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How Feasible are Steganographic and Stealth Attacks on TIA Project Metadata of ICS: A Case Study with Real-world Data

Published: 22 November 2021 Publication History

Abstract

The protection of industrial control systems (ICS) is crucial for a robust provision of essential services for the modern society. Stealthy and steganographic attacks are a considerable threat against the reliability and security of such ICS. Several ICS components are maintained via the popular Totally Integrated Automation (TIA) project software. In this paper, we investigate TIA project metadata of a German car manufacturer, in particular an axis and a soldering tip project. We analyze the devices’ metadata and their changes over time to determine whether modifications would potentially appear as anomalies when being monitored. Our results show that most TIA project attributes do not change or change very rarely, rendering such attributes mostly unsuitable for hiding information as well as for conducting stealthy attacks.

References

[1]
C. Feng, T. Li, Z. Zhu, and D. Chana. 2017. A deep learning-based framework for conducting stealthy attacks in industrial control systems. arXiv preprint arXiv:1709.06397(2017).
[2]
L. Hartmann and S. Wendzel. 2021, in press. Detection of Anomalous Values within TIA Project Data History for Industrial Control Systems. In Proc. European Interdisciplinary Cybersecurity Conference (EICC), Doctoral Symposium. ACM.
[3]
S. Wendzel, W. Mazurczyk, and G. Haas. 2017. Steganography for cyber-physical systems. Journal of Cyber Security and Mobility(2017), 105–126.

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            EICC '21: Proceedings of the 2021 European Interdisciplinary Cybersecurity Conference
            November 2021
            97 pages
            ISBN:9781450390491
            DOI:10.1145/3487405
            Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            Published: 22 November 2021

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            Author Tags

            1. Anomaly Detection
            2. Cyber Physical Systems (CPS) Security
            3. Industrial Control Systems (ICS)
            4. Intrusion Detection Systems (IDS).

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            • Refereed limited

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            EICC '21
            EICC '21: European Interdisciplinary Cybersecurity Conference
            November 10 - 11, 2021
            Virtual Event, Romania

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