A Novel Learning Approach of Adaptive Cyber Defense System for Smart Cities

Abstract

The paper includes a researching model from an attacker simultaneously and repeatedly manages attacks. Under this, a model is proposed in which iterative learning system that allows the defender to identify optimal. When the increase number of attacks targeting information and knowledge stealing information and security component, it protects the data and denying right full access to information and evolved to develop numerous natural variety of protection to assist them to avoid and eliminate danger and adapt to surroundings for survival. An adaptive cyber defense system is employed here to boost our systems resilience by security levels and metrics with transparency and secret writing. Pseudo-code illustration converges to the foremost response with regard to the attacks once the wrongdoer diminishingly traverses the system.