SACReD: An Attack Framework on SAC Resistant Delay-PUFs leveraging Bias and Reliability Factors

Abstract

The S-PUF and S <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</inf> -PUF designs (proposed in IN-DOCRYPT2019) are one of the contemporary composite strong PUF candidates of the Delay-PUF family that exhibit two distinguishing and notable attributes – (i) it is one of the few PUF constructions which is guided by theoretical analysis of the Strict Avalanche Criteria (SAC) property and not by ad-hoc choices; and (ii) though its construction is quite similar to XOR PUFs, it has very good reliability property unlike the former design due to the introduction of Maiorana-McFarland (M-M) Bent Function. These make S <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</inf> -PUF to be a very good candidate for strong PUF proposals and an interesting target from the point of view of attackers. In this work, we testify that a novel reliability based machine learning attack can be launched in this architecture against the original authors’ claim. Though it is challenging to launch a classical or reliability based ML attack directly, we leverage the bias introduced by the AND operation in the M-M bent function due to its non-linearity property. Our proposed novel attack framework, SACReD, is able to break $S_{8}, S_{10}$ and $S_{12}-$PUF designs, which were originally assumed to be secure, by taking only 400K Challenge-Response Pairs.