Title: Network data security based on routing algorithm: application in vehicular ad-hoc networks

Authors: M.S. Sonam Mittal; S.P. Prasanth; S. Julia Faith

Addresses: Department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Punjab, 140401, India ' V.S.B. Engineering College, Kovai Main Road, Post, Karudayampalayam, Tamil Nadu, 639111, India ' Department of Information Technology, S. A. Engineering College, Chennai, 600077, Tamil Nadu

Abstract: One crucial element of intelligent transportation systems (ITS) is the use of vehicle ad hoc networks, or VANETs. Among the many advantages, these networks provide are increased road safety and decreased traffic. Despite their many benefits, VANETs are nonetheless vulnerable to a variety of security risks, such as devastating blackhole attacks. The following is a summary of the primary characteristics and contributions this paper made. First, deep learning (DL) capabilities are included into every node in the DLSR protocol, enabling it to build secure routes and decide between secure and conventional routing. Furthermore, we may look at the fitness function value of each choice to decide which is preferable for the next hop by analysing the activity of malicious nodes. Second, it is thought that the DLC protocol acts as a foundation that reduces control overhead and improves node-to-node communication.

Keywords: deep learning; secure routing; clustering; blackhole; VANET; vehicular ad-hoc networks.

DOI: 10.1504/IJMNDI.2024.144006

International Journal of Mobile Network Design and Innovation, 2024 Vol.11 No.2, pp.94 - 101

Received: 19 Jun 2024
Accepted: 18 Sep 2024
Published online: 20 Jan 2025 *

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