Evaluating the Resilience of Face Recognition Systems Against Malicious Attacks

This paper presents an experiment designed to test the resilience of several user verification systems based on face recognition technology against simple identity spoofing methods, such as trying to gain access to the system by using mobile camera shots of the users, their ID cards, or social media photos of them that are available online. We also aim at identifying the compression threshold above which a photo can be used to gain access to the system. Four major user verification tools were tested: Keyemon and Luxand Blink on Windows and Android Face Unlock and FaceLock on Android. The results show all tested systems to be vulnerable to even very crude attacks, indicating that the technology is not ready yet for adoption in applications where security rather than user convenience is the main concern

Evaluating the Resilience of Face Recognition Systems Against Malicious Attacks

This paper presents an experiment designed to test the resilience of several user verification systems based on face recognition technology against simple identity spoofing methods, such as trying to gain access to the system by using mobile camera shots of the users, their ID cards, or social media photos of them that are available online. We also aim at identifying the compression threshold above which a photo can be used to gain access to the system. Four major user verification tools were tested: Keyemon and Luxand Blink on Windows and Android Face Unlock and FaceLock on Android. The results show all tested systems to be vulnerable to even very crude attacks, indicating that the technology is not ready yet for adoption in applications where security rather than user convenience is the main concern

Hill-Climbing Attack based on the Uphill Simplex Algorithm and its Application to Signature Verification

Abstract. A general hill-climbing attack to biometric systems based on a modification of the downhill simplex algorithm is presented. The scores provided by the matcher are used in this approach to adapt iteratively an initial estimate of the attacked template to the specificities of the client being attacked. The proposed attack is evaluated on a competitive feature-based signature verification system over both the MCYT and the BiosecurID databases (comprising 330 and 400 users, respectively). The results show a very high efficiency of the hill-climbing algorithm, which successfully bypassed the system for over 90 % of the attacks with a remarkably low number of scores needed.