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Filters: Author is Nahar, Amit  [Clear All Filters]
2017-04-20
Ahmadi, Ali, Bidmeshki, Mohammad-Mahdi, Nahar, Amit, Orr, Bob, Pas, Michael, Makris, Yiorgos.  2016.  A Machine Learning Approach to Fab-of-origin Attestation. Proceedings of the 35th International Conference on Computer-Aided Design. :92:1–92:6.

We introduce a machine learning approach for distinguishing between integrated circuits fabricated in a ratified facility and circuits originating from an unknown or undesired source based on parametric measurements. Unlike earlier approaches, which seek to achieve the same objective in a general, design-independent manner, the proposed method leverages the interaction between the idiosyncrasies of the fabrication facility and a specific design, in order to create a customized fab-of-origin membership test for the circuit in question. Effectiveness of the proposed method is demonstrated using two large industrial datasets from a 65nm Texas Instruments RF transceiver manufactured in two different fabrication facilities.