Toward the Generation of Test Vectors for the Detection of Hardware Trojan Targeting Effective Switching Activity

被引:2
作者
Mondal, Anindan [1 ]
Kalita, Debasish [1 ]
Ghosh, Archisman [1 ]
Roy, Suchismita [1 ]
Sen, Bibhash [1 ]
机构
[1] Natl Inst Technol Durgapur, Mahatma Gandhi Ave, Durgapur 713209, W Bengal, India
关键词
Hardware Trojan; Gate Level Netlist; test generation; switching activity; GENETIC ALGORITHM; SIDE-CHANNEL;
D O I
10.1145/3597497
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Hardware Trojans (HTs) are small circuits intentionally designed by an adversary for harmful purposes. These types of circuits are extremely difficult to detect. An HT often requires some specific signals to activate, which are almost impossible to discover. For this reason, test generation for side-channel analysis has gained significant attention in recent times and does not require HT activation. Such test generation techniques aim to generate a large amount of switching activity inside the HT circuit, increasing transient current measurement. However, such methods suffer from either long runtime or reliable results. In this work, a test generation technique is proposed based on the relative switching activity of the circuit to overcome the limitations of the existing works. Initially, the proposed technique measures the impact of each input on rare nets individually using random vector simulation. Potent inputs are selected to obtain a new set of test vectors that provide high relative switching inside a circuit. The proposed method is applied on 11 different ISCAS and 3 ITC 99 benchmark circuits. Experimental results endorse the efficacy of the proposed method outperforming traditional Hamming distance-based re-ordering techniques (up to 20x) while requiring a small runtime.
引用
收藏
页数:16
相关论文
共 28 条
  • [1] Chakraborty RS, 2009, LECT NOTES COMPUT SC, V5747, P396
  • [2] Hardware Trojan Horse Detection through Improved Switching of Dormant Nets
    Dhar, Tapobrata
    Roy, Surajit Kumar
    Giri, Chandan
    [J]. ACM JOURNAL ON EMERGING TECHNOLOGIES IN COMPUTING SYSTEMS, 2021, 17 (03)
  • [3] Francq J, 2015, DES AUT TEST EUROPE, P770
  • [4] Hasegawa K, 2018, IEEE ICCE
  • [5] Hasegawa K, 2016, IEEE INT ON LINE, P203, DOI 10.1109/IOLTS.2016.7604700
  • [6] Trigger Identification Using Difference-Amplified Controllability and Dynamic Transition Probability for Hardware Trojan Detection
    Huang, Kai
    He, Yun
    [J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2020, 15 (15) : 3387 - 3400
  • [7] Scalable Test Generation for Trojan Detection Using Side Channel Analysis
    Huang, Yuanwen
    Bhunia, Swarup
    Mishra, Prabhat
    [J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2018, 13 (11) : 2746 - 2760
  • [8] MERS: Statistical Test Generation for Side-Channel Analysis based Trojan Detection
    Huang, Yuanwen
    Bhunia, Swarup
    Mishra, Prabhat
    [J]. CCS'16: PROCEEDINGS OF THE 2016 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, 2016, : 130 - 141
  • [9] On Detecting Delay Anomalies Introduced by Hardware Trojans
    Ismari, D.
    Plusquellic, J.
    Lamech, C.
    Bhunia, S.
    Saqib, F.
    [J]. 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), 2016,
  • [10] Jain S. K., 1984, ACM IEEE 21st Design Automation Conference Proceedings 84 (cat. no. 84CH2049-5), P18, DOI 10.1109/DAC.1984.1585767