Building Detection-Resistant Reconnaissance Attacks Based on Adversarial Explainability
Summary
The growing popularity of Internet-of-Things devices makes them a desired target for malicious actors. Most attacks start with a reconnaissance phase where the attacker gathers information about the services running on the device, the open ports, and any existing vulnerabilities. These attacks are considered the initial step in most attack scenarios, and threat models. However, these attacks are usually easy to detect using machine learning-based detectors due to their simple nature and easy construction. In this paper, we present a novel method to construct detection-resistant reconnaissance attacks based on analysis of detection model's explanability. The proposed attack was implemented with a success rate exceeding 95% in bypassing detection with the change of one feature only.
Conference: 10th ACM Cyber-Physical System Security Workshop
Location: Singapore, Singapore
Date: July 2, 2024
Keywords
Computer systems organization, Embedded and cyber-physical systems, Sensors and acutators, Networks, Network Properties, Network Security, Computer methadologies, Machine learning
Links
References
| APA |
Alani, M. M., Mashatan, A., & Miri, A. (2024). Building detection-resistant reconnaissance attacks based on adversarial explainability. Proceedings of the 10th ACM Cyber-Physical System Security Workshop, 16–23. https://doi.org/10.1145/3626205.3659150 |
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| BibTeX |
@inproceedings{10.1145/3626205.3659150, author = {Alani, Mohammed M. and Mashatan, Atefeh and Miri, Ali}, title = {Building Detection-Resistant Reconnaissance Attacks Based on Adversarial Explainability}, year = {2024}, publisher = {Association for Computing Machinery}, url = {https://doi.org/10.1145/3626205.3659150}, doi = {10.1145/3626205.3659150}, booktitle = {Proceedings of the 10th ACM Cyber-Physical System Security Workshop}, pages = {16–23}, } |
| IEEE | M. M Alani, A. Mashatan, and A. Miri, “Building Detection-Resistant Reconnaissance Attacks Based on Adversarial Explainability,” in Proc. 10th ACM Cyber-Physical System Security Workshop (CPSS 2024), Singapore, Singapore, July 2, 2024, pp. 16-23. |