PROJECT TITLE :
Attack of Mechanical Replicas: Liveness Detection With Eye Movements
This paper investigates liveness detection techniques in the realm of eye movement biometrics. We have a tendency to investigate a selected state of affairs, in which an impostor constructs a man-made replica of the human eye. 2 attack eventualities are considered: one) the impostor will not have access to the biometric templates representing authentic users, and instead utilizes average anatomical values from the relevant literature and 2) the impostor gains access to the complete biometric database, and is ready to use precise anatomical values for every individual. In this paper, liveness detection is performed at the feature and match score levels for many existing kinds of eye movement biometric, based mostly on totally different aspects of the human visual system. The flexibility of every technique to differentiate between live and artificial recordings is measured by its corresponding false spoof acceptance rate, false live rejection rate, and classification rate. The results counsel that eye movement biometrics are highly immune to circumvention by artificial recordings when liveness detection is performed at the feature level. Unfortunately, not all techniques provide feature vectors that are suitable for liveness detection at the feature level. At the match score level, the accuracy of liveness detection depends highly on the biometric techniques employed.
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