Knowledge Agora

Title	Machine Learning Based Security for Smart Cities
ID_Doc	39259
Authors	Amaizu, GC; Lee, JM; Kim, DS
Title	Machine Learning Based Security for Smart Cities
Year	2022
Published
Abstract	The proliferation and wide usage of the Internet of Things (IoT) and related information and communication technologies (ICT) have led to the emergence of smart cities which comprises ubiquitous sensors, and heterogeneous network architectures. These cities are capable of relaying real-time information about the world which can then be used to improve the Qualify of Life (QoL). However, due to the unprecedented access to the city and personal data by smart city applications, there is an increase in both security and privacy threat. In this study, we propose a stacked generalization machine learning algorithm for the detection of cyberattacks in a smart city. The algorithm was tested using datasets from various smart city infrastructures. Simulation results show a high detection accuracy.
PDF

Similar Articles

ID	Score	Article
45810		Rashid, MM; Kamruzzaman, J; Hassan, MM; Imam, T; Gordon, S Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques(2020)International Journal Of Environmental Research And Public Health, 17, 24
38565		Muniswamy, A; Rathi, R A Detailed Review on Enhancing the Security in Internet of Things-Based Smart City Environment Using Machine Learning Algorithms(2024)
36781		Alrashdi, I; Alqazzaz, A; Aloufi, E; Alharthi, R; Zohdy, M; Ming, H AD-IoT: Anomaly Detection of IoT Cyberattacks in Smart City Using Machine Leaming(2019)
41197		Girubagari, N; Ravi, TN Methods of anomaly detection for the prevention and detection of cyber attacks(2023)International Journal Of Intelligent Engineering Informatics, 11, 4
41657		Elsaeidy, A; Munasinghe, KS; Sharma, D; Jamalipour, A A Machine Learning Approach for Intrusion Detection in Smart Cities(2019)
42094		Rangelov, D; Lämmel, P; Brunzel, L; Borgert, S; Darius, P; Tcholtchev, N; Boerger, M Towards an Integrated Methodology and Toolchain for Machine Learning-Based Intrusion Detection in Urban IoT Networks and Platforms(2023)Future Internet, 15, 3
41042		Priyadarshini, I Anomaly Detection of IoT Cyberattacks in Smart Cities Using Federated Learning and Split Learning(2024)Big Data And Cognitive Computing, 8, 3
38272		Saba, T; Khan, AR; Sadad, T; Hong, SP Securing the IoT System of Smart City against Cyber Threats Using Deep Learning(2022)
38618		Shitharth, S; Alshareef, AM; Khadidos, AO; Alyoubi, KH; Khadidos, AO; Uddin, M A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security(2023)Scientific Reports, 13, 1
42459		Chui, KT; Gupta, BB; Liu, JQ; Arya, V; Nedjah, N; Almomani, A; Chaurasia, P A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions(2023)Information, 14, 7