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Acceleration of Spatial Correlation Based Hardware Trojan Detection Using Shared Grids Ratio

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11989))

Abstract

Due to mostly economic reasons almost all countries including the developed ones have to handle integrated circuit designs to a foreign fab for manufacturing, which raises the security issues like intentional malicious circuit (hardware Trojan) insertion by an adversary. A previously proposed method to address these security issues detects hardware Trojan using the spatial correlations in accordance with delay based side channel analysis. However, it is never applied to full circuits and it requires too many path delay computations to select correlated path pairs. In this paper, we first apply the method and present the results for full circuits and then, the method is accelerated by proposing a novel path selection criterion which avoids the computation of path delays. In terms of detection success, the resultant method performs similar to the previous one, but in a much faster fashion.

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References

  1. Adee, S.: The hunt for the kill switch. IEEE Spectr. 45(5), 34–39 (2008)

    Article  Google Scholar 

  2. Agarwal, A., Blaauw, D., Zolotov, V.: Statistical timing analysis for intra-die process variations with spatial correlations. In: Proceedings of the 2003 IEEE/ACM International Conference on Computer-Aided Design, p. 900. IEEE Computer Society (2003)

    Google Scholar 

  3. Banga, M., Hsiao, M.S.: A region based approach for the identification of hardware trojans. In: 2008 IEEE International Workshop on Hardware-Oriented Security and Trust, pp. 40–47. IEEE (2008)

    Google Scholar 

  4. Bayrakci, A.A.: Stochastic logical effort as a variation aware delay model to estimate timing yield. Integr. VLSI J. 48, 101–108 (2015)

    Article  Google Scholar 

  5. Bhasin, S., Danger, J.L., Guilley, S., Ngo, X.T., Sauvage, L.: Hardware trojan horses in cryptographic IP cores. In: 2013 Workshop on Fault Diagnosis and Tolerance in Cryptography, pp. 15–29. IEEE (2013)

    Google Scholar 

  6. Brglez, F.: A neural netlist of 10 combinational benchmark circuits. In: Proceedings of the IEEE ISCAS: Special Session on ATPG and Fault Simulation, pp. 151–158 (1985)

    Google Scholar 

  7. Bushnell, M., Agrawal, V.: Essentials of Electronic Testing for Digital, Memory and Mixed-Signal VLSI Circuits, vol. 17. Springer, Boston (2004). https://doi.org/10.1007/b117406

    Book  Google Scholar 

  8. Esirci, F.N., Bayrakci, A.A.: Hardware trojan detection based on correlated path delays in defiance of variations with spatial correlations. In: Proceedings of the Conference on Design, Automation & Test in Europe, pp. 163–168. European Design and Automation Association (2017)

    Google Scholar 

  9. ITRS Commitee: International technology roadmap for semiconductors (ITRS) 2011 report. http://www.itrs2.net/2011-itrs.html

  10. Nangate: 45nm open cell library. http://www.nangate.com/

  11. Narasimhan, S., et al.: Hardware trojan detection by multiple-parameter side-channel analysis. IEEE Trans. Comput. 62(11), 2183–2195 (2012)

    Article  MathSciNet  Google Scholar 

  12. Nowroz, A.N., Hu, K., Koushanfar, F., Reda, S.: Novel techniques for high-sensitivity hardware trojan detection using thermal and power maps. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 33(12), 1792–1805 (2014)

    Article  Google Scholar 

  13. Rai, D., Lach, J.: Performance of delay-based trojan detection techniques under parameter variations. In: 2009 IEEE International Workshop on Hardware-Oriented Security and Trust, pp. 58–65. IEEE (2009)

    Google Scholar 

  14. Tehranipoor, M., Koushanfar, F.: A survey of hardware trojan taxonomy and detection. IEEE Des. Test Comput. 27(1), 10–25 (2010)

    Article  Google Scholar 

  15. Tehranipoor, M., Wang, C.: Introduction to Hardware Security and Trust. Springer, New York (2011). https://doi.org/10.1007/978-1-4419-8080-9

    Book  Google Scholar 

  16. Yoshimizu, N.: Hardware trojan detection by symmetry breaking in path delays. In: 2014 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST), pp. 107–111. IEEE (2014)

    Google Scholar 

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Correspondence to Fatma Nur Esirci .

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Esirci, F.N., Bayrakci, A.A. (2020). Acceleration of Spatial Correlation Based Hardware Trojan Detection Using Shared Grids Ratio. In: Slamanig, D., Tsigaridas, E., Zafeirakopoulos, Z. (eds) Mathematical Aspects of Computer and Information Sciences. MACIS 2019. Lecture Notes in Computer Science(), vol 11989. Springer, Cham. https://doi.org/10.1007/978-3-030-43120-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-43120-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43119-8

  • Online ISBN: 978-3-030-43120-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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