Optimized Deep Neural Model-Based Intrusion Detection and Mitigation System for Vehicular Ad-Hoc Network

Sontakke, Prakash V.; Chopade, Nilkanth B.

doi:10.1080/01969722.2022.2137643

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2023

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“…In [25], they propose a novel system for detecting and mitigating attacks in vehicular ad-hoc networks using a weight-optimized deep neural network and an improved particle swarm optimization algorithm. The system extracts features related to traffic flow and vehicle position, detects attacks, and uses a mitigation process based on BAIT.…”

Section: Deep Learningmentioning

confidence: 99%

The Evolution of VANET Networks: A Review of Emerging Trends in Artificial Intelligence and Software-Defined Networks

Sánchezl,

Parra,

J. Espitia R

2023

Artificial Intelligence, Soft Computing and Applications

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The use of vehicular ad hoc networks (Vanet) has become increasingly important in today's world due to their ability to enhance driving safety and vehicular traffic efficiency. This article will discuss artificial intelligence techniques used in Vanet, including machine learning, deep learning, and swarm intelligence techniques. Furthermore, we will examine the routing challenges within Vanet, including issues like communication link disruptions, obstacles, and varying vehicle speeds. Lastly, we will explore the implementation of software-defined networks (SDN) in Vanet, encompassing SDN protocols and architectures.

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Section: Deep Learningmentioning

confidence: 99%