Side-Channel Based Intrusion Detection for Industrial Control Systems

Aubel, Pol Van; Papagiannopoulos, Kostas; Chmielewski, Łukasz; Doerr, Christian

doi:10.1007/978-3-319-99843-5_19

Cited by 15 publications

(7 citation statements)

References 22 publications

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“…Their technique uses knowledge of the base system and a p-test to detect the alterations. The research performed in [11] attempts to detect incorrectly operating industrial control systems using electromagnetic (EM) emissions. Using a baseline measurement and real-time EM emissions a comparison is performed using statistical techniques to detect anomalies.…”

Section: Related Workmentioning

confidence: 99%

Using Side Channel Information and Artificial Intelligence for Malware Detection

Maxwell

Niblick

Ruiz

2021

2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

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Cybersecurity continues to be a difficult issue for society especially as the number of networked systems grows. Techniques to protect these systems range from rules-based to artificial intelligence-based intrusion detection systems and antivirus tools. These systems rely upon the information contained in the network packets and download executables to function. Side channel information leaked from hardware has been shown to reveal secret information in systems such as encryption keys. This work demonstrates that side channel information can be used to detect malware running on a computing platform without access to the code involved.

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Section: Related Workmentioning

confidence: 99%

Using Side Channel Information and Artificial Intelligence for Malware Detection

Maxwell

Niblick

Ruiz

2021

2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

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“…Other research focuses on side channel, or sensoring of secondary measures of data, to detect abnormally behaving systems. Anomaly detection methodologies have been developed through the use of measuring acoustics [12], electromagnetic (EM) emissions [13] [14], and power consumption [15] [16]. Individually, these methods are all useful in detecting anomalous or rare behavior.…”

Section: Related Workmentioning

confidence: 99%

Fused Sensor Analysis and Advanced Control of Industrial Field Devices for Security

Rice

Seppala

Edgar

et al. 2019

Proceedings of the Northwest Cybersecurity Symposium

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Embedded field devices that sense and control physical processes in critical infrastructure are soft targets for cyber-attack because they lack the fundamental features for existing cyber security monitoring and control. In this paper we present a new platform to collect and fuse data across multiple cyber and physical streams from these field devices to enable the host based attack detection and security control capabilities that have become common within IT environments. Experiments of different attack behaviors are discussed and initial machine learning detection approach analysis is presented.

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“…Commonly, side channels are an attack vector found in various application areas, such as acoustic side channel attacks on industrial manufacturing [1], attacks on cryptographic hardware [30] and quantum key distribution [29]. However, Van Aubel et al present a method to employ side channels for intrusion detection in ICSs [27]. They use the electro-magnetic field of a Programmable Logic Controller (PLC) during operation, create motifs and compare those motifs to the motifs of a PLC under attack.…”

Section: Related Workmentioning

confidence: 99%

Discussing the Feasibility of Acoustic Sensors for Side Channel-aided Industrial Intrusion Detection

Antón

Lohfink

Schotten

2019

Proceedings of the Third Central European Cybersecurity Conference

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The fourth industrial revolution leads to an increased use of embedded computation and intercommunication in an industrial environment. While reducing cost and effort for set up, operation and maintenance, and increasing the time to operation or market respectively as well as the efficiency, this also increases the attack surface of enterprises. Industrial enterprises have become targets of cyber criminals in the last decade, reasons being espionage but also politically motivated. Infamous attack campaigns as well as easily available malware that hits industry in an unprepared state create a large threat landscape. As industrial systems often operate for many decades and are difficult or impossible to upgrade in terms of security, legacy-compatible industrial security solutions are necessary in order to create a security parameter. One plausible approach in industry is the implementation and employment of side-channel sensors. Combining readily available sensor data from different sources via different channels can provide an enhanced insight about the security state. In this work, a data set of an experimental industrial set up containing side channel sensors is discussed conceptually and insights are derived. CCS CONCEPTS• Security and privacy → Intrusion detection systems; Network security; • Theory of computation → Design and analysis of algorithms; • Applied computing → Enterprise architectures.

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Side-Channel Based Intrusion Detection for Industrial Control Systems

Cited by 15 publications

References 22 publications

Using Side Channel Information and Artificial Intelligence for Malware Detection

Using Side Channel Information and Artificial Intelligence for Malware Detection

Fused Sensor Analysis and Advanced Control of Industrial Field Devices for Security

Discussing the Feasibility of Acoustic Sensors for Side Channel-aided Industrial Intrusion Detection

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