Smart Grid Cyber Attacks Detection Using Supervised Learning and Heuristic Feature Selection

Sakhnini, Jacob; Karimipour, Hadis

doi:10.1109/sege.2019.8859946

Cited by 102 publications

(54 citation statements)

References 20 publications

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“…Active research in this area thus seeks to find how k-NN can be used for real-time detections of cyberattacks [74]. Recently, the technique was employed to detect attacks such as data tampering and false data injection against industrial control systems [75] and smart grids [76]. It performs well when the data can be represented through a model that allows the measurement of their distance to other data-for example, in terms of a Gaussian distribution [75] or a vector [76].…”

Section: K-nearest Neighborsmentioning

confidence: 99%

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

et al. 2020

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Cybersecurity is a fast-evolving discipline that is always in the news over the last decade, as the number of threats rises and cybercriminals constantly endeavor to stay a step ahead of law enforcement. Over the years, although the original motives for carrying out cyberattacks largely remain unchanged, cybercriminals have become increasingly sophisticated with their techniques. Traditional cybersecurity solutions are becoming inadequate at detecting and mitigating emerging cyberattacks. Advances in cryptographic and Artificial Intelligence (AI) techniques (in particular, machine learning and deep learning) show promise in enabling cybersecurity experts to counter the ever-evolving threat posed by adversaries. Here, we explore AI's potential in improving cybersecurity solutions, by identifying both its strengths and weaknesses. We also discuss future research opportunities associated with the development of AI techniques in the cybersecurity field across a range of application domains.

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Section: K-nearest Neighborsmentioning

confidence: 99%

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

et al. 2020

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“…False Data Injection (FDI) attacks consist of malicious data injected into measurement meters [63]. FDI attacks can be performed by manipulating the measurements along the network by a linear factor of the Jacobian matrix of the power system [25,64]. This change in measurement is undetected by the current state estimation techniques [65].…”

Section: False Data Injection Attacksmentioning

confidence: 99%

“…For defense methods to be scalable to larger systems, purely model-based attack detection techniques are insufficient to guarantee the security of the smart grid [92,25]. As such, the use of intelligent systems and machine learning for detecting cyber attacks is proposed.…”

Section: Detection Of Attacksmentioning

confidence: 99%

“…Alternatively, intelligent systems have also been proposed in literature. The use of supervised learning was proposed for detection of false data injection (FDI) attacks [24,25]. While supervised machine learning techniques offer higher accuracy [26], semi-supervised machine learning techniques may rely on lesser studied features such as spatial and temporal correlation of smart meter measurements [27].…”

Section: Introductionmentioning

confidence: 99%

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Security aspects of Internet of Things aided smart grids: A bibliometric survey

et al. 2021

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The integration of sensors and communication technology in power systems, known as the smart grid, is an emerging topic in science and technology. One of the critical issues in the smart grid is its increased vulnerability to cyber threats. As such, various types of threats and defense mechanisms are proposed in literature. This paper offers a bibliometric survey of research papers focused on the security aspects of Internet of Things (IoT) aided smart grids. To the best of the authors' knowledge, this is the very first bibliometric survey paper in this specific field. A bibliometric analysis of all journal articles is performed and the findings are sorted by dates, authorship, and key concepts. Furthermore, this paper also summarizes the types of cyber threats facing the smart grid, the various security mechanisms proposed in literature, as well as the research gaps in the field of smart grid security.

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“…Thus, to accommodate these decentralization and digitalization trends, local distributed control and management techniques are in need [20]. The importance of this issue has led many researchers to seek new methodologies and concepts to improve the performance and security of the power systems [8], [13], [21], [22]. Application of blockchain is one of the newest ones.…”

Section: Fig 1 Power System Changes and Challengesmentioning

confidence: 99%

Blockchain Applications in Power Systems: A Bibliometric Analysis

Rouzbahani

Karimipour

Dehghantanha

et al. 2020

Advances in Information Security

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Power systems are growing rapidly, due to ever-increasing demand for electrical power. These systems require novel methodologies and modern tools and technologies, to better perform, particularly for communication among different parts. Therefore, power systems are facing new challenges such as energy trading and marketing and cyber threats. Using blockchain in power systems, as a solution, is one of the newest methods. Most studies aim to investigate innovative approaches of blockchain application in power systems. Even though, many articles published to support the research activities, there has not been any bibliometric analysis which specifies the research trends. This paper aims to present a bibliographic analysis of the blockchain application in power systems related literature, in the Web of Science (WoS) database between January 2009 and July 2019 . This paper discusses the research activities and performed a detailed analysis by looking at the number of articles published, citations, institutions, research area, and authors. From the analysis, it was concluded that there are several significant impacts of research activities in China and USA, in comparison to other countries.

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Smart Grid Cyber Attacks Detection Using Supervised Learning and Heuristic Feature Selection

Cited by 102 publications

References 20 publications

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

Security aspects of Internet of Things aided smart grids: A bibliometric survey

Blockchain Applications in Power Systems: A Bibliometric Analysis

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