Paper
5 May 2022 Density peak-based clustering of industrial control protocols for reverse engineering
Di Tong, Yongjun Wang
Author Affiliations +
Proceedings Volume 12245, International Conference on Cryptography, Network Security, and Communication Technology (CNSCT 2022); 122450C (2022) https://doi.org/10.1117/12.2635863
Event: International Conference on Cryptography, Network Security, and Communication Technology (CNSCT 2022), 2022, Sanya, China
Abstract
Message clustering is the first and most crucial step in protocol reverse engineering, and the accuracy of protocol clustering directly affects protocol format extraction and state machine inference. The existing text protocol clustering methods do not apply to industrial control protocols, and the number of clusters and cluster centers cannot be determined automatically. The n-gram model is used to extract the protocol message features and construct the message feature vector for the clustering algorithm, which preserves the feature information in the protocol messages; density peak clustering is used to avoid the problem that the initial number of clusters and cluster centers cannot be determined automatically, and the automatic clustering of industrial control protocols is realized. It is tested on three commonly used industrial control protocol datasets, Modbus, DNP3, and S7common, and achieves good results on two metrics, purity and F1 score.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Di Tong and Yongjun Wang "Density peak-based clustering of industrial control protocols for reverse engineering", Proc. SPIE 12245, International Conference on Cryptography, Network Security, and Communication Technology (CNSCT 2022), 122450C (5 May 2022); https://doi.org/10.1117/12.2635863
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling

Control systems

Binary data

Reverse engineering

Feature extraction

Computer security

Control systems design

Back to Top