Journal article
Characterization of In-Cone Logic Locking Resiliency Against the SAT Attack
IEEE transactions on computer-aided design of integrated circuits and systems, v 39(8), pp 1607-1620
Aug 2020
Abstract
The resiliency of in-cone logic locking techniques to the satisfiability (SAT) attack is characterized in this paper. An analysis of the parameters of the SAT solver that impact security and a characterization of the effect netlist topology has on the security of the circuit is presented. The analysis of SAT solver parameters and logic structure is used to develop three novel logic locking gate selection algorithms based on maximum fanout free cones (MFFCs) and gate controllability for circuits implementing XOR, look-up table (LUT), and 2\times 1 MUX-based logic obfuscation. The XOR, LUT, and MUX MFFC-based algorithms resulted in an average increase of, respectively, 61.8%, 123.6%, and 38.5% in the minimum number of iterations required to complete the SAT attack across 1,000 different variable orderings of the netlist while applying the locking techniques to 5% of the gates within the netlist. In addition, the SAT attack resiliency and output corruption of the developed algorithms are compared with out-of-cone locking techniques.
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Details
- Title
- Characterization of In-Cone Logic Locking Resiliency Against the SAT Attack
- Creators
- Kyle Juretus - Drexel UniversityIoannis Savidis - Drexel University
- Publication Details
- IEEE transactions on computer-aided design of integrated circuits and systems, v 39(8), pp 1607-1620
- Publisher
- IEEE
- Grant note
- Drexel Ventures Innovation Fund 32 CFR 168a / Air Force Office of Scientific Research, National Defense Science and Engineering Graduate Fellowship (10.13039/100014037) CNS-1648878; CNS-1751032 / National Science Foundation (10.13039/100000001)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000550655600006
- Scopus ID
- 2-s2.0-85068165317
- Other Identifier
- 991019168276604721
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Interdisciplinary Applications
- Engineering, Electrical & Electronic