Zhengxiong Luo (Tsinghua University), Kai Liang (Central South University), Yanyang Zhao (Tsinghua University), Feifan Wu (Tsinghua University), Junze Yu (Tsinghua University), Heyuan Shi (Central South University), Yu Jiang (Tsinghua University)

Automatic protocol reverse engineering is essential for various security applications. While many existing techniques achieve this task by analyzing static network traces, they face increasing challenges due to their dependence on high-quality samples. This paper introduces DynPRE, a protocol reverse engineering tool that exploits the interactive capabilities of protocol servers to obtain more semantic information and additional traffic for dynamic inference. DynPRE first processes the initial input network traces and learns the rules for interacting with the server in different contexts based on session-specific identifier detection and adaptive message rewriting. It then applies exploratory request crafting to obtain semantic information and supplementary samples and performs real-time analysis. Our evaluation on 12 widely used protocols shows that DynPRE identifies fields with a perfection score of 0.50 and infers message types with a V-measure of 0.94, significantly outperforming state-of-the-art methods like Netzob, Netplier, FieldHunter, BinaryInferno, and Nemesys, which achieve average perfection and V-measure scores of (0.15, 0.72), (0.16, 0.73), (0.15, 0.83), (0.15, -), and (0.31, -), respectively. Furthermore, case studies on unknown protocols highlight the effectiveness of DynPRE in real-world applications.

View More Papers

WIP: Modeling and Detecting Falsified Vehicle Trajectories Under Data...

Jun Ying, Yiheng Feng (Purdue University), Qi Alfred Chen (University of California, Irvine), Z. Morley Mao (University of Michigan and Google)

Read More

Secure Control of Connected and Automated Vehicles Using Trust-Aware...

H M Sabbir Ahmad, Ehsan Sabouni, Akua Dickson (Boston University), Wei Xiao (Massachusetts Institute of Technology), Christos Cassandras, Wenchao Li (Boston University)

Read More

dRR: A Decentralized, Scalable, and Auditable Architecture for RPKI...

Yingying Su (Tsinghua university), Dan Li (Tsinghua university), Li Chen (Zhongguancun Laboratory), Qi Li (Tsinghua university), Sitong Ling (Tsinghua University)

Read More