Biblio

The design methods and the detection methods for Hardware Trojan develop rapidly. Existing trustiness verification methods are effective to obviously malicious HT but no effect on Stealthy Trojan. Stealthy Trojan is an advanced attack form and hard to be detected. In this paper, we analyze the characteristic of stealthy Trojan and propose a static detection method based on feature analysis. The results on ISCAS benchmarks show that the proposed method can detect the Stealthy Trojan node and is convenient to be implanted into other scalable verification framework.

Software verification has been well applied in safety critical areas and has shown the ability to provide better quality assurance for modern software. However, as lines of code and complexity of software systems increase, the scalability of verification becomes a challenge. In this paper, we present an automatic software verification framework TSV to address the scalability issues: (i) the extended structural abstraction and property-guided program slicing to solve large-scale program verification problem, saving time and memory without losing accuracy; (ii) automatically select different verification methods according to the program and property context to improve the verification efficiency. For evaluation, we compare TSV's different configurations with existing C program verifiers based on open benchmarks. We found that TSV with auto-selection performs better than with bounded model checking only or with extended structural abstraction only. Compared to existing tools such as CMBC and CPAChecker, it acquires 10%-20% improvement of accuracy and 50%-90% improvement of memory consumption.