车辆自组织网络中攻击检测和数据传输的聚类方法。

IF 1.6 3区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Network-Computation in Neural Systems Pub Date : 2025-08-01 Epub Date: 2023-11-18 DOI:10.1080/0954898X.2023.2279973

Atul Barve, Pushpinder Singh Patheja

引用次数: 0

摘要

车载自组织网络(vanet)在智能城市和智能交通系统的应用中发挥着越来越重要的作用。然而，VANET通信的可靠性和稳定性面临着巨大的障碍。Natura 2000 (N2k)是全球最大的保护区协调网络，因其以保护为中心的管理结构缺乏战略眼光而受到严重批评。本研究提出了一个三阶段策略来解决这些问题，旨在有效和可持续地管理N2K场地。该新方法采用dnn辅助典型相关分析(DNN-CCAS)，包括簇形成、簇头选择和爆发识别，以增强VANET安全性。车辆聚类从一种改进的k -辅音方法开始，通过AKCEM聚类强调位置和速度。通过线性测量漫步方法选择簇头，然后使用DNN-CCAS将数据安全传输到云，如果簇头被认为是正常的。所提出的方法优于现有的技术，达到了令人印象深刻的91%的准确率。这一综合战略不仅解决了VANET的通信挑战，而且旨在通过将战略愿景纳入保护实践，彻底改变N2K遗址的管理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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RETRACTED ARTICLE: A clustering approach for attack detection and data transmission in vehicular ad-hoc networks.

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来源期刊

Network-Computation in Neural Systems 工程技术-工程：电子与电气

CiteScore

3.70

自引率

1.30%

发文量

审稿时长

>12 weeks

期刊介绍： Network: Computation in Neural Systems welcomes submissions of research papers that integrate theoretical neuroscience with experimental data, emphasizing the utilization of cutting-edge technologies. We invite authors and researchers to contribute their work in the following areas: Theoretical Neuroscience: This section encompasses neural network modeling approaches that elucidate brain function. Neural Networks in Data Analysis and Pattern Recognition: We encourage submissions exploring the use of neural networks for data analysis and pattern recognition, including but not limited to image analysis and speech processing applications. Neural Networks in Control Systems: This category encompasses the utilization of neural networks in control systems, including robotics, state estimation, fault detection, and diagnosis. Analysis of Neurophysiological Data: We invite submissions focusing on the analysis of neurophysiology data obtained from experimental studies involving animals. Analysis of Experimental Data on the Human Brain: This section includes papers analyzing experimental data from studies on the human brain, utilizing imaging techniques such as MRI, fMRI, EEG, and PET. Neurobiological Foundations of Consciousness: We encourage submissions exploring the neural bases of consciousness in the brain and its simulation in machines.