Securing modern power systems: Implementing comprehensive strategies to enhance resilience and reliability against cyber-attacks

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102647 - 102647

Published: July 30, 2024

Recent technological advancements in the energy sector, such as proliferation of electric vehicles, and smart power electronic devices, have substantially increased demand for reliable quality supply. This surge consumption has posed significant concerns traditional systems regarding systems' resilience reliability. To address these challenges, system engineers researchers proposed digitalization systems, resulting remotely controlled operated grids. However, transition towards grids introduced new vulnerabilities, specifically form cyber-attacks. One notable example is recent malicious attack on Ukrainian system, which left three distribution networks destroyed, causing losses damage to thousands customers. In an era marked by rapid advancement, security modern infrastructure against cyber-attackers emerged a paramount concern operators. paper presents comprehensive examination cybersecurity strategies aimed at strengthening reliability systems. By thoroughly analyzing various cyber-attacks effective defence strategies, it evident that plays crucial role maintaining continuous supply reducing impact potential contingencies. The study further provides valuable perspectives changing landscape cyber threats faced combining insights from advanced research industry expertise. conventional techniques cutting-edge technologies, recommendations are provided improving protecting vital grid assets, substations. serves essential resource policymakers, practitioners, seeking understand complex relationship between

Language: Английский

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Handover Decision with Multi-Access Edge Computing in 6G Networks: A Survey

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 103934 - 103934

Published: Jan. 1, 2025

Language: Английский

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An RFE/Ridge-ML/DL based anomaly intrusion detection approach for securing IoMT system

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102659 - 102659

Published: Aug. 2, 2024

Smart healthcare is one of the promising areas Internet Things (IoT), particularly in case Covid-19 pandemic. Real-time patient monitoring and remote diagnostics facilitate better medical services to preserve human lives using Medical (IoMT) technology. Regardless numerous benefits, IoMT devices are susceptible sophisticated cyber-attacks at a breakneck pace, which lead tampering with data threaten patients' lives. In similar context, 2022 ransomware cyber-attack on Versailles André-Mignot Hospital compromised system disclosed tremendous amounts information. Towards this direction, most researchers have solely developed either machine learning or Deep algorithms identify network traffic anomalies. Motivated by above challenges, an effort has been made paper design Recursive Feature Elimination (RFE) integrated paradigms Ridge regression merged into deep models for implementing accurate anomaly intrusion detection based real-time dataset WUSTL-EHMS. Among used, proposed approach confirms that RFE-based Decision Tree (DT) outperforms state-of-the-art techniques training accuracy 99 % testing 97.85 while maintaining reduction FAR 0.03. nutshell, it proven suggested framework can be deployed build detection, reinforcing against widespread safeguarding integrity advanced systems.

Language: Английский

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Enhancing cybersecurity incident response: AI-driven optimization for strengthened advanced persistent threat detection

Results in Engineering, Journal Year: 2025, Volume and Issue: 25, P. 104078 - 104078

Published: Jan. 21, 2025

Language: Английский

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Machine learning approach with a posteriori-based feature to predict service life of a thermal cracking furnace with coking deposition

Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102349 - 102349

Published: June 1, 2024

A thermal cracking furnace is an important equipment in the petrochemical industry that typically used for breaking long hydrocarbons into short chains and producing coke as a byproduct. Deposition of generated increases temperature at outside coil wall, necessitating regular maintenance to prevent failure. Therefore, this study proposed machine learning approach with posteriori-based feature predict service life runtime The consists two-level model, which aims improve prediction accuracy reduce sensitivity. label classified week range label, can be categorized by classification criteria three classes: weekly, bi-weekly, quarter-weekly. first-level model utilized extract sensor features posterior probability class score. These scores are then processed sorted moving windows generate second-level model. results showed could process variation identify needs, improved 23.94% 17.67% clean coke-contaminated datasets compared conventional respectively. Additionally, most general (quarter-weekly) provided best performance bi-weekly weekly classes. has potential under pseudo-steady state conditions, where coking evolves gradually over time.

Language: Английский

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Generative Artificial Intelligence and Machine Learning for Identity and Access Management

Proceedings of the Technical University of Sofia, Journal Year: 2025, Volume and Issue: 74(3)

Published: Jan. 7, 2025

Language: Английский

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A Deep Learning Approach for the Detection of Intrusions on Network Traffic

Lecture notes in networks and systems, Journal Year: 2025, Volume and Issue: unknown, P. 319 - 331

Published: Jan. 1, 2025

Language: Английский

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Enhancing IoT Security in Vehicles: A Comprehensive Review of AI-Driven Solutions for Cyber-Threat Detection

AI, Journal Year: 2024, Volume and Issue: 5(4), P. 2279 - 2299

Published: Nov. 6, 2024

Background: The Internet of Things (IoT) has improved many aspects that have impacted the industry and people’s daily lives. To begin with, IoT allows communication to be made across a wide range devices, from household appliances industrial machinery. This connectivity for better integration pervasive computing, making devices “smart” capable interacting with each other corresponding users in sublime way. However, widespread adoption introduced some security challenges, because these usually run environments limited resources. As technology becomes more integrated into critical infrastructure life, need stronger measures will increase. These are exposed variety cyber-attacks. literature review synthesizes current research artificial intelligence (AI) technologies improve security. addresses key questions, including: (1) What primary challenges threats face?; (2) How can AI used security?; (3) techniques currently being this purpose?; (4) does applying differ traditional methods? Methods: We included total 33 peer-reviewed studies published between 2020 2024, specifically journal conference papers written English. Studies irrelevant use security, duplicate studies, articles without full-text access were excluded. search was conducted using scientific databases, including MDPI, ScienceDirect, IEEE Xplore, SpringerLink. Results synthesized through narrative synthesis approach, help Parsifal tool organize visualize themes trends. Results: focus on machine learning, deep federated which anomaly detection identify mitigate inherent devices. AI-driven offer promising solutions attack predictive analysis, reducing human intervention significantly. acknowledges limitations such as rapidly evolving nature technologies, early-stage development or proprietary techniques, variable performance models real-world applications, potential biases selection articles. risk bias systematic is moderate. While study data collection processes robust, reliance exploration process introduce risk. Transparency funding conflict interest reporting reduces those areas. Discussion: effectiveness AI-based approaches vary depending model computational efficiency. In article, we provide comprehensive overview existing applied learning (ML), (DL), hybrid approaches. also examine their role enhancing accuracy. Despite all advances, still remain terms privacy scalability Conclusion: provides ML applications enhance discuss outline future directions, emphasizing collaboration interested parties ongoing innovation address threat landscape

Language: Английский

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XSShield: A Novel Dataset and Lightweight Hybrid Deep Learning Model for XSS Attack Detection

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 103363 - 103363

Published: Nov. 13, 2024

Language: Английский

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