Probabilistic Assessment Model for Middle-Man Attack Detection in Fifth-Generation Communication Networks
Fifth-Generation (5G) communication and mobile network provides global access to resources and applications in a pervasive manner. It integrates wireless communication networks (WCNs) user equipment (UE), heterogeneous cloud service platform, and communication protocols for pervasive access and availability. However, middle-man/ spoofing attacks lure reliable services in this environment. This article introduces a Probabilistic Assessment Model (PAM) for improving the spoof detection and service response in a 5G WCN. The proposed model exploits the spoof occurrence probability for improving the detection of replicated sequences. The constraints in response sequence due to response loss probability are identified fore-hand for modifying its sequence to improve the response probability. The proposed method's performance is verified using experimental analysis for detection ratio, response probability, and response delay.