ICEPRE: ICS Protocol Reverse Engineering via Data-Driven Concolic Execution


연구 분야: Analysis



학회: Proceedings of the ACM on Software Engineering, Volume 2, Issue ISSTA


초록

With the advancement of digital transformation, Industrial Control Systems (ICS) are becoming increasingly open and intelligent. However, inherent vulnerabilities in ICS protocols pose significant security threats to devices and systems. The proprietary nature of ICS protocols complicates the security analysis and deployment of protective mechanisms for ICS. Protocol reverse engineering aims to infer the syntax, semantics, and state machines of protocols in the absence of official specifications. Traditional protocol reverse engineering tools face considerable limitations due to the lack of executable environments, incomplete inference strategies, and low-quality network traffic. In this paper, we present ICEPRE, a novel data-driven protocol reverse engineering method based on concolic execution, which uniquely integrates network trace with static analysis. Unlike conventional methods that rely on executable environments, ICEPRE statically tracks the program's parsing process for specific input messages. Furthermore, we employ an innovative field boundary inference strategy to infer the protocol's syntax by analyzing how the protocol parser handles different fields. Our evaluation demonstrates that ICEPRE significantly outperforms previous protocol reverse engineering tools in field boundary inference, achieving an F1 score of 0.76 and a perfection score of 0.67, while DynPRE, BinaryInferno, Nemeys, and Netzob yield (0.65, 0.35), (0.42, 0.14), (0.39, 0.09), and (0.27, 0.10), respectively. These results underscore the superior overall performance of our method. Additionally, ICEPRE exhibits exceptional performance with proprietary protocols in real-world scenarios, highlighting its practical applicability in downstream applications.


Author Profile
Yibo Qu

Institute of Information Engineering at Chinese Academy of Sciences Beijing China

Austria
Author Profile
Dongliang Fang

Institute of Information Engineering at Chinese Academy of Sciences Beijing China

Austria
Author Profile
Zhen Wang

Institute of Information Engineering at Chinese Academy of Sciences Beijing China

Austria

📄 논문 정보

발행 연도 2025년
인용수 0
출판 국가 China, Austria
사이트 ACM
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