EDSM-Based Binary Protocol State Machine Reversing
Source abstract
Abstract
Internet communication protocols define the behavior rules of network components when they communicate with each other. With the continuous development of network technologies, many private or unknown network protocols are emerging in endlessly various network environments. Herein, relevant protocol specifications become difficult or unavailable to translate in many situations such as network security management and intrusion detection. Although protocol reverse engineering is being investigated in recent years to perform reverse analysis on the specifications of unknown protocols, most existing methods have proven to be time-consuming with limited efficiency, especially when applied on unknown protocol state machines. This paper proposes a state merging algorithm based on EDSM (Evidence-Driven State Merging) to infer the transition rules of unknown protocols in form of state machines with high efficiency. Compared with another classical state machine inferring method based on Exbar algorithm, the experiment results demonstrate that our proposed method could run faster, especially when dealing with massive training data sets. In addition, this method can also make the state machines have higher similarities with the reference state machines constructed from public specifications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Network Security and Intrusion Detection · Smart Grid Security and Resilience · Advanced Malware Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (33)
Show source-provided references
1. A survey on emerging SDN and NFV security mechanisms for IoT systems10.1109/COMST.2018.2862350 ↗
2. Internet of things security: A top-down survey10.1016/j.comnet.2018.03.012 ↗
3. A cross layer protocol for fast identification of blocked tags in large-scale rfid systems10.32604/cmc.2020.010190 ↗
4. Unsupervised learning approach for network intrusion detection system using autoencoders10.1007/s11227-019-02805-w ↗
5. Distributed localization in wireless sensor networks under denial-of-service attacks10.1109/LCSYS.2020.3003789 ↗
6. A novel intrusion detection algorithm based on long short term memory network10.32604/jqc.2020.010819 ↗
7. Network packet filtering and deep packet inspection hybrid mechanism for IDS early packet matching
8. Solutions for deep packet inspection in industrial communications
9. Research on network traffic identification based on machine learning and deep packet inspection
10. A convolution-based system for malicious URLS detection10.32604/cmc.2020.06507 ↗
11. Towards automatic protocol field inference10.1016/j.comcom.2016.02.015 ↗
12. Inference of network unknown protocol structure using CSP (contiguous sequence pattern) algorithm based on tree structure
13. Message format and field semantics inference for binary protocols using recorded network traffic
14. Unsupervised field segmentation of unknown protocol messages10.1016/j.comcom.2019.06.013 ↗
15. Discoverer: Automatic protocol reverse engineering from network traces
16. Analyzing network protocols of application layer using hidden semi-markov model
17. Clustering of unknown protocol messages based on format comparison10.1016/j.comnet.2020.107296 ↗
18. Mining protocol state machines by interactive grammar inference
19. Towards automated protocol reverse engineering using semantic information
20. An automatic network protocol state machine inference method in protocol reverse engineering10.4028/www.scientific.net/AMM.513-517.2496 ↗
21. Automatic protocol reverse engineering using grammatical inference10.3233/JIFS-169294 ↗
22. PRETT: protocol reverse engineering using binary tokens and network traces10.1007/978-3-319-99828-2_11 ↗
23. A reverse engineering tool for extracting protocols of networked applications
24. Prospex: Protocol specification extraction
25. A survey of state merging strategies for DFA identification in the limit10.17345/triangle8.121-136 ↗
26. Optimal Petri net supervisor synthesis for forbidden state problems using marking mask10.1016/j.ins.2019.07.008 ↗
27. Results of the Abbadingo one DFA learning competition and a new evidence-driven state merging algorithm
28. What packets may come: Automata for network monitoring10.1145/373243.360221 ↗
29. Multiple sequence alignment10.1016/0022-2836(86)90252-4 ↗
30. A general method applicable to the search for similarities in the amino acid sequence of two proteins10.1016/0022-2836(70)90057-4 ↗
31. Traffic to protocol reverse engineering
32. Inference of regular languages using state merging algorithms with search10.1016/j.patcog.2004.03.027 ↗
33. K. J. Lang, “Faster algorithms for finding minimal consistent DFAs,” NEC Research Institute, Tech. Rep., 1999.