When Human cognitive modeling meets PINs: User-independent inter-keystroke timing attacks
This poses a serious threat to real-world applications by enabling large-scale attacks on PINs, though it is incremental as it builds on existing timing attack concepts.
The paper tackles the problem of user-independent inter-keystroke timing attacks on PINs by proposing a method based on a human cognitive model, achieving performance significantly better than random guessing in various online attack settings.
This paper proposes the first user-independent inter-keystroke timing attacks on PINs. Our attack method is based on an inter-keystroke timing dictionary built from a human cognitive model whose parameters can be determined by a small amount of training data on any users (not necessarily the target victims). Our attacks can thus be potentially launched on a large scale in real-world settings. We investigate inter-keystroke timing attacks in different online attack settings and evaluate their performance on PINs at different strength levels. Our experimental results show that the proposed attack performs significantly better than random guessing attacks. We further demonstrate that our attacks pose a serious threat to real-world applications and propose various ways to mitigate the threat.