1 |
YANG K Y, HICKS M, DONG Q, et al. A2: analog malicious hardware[C]//Proceedings of the IEEE Symposium on Security and Privacy. Washington D. C., USA: IEEE Press, 2016: 18-37.
|
2 |
YANG Y P, YE J, CAO Y, et al. Survey: hardware Trojan detection for netlist[C]//Proceedings of the 29th Asian Test Symposium (ATS). Washington D. C., USA: IEEE Press, 2020: 1-6.
|
3 |
SALMANI H. COTD: reference-free hardware Trojan detection and recovery based on controllability and observability in gate-level netlist. IEEE Transactions on Information Forensics and Security, 2017, 12(2): 338- 350.
doi: 10.1109/TIFS.2016.2613842
|
4 |
HICKS M, FINNICUM M, KING S T, et al. Overcoming an untrusted computing base: detecting and removing malicious hardware automatically[C]//Proceedings of the IEEE Symposium on Security and Privacy. Washington D. C., USA: IEEE Press, 2010: 159-172.
|
5 |
STURTON C, HICKS M, WAGNER D, et al. Defeating UCI: building stealthy and malicious hardware[C]//Proceedings of the IEEE Symposium on Security and Privacy. Washington D. C., USA: IEEE Press, 2011: 64-77.
|
6 |
ZHANG J, YUAN F, WEI L X, et al. VeriTrust: verification for hardware trust. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2015, 34(7): 1148- 1161.
doi: 10.1109/TCAD.2015.2422836
|
7 |
YAO S, CHEN X M, ZHANG J, et al. FASTrust: feature analysis for third-party IP trust verification[C]//Proceedings of the IEEE International Test Conference (ITC). Washington D. C., USA: IEEE Press, 2015: 1-10.
|
8 |
WANG C. Analysis and modeling of hardware Trojans with few state points[C]//Proceedings of the 19th Annual Conference of Computer Engineering and Technology. Washington D. C., USA: IEEE Press, 2015: 276-281.
|
9 |
LU R J, SHEN H H, FENG Z H, et al. HTDet: a clustering method using information entropy for hardware Trojan detection. Tsinghua Science and Technology, 2021, 26(1): 48- 61.
doi: 10.26599/TST.2019.9010047
|
10 |
XIE X, SUN Y Y, CHEN H D, et al. Hardware Trojans classification based on controllability and observability in gate-level netlist. IEICE Electronics Express, 2017, 14(18): 20170682.
doi: 10.1587/elex.14.20170682
|
11 |
DHARMADHIKARI P, RAJU A, VEMURI R. Detection of sequential Trojans in embedded system designs without scan chains[C]//Proceedings of the IEEE Computer Society Annual Symposium on VLSI (ISVLSI). Washington D. C., USA: IEEE Press, 2018: 678-683.
|
12 |
KOK C H, OOI C Y, MOGHBEL M, et al. Classification of Trojan nets based on SCOAP values using supervised learning[C]//Proceedings of the IEEE International Symposium on Circuits and Systems. Washington D. C., USA: IEEE Press, 2019: 1-5.
|
13 |
HUANG K, HE Y. Trigger identification using difference-amplified controllability and dynamic transition probability for hardware Trojan detection. IEEE Transactions on Information Forensics and Security, 2020, 15, 3387- 3400.
doi: 10.1109/TIFS.2019.2946044
|
14 |
SU Y, SHEN H H, LU R J, et al. A stealthy hardware Trojan design and corresponding detection method[C]//Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS). Washington D. C., USA: IEEE Press, 2021: 1-6.
|
15 |
SHEN H H, TAN H Z, LI H W, et al. LMDet: a "naturalness" statistical method for hardware Trojan detection. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2018, 26(4): 720- 732.
doi: 10.1109/TVLSI.2017.2781423
|
16 |
LU R J, SHEN H H, SU Y, et al. GramsDet: hardware Trojan detection based on recurrent neural network[C]//Proceedings of the 28th Asian Test Symposium (ATS). Washington D. C., USA: IEEE Press, 2019: 111-1115.
|
17 |
MURALIDHAR N, ZUBAIR A, WEIDLER N, et al. Contrastive graph convolutional networks for hardware Trojan detection in third party IP cores[C]//Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust. Washington D. C., USA: IEEE Press, 2021: 181-191.
|
18 |
YAMASHITA K, KATO T, HASEGAWA K, et al. Effective hardware-Trojan feature extraction against adversarial attacks at gate-level netlists[C]//Proceedings of the 28th International Symposium on On-Line Testing and Robust System Design (IOLTS). Washington D. C., USA: IEEE Press, 2022: 1-7.
|
19 |
|
20 |
黄钊, 王泉杨, 杨鹏飞. 硬件木马: 关键问题研究进展及新动向. 计算机学报, 2019, 42(5): 993- 1017.
URL
|
|
HUANG Z, WAGN Q Y, YANG P F. Hardware Trojan: research progress and new trends on key problems. Chinese Journal of Computers, 2019, 42(5): 993- 1017.
URL
|
21 |
CHAKRABORTY R S, PAUL S, BHUNIA S. On-demand transparency for improving hardware Trojan detectability[C]//Proceedings of the IEEE International Workshop on Hardware-Oriented Security and Trust. Washington D. C., USA: IEEE Press, 2008: 48-50.
|
22 |
KAMHOUA C A, ZHAO H, RODRIGUEZ M, et al. A game-theoretic approach for testing for hardware Trojans. IEEE Transactions on Multi-Scale Computing Systems, 2016, 2(3): 199- 210.
doi: 10.1109/TMSCS.2016.2564963
|
23 |
SAAD W, SANJAB A, WANG Y P, et al. Hardware Trojan detection game: a prospect-theoretic approach. IEEE Transactions on Vehicular Technology, 2017, 66(9): 7697- 7710.
doi: 10.1109/TVT.2017.2686853
|
24 |
TEHRANIPOOR M, KOUSHANFAR F. A survey of hardware Trojan taxonomy and detection. IEEE Design & Test of Computers, 2010, 27(1): 10- 25.
|
25 |
赵剑锋, 史岗. 硬件木马研究动态综述. 信息安全学报, 2017, 2(1): 74- 90.
URL
|
|
ZHAO J F, SHI G. A Survey on the studies of Hardware Trojan. Journal of Cyber Security, 2017, 2(1): 74- 90.
URL
|
26 |
BHASIN S, REGAZZONI F. A survey on hardware Trojan detection techniques[C]//Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS). Washington D. C., USA: IEEE Press, 2015: 2021-2024.
|
27 |
|