AI based Adaptive Network for Smart Cities
Abstract
Self-aware, Self-Defending Adaptive Network is a network that defends itself from security breaches in the deployment of smart cities. An adaptive system that knows and recognizes the level of threat faced by an intrusion across a network of smart cities. To detect and separate security threats, the AI program uses a new method of machine learning to track any aspect of a network. Threats include ransomware, high-jacking code, intrusion and illegal entry, theft, and unauthorized use. An autonomous system comprises of a collection of autonomous modules that are introduced and removed dynamically. To order to achieve machine objectives, nodes inside such an ensemble will cooperate. In response to changes in its operating environment, the self-adaptive network modifies its own behavior. We mean anything that the network can observe, such as user interaction, network devices and sensors, or instrumentation, by operating environment.
References
2. A neural network based feedforward adaptive controller for robots R. Carelli ; E.F. Camacho ; D. Patino
3. Adaptive delay-based congestion control for high bandwidth-delay product networks Hyungsoo Jung ; Shin-gyu Kim ; Heon Y. Yeom ; Sooyong Kang ; Lavy Libman
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