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Logic Locking at the Frontiers of Machine Learning: A Survey on Developments and Opportunities

Authors:: Šišejković, D. , Reimann, L. M. , Moussavi, E. , Merchant, F. , Leupers, R.
Book Title:: IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SOC)
Date:: 2021
DOI:: 10.1109/VLSI-SoC53125.2021.9606979
Language:: English
Abstract:: In the past decade, a lot of progress has been made in the design and evaluation of logic locking; a premier technique to safeguard the integrity of integrated circuits throughout the electronics supply chain. However, the widespread proliferation of machine learning has recently introduced a new pathway to evaluating logic locking schemes. This paper summarizes the recent developments in logic locking attacks and countermeasures at the frontiers of contemporary machine learning models. Based on the presented work, the key takeaways, opportunities, and challenges are highlighted to offer recommendations for the design of next-generation logic locking.
Download:: BibTeX