Bank of Models: Sensor Attack Detection and Isolation in Industrial Control Systems
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-93200-8_1
Reference49 articles.
1. Ahmed, C.M., A.Sridhar, M., A.: Limitations of state estimation based cyber attack detection schemes in industrial control systems. In: IEEE Smart City Security and Privacy Workshop, CPSWeek (2016)
2. Ahmed, C.M., Mathur, A.P.: Challenges in machine learning based approaches for real-time anomaly detection in industrial control systems. In: Proceedings of the 6th ACM on Cyber-Physical System Security Workshop. p. 23–29. CPSS ’20, Association for Computing Machinery, New York, NY, USA (2020). https://doi.org/10.1145/3384941.3409588
3. Ahmed, C.M., Murguia, C., Ruths, J.: Model-based attack detection scheme for smart water distribution networks. In: Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, pp. 101–113. ASIA CCS ’17, ACM, New York, NY, USA (2017). https://doi.org/10.1145/3052973.3053011
4. Ahmed, C.M., et al.: Noiseprint: Attack detection using sensor and process noise fingerprint in cyber physical systems. In: Proceedings of the 2018 on Asia Conference on Computer and Communications Security, pp. 483–497. ASIACCS ’18, ACM, New York, NY, USA (2018). https://doi.org/10.1145/3196494.3196532
5. Ahmed, C.M., Zhou, J.: Challenges and opportunities in cyberphysical systems security: a physics-based perspective. IEEE Secur. Privacy 18(6), 14–22 (2020)
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