Encrypted Access Mapping in a Distinctly Routed Optimized Immune System to Prevent DoS Attack Variants in VANET Architecture

Abstract

The use of vehicle ad hoc networks (VANET) is increasing, VANET is a network in which two or more vehicles communicate with each other. The VANET architecture is vulnerable to various attacks, such as DoS and DDoS attacks hence various strategies were previously employed to combat these attacks, but the presence of end-to-end transparency and N-to-1 mapping of different IP addresses create failure in the blockage and not able to determine the twelve variants of DDoS attacks hence a novel technique, Encrypted Access Hex-tuple Mapping Attack detection was proposed, which uses triple random hyperbolic encryption, which performs triple random encoding to encrypt traffic signals and obtains the public key by plotting random values in hyperbola to strengthen the access control in the middlebox and Deep auto sparse impasse NN is used to detect twelve variant DDoS attacks in the VANET architecture. Moreover, to provide immunity against attack, the existing approach uses various artificial immune systems to prevent DDoS attacks but the selection of positive and negative clusters generates too many indicator packets. Hence a novel technique, Stable Automatic Optimized Cache Routing proposed, which uses a Deep trust factorization NN to detect irrational nodes without requiring prior negotiation about local outliner factor and direct evidence by automatically extracting trust factors of each node to manage the packet flows and detecting transmission of dangerous malware files in the network to prevent various types of hybrid DDoS attacks at VANET architecture. The proposed model is implemented in NS-3 to detect and prevent hybrid DDoS attacks.