A survey of intrusion detection techniques for cyber-physical systems

By Robert Mitchell, Ing-Ray Chen. ACM Computing Surveys, 2014

722 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/22b56df45e2ff1aafca278253c24c6abafd0d0c7

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In Artificial Intelligence

In Computer Networks and Communications

In Control and Systems Engineering

Citations in the corpus

Internet of things security: A top-down survey (2018, background): “Some surveys [25, 89] have discussed intrusion detection systems (IDS) in wireless sensor networks and Internet of Things and have provided analysis and comparison of the main existing IDSs.”
Detecting Cyber Attacks in Industrial Control Systems Using Convolutional Neural Networks (2018, methodology): “[33], anomaly detection techniques used in ICS intrusion detection can be broadly divided into supervised, unsupervised, and semi-supervised techniques.”
A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems (2018, background): “The expected or faulty behavior is represented either via formal models or specifications (runtime verification) [29], [30], signatures describing attack behaviors [23], [24], learned models (classification, statistics) [23], [24], [31], [39], clusters or the data instances itself (nearest-neighbor)”
Cyber-Physical Systems Security—A Survey (2017, methodology): “For example, Intrusion Detection Systems (IDS) should be time-critical so that long delays are intolerable [112].”
A Survey of Intrusion Detection for In-Vehicle Networks (2020, background): “Some state-of-the-art surveys about IVN cybersecurity and cyber-physical systems (CPSs) are available [25]–[27].”
A Survey of Physics-Based Attack Detection in Cyber-Physical Systems (2018, background): “Similar work has been done in smart grid networks [1, 9] and in general CPS systems [72]; however, as Hadvziosmanovic et al. showed [30], intrusion detection systems that fail to incorporate domain-specific knowledge and the context in which they are operating will still perform poorly in practical…”
Network Intrusion Detection for IoT Security Based on Learning Techniques (2019, background): “from Wireless Sensors Networks (WSN) and Cyber Physical Systems (CPS) [7] due to heterogeneous composition of layers in terms of protocols, standards and technologies.”
Internet of Things intrusion detection systems: a comprehensive review and future directions (2022, methodology): “Speciﬁcation-based methods have been used to identify intrusion when network activity differs from speciﬁcation speciﬁcations [66].”
Smart Cities: A Survey on Data Management, Security, and Enabling Technologies (2017, background): “sion detection systems have been proposed [302], [304]–[306].”
A Survey of Random Forest Based Methods for Intrusion Detection Systems (2018, background): “Mitchell and Chen (2014a) provide a survey of intrusion detection approaches for wireless networks.”
A Review of Intrusion Detection Systems Using Machine and Deep Learning in Internet of Things: Challenges, Solutions and Future Directions (2020, methodology): “The surveys cover research work on IDSs for cloud-based IoT systems [16], Wireless sensor networks [17–19], cyber-physical systems [20], and mobile ad hoc networks (MANETs) [21–23].”