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A Unified Submodular Framework for Multimodal IC Trojan Detection

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Information Hiding (IH 2010)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6387))

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Abstract

This paper presents a unified formal framework for integrated circuits (IC) Trojan detection that can simultaneously employ multiple noninvasive measurement types. Hardware Trojans refer to modifications, alterations, or insertions to the original IC for adversarial purposes. The new framework formally defines the IC Trojan detection for each measurement type as an optimization problem and discusses the complexity. A formulation of the problem that is applicable to a large class of Trojan detection problems and is submodular is devised. Based on the objective function properties, an efficient Trojan detection method with strong approximation and optimality guarantees is introduced. Signal processing methods for calibrating the impact of inter-chip and intra-chip correlations are presented. We propose a number of methods for combining the detections of the different measurement types. Experimental evaluations on benchmark designs reveal the low-overhead and effectiveness of the new Trojan detection framework and provides a comparison of different detection combining methods.

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References

  1. Agrawal, D., Baktir, S., Karakoyunlu, D., Rohatgi, P., Sunar, B.: Trojan detection using ic fingerprinting. In: S&P, pp. 296–310 (2007)

    Google Scholar 

  2. Alkabani, Y., Koushanfar, F.: Consistency-based characterization for ic trojan detection. In: ICCAD, pp. 123–127 (2009)

    Google Scholar 

  3. Banga, M., Chandrasekar, M., Fang, L., Hsiao, M.: Guided test generation for isolation and detection of embedded trojans in \(\sc{IC}s\). In: GLS-VLSI, pp. 363–366 (2008)

    Google Scholar 

  4. Banga, M., Hsiao, M.: A region based approach for the identification of hardware trojans. In: HOST, pp. 43–50 (2008)

    Google Scholar 

  5. Cao, Y., Clark, L.T.: Mapping statistical process variations toward circuit performance variability: an analytical modeling approach. In: DAC, pp. 658–663 (2005)

    Google Scholar 

  6. Chekuri, C., Pal, M.: A recursive greedy algorithm for walks in directed graphs. In: FOCS, pp. 245–253 (2005)

    Google Scholar 

  7. Das, A., Kempe, D.: Algorithms for subset selection in linear regression. In: STOC, pp. 45–54 (2008)

    Google Scholar 

  8. Defense Science Board (DSB) study on High Performance Microchip Supply (2005), http://www.acq.osd.mil/dsb/reports/2005-02-HPMS_Report_Final.pdf

  9. Feige, U.: A threshold of ln n for approximating set cover. Journal of ACM 45(4), 634–652 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  10. Jha, N., Gupta, S.: Testing of Digital Systems. Cambridge University Press, Cambridge (2003)

    Book  Google Scholar 

  11. Jin, Y., Makris, Y.: Hardware trojan detection using path delay fingerprint. In: HOST, pp. 51–57 (2008)

    Google Scholar 

  12. Koushanfar, F., Boufounos, P., Shamsi, D.: Post-silicon timing characterization by compressed sensing. In: ICCAD, pp. 185–189 (2008)

    Google Scholar 

  13. Krause, A., Guestrin, C.: Near-optimal observation selection using submodular functions. In: AAAI, pp. 1650–1654 (2007)

    Google Scholar 

  14. Kreinovich, V., Lakeyev, A., Rohn, J., Kahl, P.: Computational Complexity and Feasibility of Data Processing and Interval Computations. Kluwer Academic Publishers, Dordrecht (1997)

    MATH  Google Scholar 

  15. Leskovec, J., Krause, A., Guestrin, C., Faloutsos, C., VanBriesen, J., Glance, N.: Cost-effective outbreak detection in networks. In: SIGKDD, pp. 420–429 (2007)

    Google Scholar 

  16. Li, J., Lach, J.: At-speed delay characterization for IC authentication and trojan horse detection. In: HOST, pp. 8–14 (2008)

    Google Scholar 

  17. Liu, F.: A general framework for spatial correlation modeling in VLSI design. In: DAC, pp. 817–822 (2007)

    Google Scholar 

  18. Mossel, E., Roch, S.: On the submodularity of influence in social networks. In: STOC, pp. 128–134 (2007)

    Google Scholar 

  19. Murakami, A., Kajihara, S., Sasao, T., Pomeranz, I., Reddy, S.M.: A test structure for characterizing local device mismatches. In: ITC, p. 376 (2000)

    Google Scholar 

  20. Nelson, M., Nahapetian, A., Koushanfar, F., Potkonjak, M.: Svd-based ghost circuitry detection. In: Katzenbeisser, S., Sadeghi, A.-R. (eds.) IH 2009. LNCS, vol. 5806, pp. 221–234. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  21. Nemhauser, G., Wolsey, L., Fisher, M.: An analysis of the approximations for maximizing submodular set functions. Math. Programming 14, 265–294 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  22. Potkonjak, M., Nahapetian, A., Nelson, M., Massey, T.: Hardware trojan horse detection using gate-level characterization. In: DAC, pp. 688–693 (2009)

    Google Scholar 

  23. Rad, R., Plusquellic, J., Tehranipoor, M.: A sensitivity analysis of power signal methods for detecting hardware trojans under real process and environmental conditions. IEEE Trans. on Very Large Scale Integration (VLSI) Systems 99 (2009)

    Google Scholar 

  24. Rad, R., Wang, X., Plusquellic, J., Tehranipoor, M.: Power supply signal calibration techniques for improving detection resolution to hardware trojans. In: ICCAD, pp. 632–639 (2008)

    Google Scholar 

  25. Chakravarty, S., Thadikaran, P.: Simulation and generation of iddq tests for bridging faults in combinational circuits. IEEE Trans. on Computers 45(10), 1131–1140 (1996)

    Article  MATH  Google Scholar 

  26. Sabade, S., Walker, D.: IDDX-based test methods: A survey. ACM Trans. Design Automation of Electronic Systems 9(2), 159–198 (2004)

    Article  Google Scholar 

  27. Srivastava, A., Sylvester, D., Blaauw, D.: Statistical Analysis and Optimization for VLSI: Timing and Power. Springer, Heidelberg (2005)

    Google Scholar 

  28. Wei, S., Meguerdichian, S., Potkonjak, M.: Gate-level characterization: Foundations and hardware security applications. In: DAC (2010)

    Google Scholar 

  29. Yang, K., Cheng, K.T., Wang, L.: TranGen: A SAT-based ATPG for path-oriented transition faults. In: ASPDAC, pp. 92–97 (2004)

    Google Scholar 

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Koushanfar, F., Mirhoseini, A., Alkabani, Y. (2010). A Unified Submodular Framework for Multimodal IC Trojan Detection. In: Böhme, R., Fong, P.W.L., Safavi-Naini, R. (eds) Information Hiding. IH 2010. Lecture Notes in Computer Science, vol 6387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16435-4_2

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  • DOI: https://doi.org/10.1007/978-3-642-16435-4_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16434-7

  • Online ISBN: 978-3-642-16435-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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