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

QUACK: Hindering Deserialization Attacks via Static Duck Typing

Yaniv David (Columbia University), Neophytos Christou (Brown University), Andreas D. Kellas (Columbia University), Vasileios P. Kemerlis (Brown University), Junfeng Yang (Columbia University)

Read More

Towards generic backward-compatible software upgrades for COSPAS-SARSAT EPIRB 406...

Ahsan Saleem (University of Jyväskylä, Finland), Andrei Costin (University of Jyväskylä, Finland), Hannu Turtiainen (University of Jyväskylä, Finland), Timo Hämäläinen (University of Jyväskylä, Finland)

Read More

AAKA: An Anti-Tracking Cellular Authentication Scheme Leveraging Anonymous Credentials

Hexuan Yu (Virginia Polytechnic Institute and State University), Changlai Du (Virginia Polytechnic Institute and State University), Yang Xiao (University of Kentucky), Angelos Keromytis (Georgia Institute of Technology), Chonggang Wang (InterDigital), Robert Gazda (InterDigital), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

Read More

Aligning Confidential Computing with Cloud-native ML Platforms

Angelo Ruocco, Chris Porter, Claudio Carvalho, Daniele Buono, Derren Dunn, Hubertus Franke, James Bottomley, Marcio Silva, Mengmei Ye, Niteesh Dubey, Tobin Feldman-Fitzthum (IBM Research)

Read More