Stealthy deception attacks against SCADA systems

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Abstract

SCADA protocols for Industrial Control Systems (ICS) are vulnerable to network attacks such as session hijacking. Hence, research focuses on network anomaly detection based on meta–data (message sizes, timing, command sequence), or on the state values of the physical process. In this work we present a class of semantic network-based attacks against SCADA systems that are undetectable by the above mentioned anomaly detection. After hijacking the communication channels between the Human Machine Interface (HMI) and Programmable Logic Controllers (PLCs), our attacks cause the HMI to present a fake view of the industrial process, deceiving the human operator into taking manual actions. Our most advanced attack also manipulates the messages generated by the operator’s actions, reversing their semantic meaning while causing the HMI to present a view that is consistent with the attempted human actions. The attacks are totaly stealthy because the message sizes and timing, the command sequences, and the data values of the ICS’s state all remain legitimate. We implemented and tested several attack scenarios in the test lab of our local electric company, against a real HMI and real PLCs, separated by a commercial-grade firewall. We developed a real-time security assessment tool, that can simultaneously manipulate the communication to multiple PLCs and cause the HMI to display a coherent system–wide fake view. Our tool is configured with message-manipulating rules written in an ICS Attack Markup Language (IAML) we designed. Our semantic attacks all successfully fooled the operator and brought the system to states of blackout and possible equipment damage.

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APA

Kleinmann, A., Amichay, O., Wool, A., Tenenbaum, D., Bar, O., & Lev, L. (2018). Stealthy deception attacks against SCADA systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10683 LNCS, pp. 93–109). Springer Verlag. https://doi.org/10.1007/978-3-319-72817-9_7

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