Ising-PUF: A machine learning attack resistant PUF featuring lattice like arrangement of Arbiter-PUFs

A concept of Ising-PUF, a novel PUF structure that utilizes chaotic behavior of mutually interacting small PUFs, is proposed. Ising-PUF consists of a lattice like arrangement of small PUFs, each of which contains a spin register that stores the response of the small PUF, which also serves as a challenge of its neighbors. The spin patterns that develop along time determine the 1-bit response of the Ising-PUF. Utilizing state-memorizing nature of the spin registers, Ising-PUF attains a challenge hysteresis, i.e., allowing sequence of challenge inputs that continuously stimulate its chaotic behavior, which provides the drastically large challenge-to-response space. Experimental results demonstrate nearly ideal metrics; inter-chip Hamming distance (HD) of 50.1% and inter-environment HD of 2.26%. Further, Ising-PUF is remarkably tolerant to machine learning attacks, demonstrating that, even with a deep neural network using a 50k training cRPs, the prediction accuracy remains 50%, which is comparable to a random guess.

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