Cyber Security Issue in Smart Grid

Kumar, Vatan; Gupta, C. P.

doi:10.1109/gucon50781.2021.9573600

Cited by 8 publications

(2 citation statements)

References 3 publications

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“…Cyber Sabotage can physically disrupt nuclear equipment, introduce viruses/malware into the power plant and lead to a nuclear explosion. Some examples of the cyberattack on nuclear power plants are the Stuxnet computer worm attack on Iran's Nuclear Power Plants, the cyberattack on India's Kudankulam Nuclear power plant, and the Ukraine power grid hack (Kumar and Gupta, 2021).…”

Section: Research Challenges and Issues In Cyber Securitymentioning

confidence: 99%

Cyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A Survey

Manjula¹,

Venkatesh²,

Venugopal³

2023

Journal of Computer Science

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Recent advancements in e-business, e-healthcare, e-governance, and online digital transactions have brought valuable benefits. Unfortunately, it raises severe cyber-attacks. Cyberattacks disrupt normal operations, try to retrieve confidential information and defense secrets, and subvert the nation's defense systems and Internet-connected devices. Cyber security solutions are required to detect, analyze, defend against threats and protect sensitive data from unauthorized access. This study gives a detailed survey of different cybersecurity attacks, like Denial-of-service attacks, Botnet Evasion Attacks, Malware invasions, Spam and phishing invasion, Spoofing, Domain Generation algorithms, Probing attacks, R2L, and U2R attacks. This research review emphasizes Machine Learning and Deep Learning-based approaches to Cybersecurity problems. This study's key highlights are the research challenges, cybersecurity issues, cyber security domains, and tools for the Intrusion detection system. Data sets play a vital role in cybersecurity research; hence, Private and Publically available datasets are reviewed in this study. Various performance matrices are discussed in this survey which can be used to evaluate the effectiveness of cybersecurity solutions.

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Section: Research Challenges and Issues In Cyber Securitymentioning

confidence: 99%

Cyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A Survey

Manjula¹,

Venkatesh²,

Venugopal³

2023

Journal of Computer Science

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“…According to the findings of these research, there is a wide variety of potential damage that could occur, including power outages, damage to equipment, and revenue loss [19]. They have also investigated how the trust and confidence of customers and stakeholders in the electricity sector is affected by cyberattacks [20]. This research underscores the necessity for enterprises in the power industry to prioritize the development of effective cybersecurity policies and solutions to defend themselves from the risks that are being highlighted [21].…”

Section: ░ 3 Literature Reviewmentioning

confidence: 99%

Staying Ahead of Threats: A Review of AI and Cyber Security in Power Generation and Distribution

Mohamed¹,

Oubelaid

Almazrouei³

2023

IJEER

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The integration of artificial intelligence (AI) and the Internet of Things (IoT) in the power generation and distribution industry presents opportunities and challenges, particularly in the area of cybersecurity. Previous studies have explored the potential of AI to enhance cybersecurity in power systems, but limitations in terms of sample size and scope have hindered a comprehensive understanding of the current state of the field. To address this gap, this paper presents a systematic literature review of 30 papers that analyzes and categorizes relevant research based on their focus on threats, solutions, and future trends. The results indicate that 30 articles provide evidence supporting the use of AI and machine learning techniques to significantly enhance cybersecurity in the power sector. However, the study also highlights the need for continuous monitoring, threat intelligence, and risk management to stay ahead of evolving threats. Notably, this paper provides novel insights into the use of cybersecurity measures, blockchain technology, and awareness of the impact of AI in the power sector, with 90% of organizations using cybersecurity measures, 50% employing blockchain technology, 20% experiencing a cyberattack, and 60% being aware of the impact of AI. The study's limitations include a lack of detailed information on the organizations studied, such as their size and location, and the absence of a standardized approach to data collection across the selected papers. Nonetheless, this paper offers a valuable contribution to the field of AI and cybersecurity in the power industry by providing a comprehensive overview of the current state of research and identifying key areas for further investigation.

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Countering Cybersecurity Threats in Smart Grid Systems Using Machine Learning

Bean

Zhang

et al. 2022

Emerging Trends in Cybersecurity Applications

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Cyber Security Issue in Smart Grid

Cited by 8 publications

References 3 publications

Cyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A Survey

Cyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A Survey

Staying Ahead of Threats: A Review of AI and Cyber Security in Power Generation and Distribution

Countering Cybersecurity Threats in Smart Grid Systems Using Machine Learning

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