Formal Verification Approach to Detect Always-On Denial of Service Trojans in Pipelined Circuits

被引:2
作者
Ponugoti, Kushal K. [1 ]
Srinivasan, Sudarshan K. [1 ]
Mathure, Nimish [1 ]
机构
[1] North Dakota State Univ, Dept Elect & Comp Engn, Fargo, ND 58105 USA
来源
2021 28TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS, AND SYSTEMS (IEEE ICECS 2021) | 2021年
基金
美国国家科学基金会;
关键词
Formal Verification; Hardware Trojans; Denial of Service; Always-On;
D O I
10.1109/ICECS53924.2021.9665617
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Always-On Denial of Service (DoS) Trojans with power drain payload can be disastrous in systems where on-chip power resources are limited. These Trojans are designed so that they have no impact on system behavior and hence, harder to detect. A formal verification method is presented to detect sequential always-on DoS Trojans in pipelined circuits and pipelined microprocessors. Since the method is proof-based, it provides a 100% accurate classification of sequential Trojan components. Another benefit of the approach is that it does not require a reference model, which is one of the requirements of many Trojan detection techniques (often a bottleneck to practical application). The efficiency and scalability of the proposed method have been evaluated on 36 benchmark circuits. The most complex of these benchmarks has as many as 135,898 gates. Detection times are very efficient with a 100% rate of detection, i.e., all Trojan sequential elements were detected and all non-trojan sequential elements were classified as such.
引用
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页数:6
相关论文
共 18 条
  • [1] Becker GT, 2013, LECT NOTES COMPUT SC, V8086, P197, DOI 10.1007/978-3-642-40349-1_12
  • [2] Burch J. R., 1994, Computer Aided Verification. 6th International Conference, CAV '94. Proceedings, P68
  • [3] Z3: An efficient SMT solver
    de Moura, Leonardo
    Bjorner, Nikolaj
    [J]. TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS, 2008, 4963 : 337 - 340
  • [4] Hardware Trojan Detection Using Changepoint-Based Anomaly Detection Techniques
    Elnaggar, Rana
    Chakrabarty, Krishnendu
    Tahoori, Mehdi B.
    [J]. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2019, 27 (12) : 2706 - 2719
  • [5] Fern N, 2017, ASIA S PACIF DES AUT, P598, DOI 10.1109/ASPDAC.2017.7858389
  • [6] Unveiling the ISCAS-85 benchmarks: A case study in reverse engineering
    Hansen, MC
    Yalcin, H
    Hayes, JP
    [J]. IEEE DESIGN & TEST OF COMPUTERS, 1999, 16 (03): : 72 - 80
  • [7] Overcoming an Untrusted Computing Base: Detecting and Removing Malicious Hardware Automatically
    Hicks, Matthew
    Finnicum, Murph
    King, Samuel T.
    Martin, Milo M. K.
    Smith, Jonathan M.
    [J]. 2010 IEEE SYMPOSIUM ON SECURITY AND PRIVACY, 2010, : 159 - 172
  • [8] Kumar K. Mahesh, 2015, 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO), P1, DOI 10.1109/ISCO.2015.7282319
  • [9] Silicon Demonstration of Hardware Trojan Design and Detection in Wireless Cryptographic ICs
    Liu, Yu
    Jin, Yier
    Nosratinia, Aria
    Makris, Yiorgos
    [J]. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2017, 25 (04) : 1506 - 1519
  • [10] Salmani H, 2013, 2013 IEEE 31ST INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD), P471, DOI 10.1109/ICCD.2013.6657085