IP Soft Core Hardware Trojan Detection Method Based on Grayscale Graph Analysis
With the refinement of the division of labor in chip design,manufacturing,and packaging processes,the use of third-party Intellectual Property(IP)soft cores for secondary development can significantly improve design efficiency and reduce duplication of work.However,while a large number of non-autonomous controllable IP soft cores are used to accelerate the design,it also puts the chip at risk of being implanted in hardware Trojans in the design stage,and the chip security is difficult to guarantee.Current IP soft core security detection methods mainly rely on functional testing,code coverage,and flip rate analysis,or keyword matching at the semantic level,and cannot detect encrypted IP soft cores.Based on the hardware analysis of the Trojan structure and its implementation features in IP soft cores,this study uses the feature differences between non-controllable IP and"Golden"IP soft cores in Register Transfer Level(RTL)code grayscale maps,and constructs the"Golden"soft core set based on Trust-Hub.Additionally,it proposes a detection model and an algorithm for IP soft hardware Trojans based on grayscale map features.The experiment takes the functional tampering IP soft core B19-T100 as the object,and by adjusting the appropriate imaging matrix parameters,the hardware Trojan detection is realized by block matching and comparison.The detection accuracy of the proposed algorithm is 97.18%.A total of 18 samples of five categories such as B19,B15,and S38417 are tested,and the average detection accuracy is greater than 92%.The results demonstrate that the algorithm can effectively identify the hardware Trojan,and the detection accuracy and applicability are strong.
国家科技期刊平台
NSTL
万方数据
