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DeepAttack: A Deep Learning Based Oracle-less Attack on Logic Locking

Authors:: Raj, A. , Avula, N. , Das, P. , Šišejković, D. , Merchant, F. , Acharyya, A.
Book Title:: Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS)
Status:: accepted for publication
Date:: Jan. 2023
Language:: English
Abstract:: Logic locking is one of the most promising design-for-trust techniques for protecting intellectual property from reverse engineering, IP piracy, and modification throughout the electronic supply chain. However, oracle-less deobfuscation attacks that do not require an activated chip have been successful in obtaining the secret key of locked designs. This requires a detailed determination of the extent of vulnerability available in obfuscated circuitry. In this paper, we propose the oracle-less DeepAttack; an attack on logic locking that is capable of extracting the activation key of the locked netlist using a deep learning model. Based on the evaluation on ISCAS-85 and EPFL benchmarks, DeepAttack achieves an average key prediction accuracy of 93.39%, outperforming the oracle-less state-of-the-art attacks SAIL, Snapshot, and OMLA by 21.28, 10.73, and 3.84 percentage points, respectively.
Download:: BibTeX