Distributed Intrusion Detection System in a Multi-Layer Network Architecture of Smart Grids

By Yichi Zhang, Lingfeng Wang, Weiqing Sun, Robert C. Green, Mansoor Alam. IEEE Transactions on Smart Grid, 2011

444 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/9d17e0502d8d240c1d517c7367d62c8688ffc43d

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In Biomedical Engineering

In Computer Networks and Communications

In Control and Systems Engineering

Citations in the corpus

A survey of intrusion detection techniques for cyber-physical systems (2014, unknown): “Many IDSs [Park et al. 2010; Mitchell and Chen 2011, 2013d, 2013c; Lauf et al. 2010; He and Blum 2011; Zhang et al. 2011b, 2011a; Asfaw et al. 2010; Carcano et al. 2011; Zimmer et al. 2010; Mitchell and Chen 2012b, 2012a, 2013b, 2013a] that use host-based auditing analyze logs maintained by a node…”
A visual analytics approach to understanding cycling behaviour (2012, unknown): “Further experiments in different application domains and comparison with other propositionalization methods, e.g. Kuželka and Železný (2011), are under way.”
On the features and challenges of security and privacy in distributed internet of things (2013, background): “Moreover, lessons might be taken from existing distributed intrusion detection systems implemented in similar environments such as smart grids [64].”
Aggregated-Proofs Based Privacy-Preserving Authentication for V2G Networks in the Smart Grid (2012, background): “For instance, a specific battery vehicle moves from the range of to the range of , and it may act as for in the home mode.”
Machine Learning Methods for Attack Detection in the Smart Grid (2015, background): “MACHINE learning methods have been widely proposed in the smart grid literature for monitoring and control of power systems [1]–[4].”
Security of smart manufacturing systems (2018, background): “Smart grid [89] Behaviour Host Denial of service, unauthorized access, probing Public (NSL-KDD dataset”
Cloud Computing Applications for Smart Grid: A Survey (2015, background): “A proper data management mechanism is necessary to be deployed for handling such massive data. d) Layered architecture: A smart grid is a combination of different layers — network, communication, electricity distribution, transmission, and generation [10].”
Detection of Faults and Attacks Including False Data Injection Attack in Smart Grid Using Kalman Filter (2014, background): “Similarly, a distributed intrusion detection system is discussed in [2].”
Cyber-security in smart grid: Survey and challenges (2018, methodology): “ • DOS [15, 35] Backdoor [43] Medium • • Social engineering [1, 29] • Scanning [25, 28] • MITM [17, 36] Replay attack [1, 34] • Jamming channel [16, 38] • Masquerade attack [33] • Integrity violation [1, 41, 46] Low Popping the HMI [1] TABLE I : LIKELIHOOD OF THE ATTACK TO BE PERFORMED AND ITS ASSOC”
Detecting Cyber Attacks in Industrial Control Systems Using Convolutional Neural Networks (2018, background): “Semi-supervised methods usually have lower false-positive rates than their fully unsupervised alternatives [49], [48].”
A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks (2019, unknown): “cious data and possible cyber attacks [108].”
Developing a Hybrid Intrusion Detection System Using Data Mining for Power Systems (2015, background): “[10] proposed a distributed IDS that analyzes communication traffic”
The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, methodology): “For instance, in [325] supervised learning models known as support vector machines (SVM) are used to extract features (e.”
Machine learning for power system disturbance and cyber-attack discrimination (2014, methodology): “in [12] propose a distributed IDS that analyzes communications traffic at different network levels of smart grid including home area networks, neighborhood area networks, and wide area networks.”
Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures (2014, methodology): “A slightly different architecture, merely inspired by NIST’s conceptual model as described above, but also by [7]–[9], is adopted for the purposes of this study.”