Research Projects

In today’s world, the people apprehension more in retrieving of content moderately than the position of the server where the respective its residence. At present, multimedia streaming providers like YouTube and Netflix together produce approximately 50% of IP traffic. The other similar service providers like Hulu, Amazon-Prime, and HBO-GO are also gaining rapid popularity. This exponential growth in the multimedia traffic over the current Internet architecture causes various challenges for network operators mainly about satisfying the user requirements (e.g., bandwidth, and latency). Taking into account the rapid growth in internet traffic, the researchers are proposing new networking paradigm from host-centric to Information-centric architecture. By using Information-centric Networking (ICN), users need not download content from content server despite they can easily access data from nearby caches in routers. In ICN-based task cooperation, the data reuse characteristic of ICN enhances the efficiency of network resource utilization. However, this also introduces plausible security vulnerabilities and cyber-attacks to the reused data, like DDoS encompassing eavesdropping attacks and unauthorized access attacks. In this project, an AI scheme will be proposed to mitigate the above security threats without compromising the efficiency of task execution using digital twin’s recommendation system NFV. The project will introduce a novel design Artificial Intelligence (AI) for an Intelligent Detection and Mitigation of cyber-attacks that ensure both data confidentiality and access control with streamlining the encryption process. Security analysis prediction using AI and experimental results will demonstrate that our proposing scheme will effectively safeguards the security of data reuse.