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Securing 3rd-Party HDL IP: a Feasibility Study Using Evolutionary Methods

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Abstract

The increasing globalization of the intellectual property (IP) industry has added a new risk for designers when using 3rd-party programs. Malicious entities have more opportunities to insert Hardware Trojans (HT) into these 3rd-party IPs, which can often remain undetected by conventional testing procedures. Even in a case where these Trojans could be detected from a full testing suite, the time associated with running the full suite could be infeasible, or the full testing suite might not be available to the designer. This work performs a feasibility study on the use of evolutionary computing (EC) to evolve 3rd-party hardware design language (HDL) IPs to remove HT from an infected IP. We measure the strength and weaknesses of EC by testing different mutations schemes across various evolutionary goals, with the use of full and partial testing suites. The scalability of the approach is then shown in higher dimensions, while showing that the synthesized designs of the evolved programs have no additional overhead compared to the original uninfected code when tested in Vivado. We then conclude with some suggestions of future works in the area of targeted evolution on larger circuits containing more complex Hardware Trojans.

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Code Availability

The code for this work is available under the MIT license at https://github.com/king2b3/GP.

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Acknowledgements

The authors would like to thank Tyler Westland, Jenna King, Joshua Mayersky, Wayne Stegner, and Siddharth Barve for their help and feedback over the process of this work.

Funding

This research was funded by Defense Associated Graduate Student Innovators project number RY20-9. This material is based on research sponsored by the Air Force Research Laboratory and the Southwestern Council for Higher Education under Agreement FA8650-18-C-1191 P00005, and is PA approved along case number AFRL-2021-1299. The US Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation thereon.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH, 45221, USA

    Bayley King & Rashmi Jha

  2. Resilient and Agile Avionics Branch, Air Force Research Lab, Dayton, OH, 45433, USA

    Temesguen Kebede & David Kap

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  1. Bayley King
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  2. Rashmi Jha
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Correspondence to Bayley King.

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King, B., Jha, R., Kebede, T. et al. Securing 3rd-Party HDL IP: a Feasibility Study Using Evolutionary Methods. J Hardw Syst Secur 6, 17–31 (2022). https://doi.org/10.1007/s41635-022-00125-9

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