is accepted as genuine. Countermeasures against such attacks are reviewed and analyzed, focusing on score quantization as a case study. It is found that hill climbing attacks are highly effective in the process of creating synthetic templates that are accepted by the matcher as genuine ones. We also find that score quantization drastically reduces the attack success rate. We analyze the hill climbing approach over two state-of-the-art fingerprint verification systems: the NIST Fingerprint Image Software 2, running on a PC and a prototype system fully embedded in a smart card (Match-on-Card). Results of both systems are obtained using a sub corpus of the publicly available MCYT database.

► We test hill-climbing attacks to minutiae-based fingerprint verification systems.
► Synthetic templates are iteratively generated until breaking user accounts.
► The systems from NIST and a smartcard using Match-on-Card are highly vulnerable.
► Attack success rate depends on the system, attack configuration, and fingerprint.
► Countermeasures as score quantization drastically reduce the vulnerability.