Cyber–Physical System Security for the Electric Power Grid
By Siddharth Sridhar, Adam Hahn, M. Govindarasu. Proceedings of the IEEE, 2012
1,148 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/c001038442e0f00742507e7741984c68473257e9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Florian Dörfler
- Francesco Bullo
- Karl Henrik Johansson
- Fabio Pasqualetti
- Henrik Sandberg
- Guang‐Hong Yang
- André M. H. Teixeira
- Kin Cheong Sou
In Control and Systems Engineering
- Henrik Sandberg
- André M. H. Teixeira
- Florian Dörfler
- Karl Henrik Johansson
- Francesco Bullo
- Fabio Pasqualetti
- Guang‐Hong Yang
- Kin Cheong Sou
Citations in the corpus
- Cyber-Physical Security Testbeds: Architecture, Application, and Evaluation for Smart Grid (2013, background): “Mitigation efforts should attempt to reduce the vulnerability of the cyber infrastructure while increasing the robustness of the power applications [18].”
- The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, background): “(i) Many security attacks envisioned for smart grid communication systems do not have a counterpart in other computer networks because they can target either the physical power system or the communication infrastructure or both [301].”
- Model-Based Attack Detection and Mitigation for Automatic Generation Control (2014, background): “Though attacks targeted at these systems are not frequent, their physical, economic and social impacts can be quite severe if successful [3].”
- Secure Control Systems: A Quantitative Risk Management Approach (2015, methodology): “Ensuring security may involve addressing a large number of threats, thus requiring the use of risk management methods [11] to prioritize the threats to be mitigated.”
- Control-Theoretic Methods for Cyberphysical Security: Geometric Principles for Optimal Cross-Layer Resilient Control Systems (2015, background): “The cyberphysical security of the future “smart grid” has been identified as an issue of primary concern [6], [26], and it has recently attracted the interest of the control and power systems communities; see [13], [22]–[27], [37], and [47].”
- Input-to-State Stabilizing Control for Cyber-Physical Systems With Multiple Transmission Channels Under Denial of Service (2018, background): “Since the integration means the deep interaction of all the physical and cyber components, the field of application of CPSs is immense, and various results have been proposed, such as stability analysis [2], [3], observer design [4], fault-tolerant control [5], and security problems [6], [7].”
- Smart Grids: A Cyber–Physical Systems Perspective (2016, background): “In SGs, advanced technologies such as phasor measurement units (PMUs), wide area measurement systems, substation automation, and advanced metering infrastructure (AMI) are being adopted, which present an even more increased dependency on cyber resources in real time which may be vulnerable to attack”
- On the Definition of Cyber-Physical Resilience in Power Systems (2015, neutral): “[67] present a classification method for control system vulnerabilities for electric grid risk assessment.”
- Design Techniques and Applications of Cyberphysical Systems: A Survey (2015, background): “Power system application-level cyber security has been discussed in [235].”
- Online False Data Injection Attack Detection With Wavelet Transform and Deep Neural Networks (2018, background): “One significant concern is their vulnerability to cyber-attacks [3]–[5].”
- Cyber-Physical Systems Security—A Survey (2017, background): “Lack of confidentiality in data aggregation protocols might result in privacy invasion of consumers’ private information such as billing information and usage patterns [102], while the lack of integrity could result in disruption in state estimation and consumption reports [145].”
- Applications of reinforcement learning in energy systems (2021, background): “In addition to the limitations caused by the increasing complexity of energy systems, particular attention should be devoted to uncertainty and security management [14].”