Smart City Gnosys

Smart city article details

Title	Computer-Aided Urban Energy Systems Cyber Attach Detection And Mitigation: Intelligence Hybrid Machine Learning Technique For Security Enhancement Of Smart Cities
ID_Doc	15442
Authors	Wu J.; Wang H.; Yao J.
Year	2024
Published	Sustainable Cities and Society, 108
DOI	http://dx.doi.org/10.1016/j.scs.2024.105384
Abstract	This paper introduces a sophisticated computer-aided system for enhancing the security of smart cities through urban cyber attack detection and mitigation. The proposed system employs a comprehensive mathematical framework that models the dynamics of cyber attacks, detection, and mitigation, capturing the intricate relationships within a smart city environment. Leveraging a hybrid approach combining Transfer Learning and Meta-Learning, the system adapts to evolving threats and tasks, showcasing superior performance in comparison to standalone methods. Simulation results demonstrate the system's robustness, with low False Positive and False Negative Rates, high System Security, and effective Mitigation Strategies. This research contributes a state-of-the-art solution for securing smart cities, leveraging intelligent hybrid machine learning techniques. © 2024 Elsevier Ltd
Author Keywords	Cybersecurity; Hybrid machine learning; Meta-learning; Smart cities; Transfer learning

Similar Articles

Id	Similarity	Authors	Title	Published
2164	0.887	Ji C.; Niu Y.	A Hybrid Evolutionary And Machine Learning Approach For Smart City Planning: Digital Twin Approach	Sustainable Energy Technologies and Assessments, 64 (2024)
6931	0.881	Mayan A.; Krishanveni S.; Jothi B.	Ai Enabled Digital Twin Models To Enhance Security In Smart Cities	2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology, IC-SIT 2024 (2024)
13293	0.871	Khan J.; Elfakharany R.; Saleem H.; Pathan M.; Shahzad E.; Dhou S.; Aloul F.	Can Machine Learning Enhance Intrusion Detection To Safeguard Smart City Networks From Multi-Step Cyberattacks?	Smart Cities, 8, 1 (2025)
47782	0.868	Ahmed Y.; Beyioku K.; Yousefi M.	Securing Smart Cities Through Machine Learning: A Honeypot-Driven Approach To Attack Detection In Internet Of Things Ecosystems	IET Smart Cities, 6, 3 (2024)
19240	0.868	Rangani H.; Chandrashekar K.	Detection And Prevention Of Cyber Threats In Smart Cities Using Machine Learning And Intrusion Detection Systems	2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024 - Proceedings (2024)
47027	0.867	Li B.; Yang X.; Wu X.	Role Of Net-Zero Renewable-Based Transportation Systems In Smart Cities Toward Enhancing Cultural Diversity: Realistic Model In Digital Twin	Sustainable Energy Technologies and Assessments, 65 (2024)
2187	0.863	Gill K.S.; Dhillon A.	A Hybrid Machine Learning Framework For Intrusion Detection System In Smart Cities	Evolving Systems, 15, 6 (2024)
17918	0.861	Abughali A.; Alansari M.; Al-Sumaiti A.S.	Deep Learning Strategies For Detecting And Mitigating Cyber-Attacks Targeting Water-Energy Nexus	IEEE Access, 12 (2024)
10411	0.859	Ahmed S.; Hossain M.F.; Kaiser M.S.; Noor M.B.T.; Mahmud M.; Chakraborty C.	Artificial Intelligence And Machine Learning For Ensuring Security In Smart Cities	Advanced Sciences and Technologies for Security Applications (2021)
57853	0.856	Al-Taleb N.; Saqib N.A.	Towards A Hybrid Machine Learning Model For Intelligent Cyber Threat Identification In Smart City Environments	Applied Sciences (Switzerland), 12, 4 (2022)