scholarly journals A Dynamic Strategy for Cyber-Attack Detection in Large-scale Power Systems via Output Clustering

2020 ◽  
Author(s):  
Ana Jevtic ◽  
Marija Ilic
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Attack Detection ◽  
Cyber Attack ◽  
Dynamic Strategy

scholarly journals A Deep and Scalable Unsupervised Machine Learning System for Cyber-Attack Detection in Large-Scale Smart Grids

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 80778-80788 ◽  
Author(s):  
Hadis Karimipour ◽  
Ali Dehghantanha ◽  
Reza M. Parizi ◽  
Kim-Kwang Raymond Choo ◽  
Henry Leung
Keyword(s):  
Machine Learning ◽  
Smart Grids ◽  
Large Scale ◽  
Attack Detection ◽  
Learning System ◽  
Cyber Attack ◽  
Unsupervised Machine Learning

Optimized cyber-attack detection method of power systems using sliding mode observer

2022 ◽  
Vol 205 ◽  
pp. 107745
Author(s):  
Mahdieh Adeli ◽  
Majid Hajatipour ◽  
Mohammad Javad Yazdanpanah ◽  
Hamed Hashemi-Dezaki ◽  
Mohsen Shafieirad
Keyword(s):  
Power Systems ◽  
Detection Method ◽  
Sliding Mode ◽  
Attack Detection ◽  
Sliding Mode Observer ◽  
Cyber Attack

scholarly journals Cyber Physical Defense Framework for Distributed Smart Grid Applications

2021 ◽  
Vol 8 ◽  
Author(s):  
Ayush Sinha ◽  
Manasi Mohandas ◽  
Pankaj Pandey ◽  
O. P. Vyas
Keyword(s):  
Smart Grid ◽  
Large Scale ◽  
Impact Analysis ◽  
Denial Of Service ◽  
Attack Detection ◽  
Cyber Attack ◽  
Physical Defense ◽  
Proposed Model ◽  
Grid Applications ◽  
Physical Spaces

Cyber-Physical Systems (CPS) is the amalgamation of highly sophisticated sensors with physical spaces. These close conjunctions of sensors with communication infrastructure intrinsically linking to society’s Critical Infrastructures (C.I.) are being witnessed more often in the context of Smart Grid (SG). As a backbone of C.I., Smart Grid demonstrates ability to precisely monitor large scale energy systems and designed in order to achieve complex local and global objectives. Being capable of performing such sophisticated operation it also bears the vulnerability of being exposed for cyber-physical co-ordinated attack that may lead to catastrophic effect. Many researchers have analyze the different stages of cyber-physical co-ordinated attacks like attack detection, prevention, impact analysis and recovery plans but there exist a research gap to address all the issues under single framework. Through this paper, we propose a novel Cyber Physical Defense Framework (CPDF) based on National Institute of Standards and Technology (NIST) guidelines to address the cyber attack on SG. Our work addresses the pre and post attack scenario, attack vector formulation through hierarchical PetriNet modeling and recovery mechanism. We have performed experiment for Distributed Denial of Service (DDoS) and False Data Injection attack (FDI) to validate our framework effectiveness and established the efficacy of proposed model. In the end, we have presented a case study of FDI attack detection using machine learning technique on IEEE 9-bus and 14-bus system.

scholarly journals Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1380
Author(s):  
Fazel Mohammadi
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Cost Effective ◽  
Attack Detection ◽  
Cyber Attacks ◽  
Point Of View ◽  
Computational Time ◽  
Cyber Attack ◽  
Factors Affecting ◽  
Detection And Identification

In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is no all-inclusive solution to fit all power systems requirements. Therefore, the recently proposed cyber-attack detection and identification methods are quantitatively compared and discussed.

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