VulHunter: A Discovery for Unknown Bugs Based on Analysis for Known Patches in Industry Internet of Things
Fu Xiao, Letian Sha, Zai-Ping Yuan, Ruchuan Wang · IEEE Transactions on Emerging Topics in Computing · 2017
With Industry 4.0 or Internet of Things (IoT) era coming, security problem plays a key role in Industry Internet of Things (IIoT), especially vulnerability discovery and analysis. However, how to discover some new bugs or vulnerabilities based on analysis for known patches is an open issue. To our best knowledge, few effective methods are established, especially for vulnerabilities in software or firmware of IIoT. In order to deal with these problems, we propose VulHunter, a discovery for unknown vulnerabilities based on analysis for known vulnerability patch packs in IIoT. Some new algorithms in binary comparison, pack extractor and background semantic solver are designed and realized in this paper. To verify our proposal, experimental tests are verified in a large number of vulnerabilities in IIoT applications and devices, and test results demonstrated that we can discover some new bugs based on analysis for known patch pack as expected, some of which can be picked to report CVE list.