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Smart city article details

Title	Intelligent Intrusion Detection System Framework For Smart Infrastructure Using Deep Learning
ID_Doc	32413
Authors	Chauhan S.; Dalwadi H.; Mahida N.; Gupta R.; Tanwar S.
Year	2024
Published	IET Conference Proceedings, 2024, 37
DOI	http://dx.doi.org/10.1049/icp.2025.0862
Abstract	A rapid growth is seen in the field of smart infrastructure where significant development is occurring in different aspects like smart cities, smart buildings, smart transportation and autonomous vehicles. All this is achieved with the intervention of IoT with such components of infrastructure. Huge IoT networks play an important role in this field. However, maintaining the security of data transmission and interaction takes center stage as an extremely important and essential problem within this complicated system. In this intricate IoT ecosystem, protecting the confidentiality and integrity of data becomes crucial to preventing any hostile attacks. We suggest a cutting-edge strategy based on the application of Artificial Neural Networks (ANNs) to address this critical issue. With the implementation of this novel approach, network security in the IoT ecosystem is strengthened by an advanced alert system that is thoroughly developed for real-time threat detection. A thorough assessment for a range of optimizers including detailed metrics evaluation is highlights Adam optimizer as the best fit giving an accuracy of 97.4% which confirms its potential to protect IoT-based condition monitoring systems. © The Institution of Engineering & Technology 2024.
Author Keywords	cyber-security; intrusion detection; IoT; Road condition monitoring; Smart Infrastructure

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