Remote Protocol Vulnerability Discovery for Intelligent Transportation Systems (ITS)

ITS are typical intelligent applications today. To attain the goals of safer and more efficient transportation systems, discovering vulnerability of ITS plays an important role. In this paper, the threat source of ITS is analyzed based on the communication view of ITS. A Protocol Vulnerability Discovery Framework is presented for securing ITS applications based on fuzzing test and automatic analysis, which support machine learning, genetic algorithms and pattern recognition technique. Finally a typical case of vulnerability discovery on Open Network Video Interface Forum (ONVIF) protocol in ITS is also given for demonstrating the effectiveness and practicability of the proposed Protocol Vulnerability Discovery Framework. Experiment result from the case shows the Protocol Vulnerability Discovery Framework support finding the vulnerability of ITS in an effective manner. Challenges from combining the different protocol fuzzing patterns and analysis patterns into one framework, and limitations are also reported and discussed. Finally, the paper concludes with future research directions and applications of proposed framework in ITS.