MLMSA: Multi-Label Multi-Side-Channel-Information enabled Deep Learning Attacks on APUF Variants. (arXiv:2207.09744v1 [cs.CR])

To improve the modeling resilience of silicon strong physical unclonable
functions (PUFs), in particular, the APUFs, that yield a very large number of
challenge response pairs (CRPs), a number of composited APUF variants such as
XOR-APUF, interpose-PUF (iPUF), feed-forward APUF (FF-APUF),and OAX-APUF have
been devised. When examining their security in terms of modeling resilience,
utilizing multiple information sources such as power side channel information
(SCI) or/and reliability SCI given a challenge is under-explored, which poses a
challenge to their supposed …

attacks channel deep learning information side-channel