A Tri-Modular Framework to Minimize Smart Grid Cyber-Attack Cognitive Gap in Utility Control Centers

Sundararajan, Aditya; Wei, Longfei; Khan, Tanwir; Sarwat, Arif I.; Rodrigo, Deepal

doi:10.1109/rweek.2018.8473503

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…In this case, a VPN should be used to establish an encrypted connection ( Noureen et al, 2019 ). These facts show that no security solution works for all firms, including energy providers ( Sundararajan et al, 2018 ; Cai et al, 2017 ; Rice & AlMajali, 2014 ). Instead, each company must customize security protocols to meet its unique needs.…”

Section: Risk Modeling Techniquesmentioning

confidence: 99%

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Security risk models against attacks in smart grid using big data and artificial intelligence

Yasin Ghadi,

Mazhar,

Aurangzeb

et al. 2024

PeerJ Computer Science

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The need to update the electrical infrastructure led directly to the idea of smart grids (SG). Modern security technologies are almost perfect for detecting and preventing numerous attacks on the smart grid. They are unable to meet the challenging cyber security standards, nevertheless. We need many methods and techniques to effectively defend against cyber threats. Therefore, a more flexible approach is required to assess data sets and identify hidden risks. This is possible for vast amounts of data due to recent developments in artificial intelligence, machine learning, and deep learning. Due to adaptable base behavior models, machine learning can recognize new and unexpected attacks. Security will be significantly improved by combining new and previously released data sets with machine learning and predictive analytics. Artificial Intelligence (AI) and big data are used to learn more about the current situation and potential solutions for cybersecurity issues with smart grids. This article focuses on different types of attacks on the smart grid. Furthermore, it also focuses on the different challenges of AI in the smart grid. It also focuses on using big data in smart grids and other applications like healthcare. Finally, a solution to smart grid security issues using artificial intelligence and big data methods is discussed. In the end, some possible future directions are also discussed in this article. Researchers and graduate students are the audience of our article.

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Section: Risk Modeling Techniquesmentioning

confidence: 99%

“…If IT should only contact OT, limiting communication to the HTTPS protocol makes sense. As a result, attacks that rely on server message blocks are prevented ( Sundararajan et al, 2018 ). Start by conducting a thorough risk analysis that considers internal and external threats.…”

Section: Risk Modeling Techniquesmentioning

confidence: 99%

Security risk models against attacks in smart grid using big data and artificial intelligence

Yasin Ghadi,

Mazhar,

Aurangzeb

et al. 2024

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…With cyber threat-aware personnel, CIs can be hardened against cyber attacks. The emergence of the IoT in ICS has led to new security challenges, which will require newly developed expertise to prepare for a wide variety of attacks that may emerge from the integration of these systems [65][66][67][68][69].…”

Section: Reason To Train Personnelmentioning

confidence: 99%

Impact, Vulnerabilities, and Mitigation Strategies for Cyber-Secure Critical Infrastructure

Riggs

Tufail

Parvez

et al. 2023

Sensors

Self Cite

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Several critical infrastructures are integrating information technology into their operations, and as a result, the cyber attack surface extends over a broad range of these infrastructures. Cyber attacks have been a serious problem for industries since the early 2000s, causing significant interruptions to their ability to produce goods or offer services to their clients. The thriving cybercrime economy encompasses money laundering, black markets, and attacks on cyber-physical systems that result in service disruptions. Furthermore, extensive data breaches have compromised the personally identifiable information of millions of people. This paper aims to summarize some of the major cyber attacks that have occurred in the past 20 years against critical infrastructures. These data are gathered in order to analyze the types of cyber attacks, their consequences, vulnerabilities, as well as the victims and attackers. Cybersecurity standards and tools are tabulated in this paper in order to address this issue. This paper also provides an estimate of the number of major cyber attacks that will occur on critical infrastructure in the future. This estimate predicts a significant increase in such incidents worldwide over the next five years. Based on the study’s findings, it is estimated that over the next 5 years, 1100 major cyber attacks will occur on critical infrastructures worldwide, each causing more than USD 1 million in damages.

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Evaluation of Missing Data Imputation Methods for an Enhanced Distributed PV Generation Prediction

Sundararajan

2019

Advances in Intelligent Systems and Computing

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A Tri-Modular Framework to Minimize Smart Grid Cyber-Attack Cognitive Gap in Utility Control Centers

Cited by 8 publications

References 10 publications

Security risk models against attacks in smart grid using big data and artificial intelligence

Security risk models against attacks in smart grid using big data and artificial intelligence

Impact, Vulnerabilities, and Mitigation Strategies for Cyber-Secure Critical Infrastructure

Evaluation of Missing Data Imputation Methods for an Enhanced Distributed PV Generation Prediction

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