Supporting vehicular emergency applications requires fast access to infrastructure so vehicles can call for help. Because of their environment's poor wireless qualities, vehicle infrastructure communication paths lack security. Modern authentication systems used to close security vulnerabilities require a lot of computing and storage power from the vehicle's OBU. Thus, anovel5G automobile network emergency situationsbased onChebyshev polynomial using fog computing and authentication is proposed.This is the first study to useChebyshev chaotic mapping algorithmthatuses a chaotic map, rotation, and XOR to generate a one-way hash and eliminate modular multiplication index or scalar multiplication on the elliptic curve. The proposed scheme hasfivestages: installation system, initialization, enrollment, mutual authentication, and emergency request. Critical to emergency services, the suggested protocol works better in resource-limited settings like car systems. Theformalsecurity analysis reveals that the suggested approach guarantees message authenticity and integrity, non-repudiation, traceability, unlinkability, identity privacy, certificate independence, and emergency response.The evaluation showed thatthe proposed method cannot execute forgery, impersonation, or replay attacks.Theproposed method has lower computational, communication, and storage overhead than earlier efforts.

Source location privacy (SLP) is a serious issue in wireless sensor networks (WSN) since Eavesdroppers tries to determine the source location. Hunting Animals in Forest is considered as an example for SLP. Many conventional schemes have been proposed for SLP in WSN, namely, Random Walk Routing, and Fake Messages Transmission, which cause critical issues (less safety period, packet delivery latency, and high energy consumption). Furthermore, the security analysis is not properly investigated in any previous work. In this paper, we propose a new model called the circular chessboard‐based secure source location privacy model (C2S2‐LOOP) with the following tasks: key generation, network topology management (clustering), intercluster routing (travel plan), and data packets encryption. All sensor nodes are deployed in a circular chessboard (Circular Field) and the key generation (PUK, SEK) is invoked using elliptic curve cryptography (ECC) with Ant Lion Optimization algorithm, which mitigate the issues of conventional ECC. Then, the network topology is managed using clustering where residual energy of the nodes is used for Cluster Head (CH) selection. Intercluster routing is implemented using packet traversing using clockwise and anticlockwise directions, which are mainly concerned with establishing a secure route between the source to the destination node. To ensure data security, we present the Chaotic Artificial Neural Network (C‐ANN) in which encryption is executed. Assume that CH near to the source node has a high trust value, then it traverses (clock‐wise) real packets towards sink node and similarly in the left side region (anticlockwise), fake packets are transmitted. Network simulations (OMNeT++) are evaluated and compared with the previous approaches, and finally, our proposed scheme concludes that it maintains not only source node location privacy (large safety period) and also reduces energy consumption by more than 40% and latency by more than 35%.