연구 분야: Infrastructure
학회: ASIA CCS '20: Proceedings of the 15th ACM Asia Conference on Computer and Communications Security
Malicious manipulations on Industrial Control Systems (ICSs) endanger critical infrastructures, causing unprecedented losses. State-of-the-art research in the discovery and exploitation of vulnerability typically assumes full visibility and control of the industrial process, which in real-world scenarios is unrealistic. In this work, we investigate the possibility of an automated end-to-end attack for an unknown control process in the constrained scenario of infecting just one industrial computer. We create databases of human-machine interface images, and Programmable Logic Controller (PLC) binaries using publicly available resources to train machine-learning models for modular and granular fingerprinting of the ICS sectors and the processes, respectively. We then explore control-theoretic attacks on the process leveraging common/ubiquitous control algorithm modules like Proportional Integral Derivative blocks using a PLC binary reverse-engineering tool, causing stable or oscillatory deviations within the operational limits of the plant. We package the automated attack and evaluate it against a benchmark chemical process, demonstrating the feasibility of advanced attacks even in constrained scenarios.
| 발행 연도 | 2020년 |
|---|---|
| 인용수 | 13 |
| 출판 국가 | United States |
| 사이트 | ACM |
| 좋아요 수 | 0 |