A SECURE DATA MANAGEMENT SCHEME FOR INTERNET OF VEHICLES

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
P. Parvathy
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引用次数: 0

Abstract

Internet of Vehicles(IoV) is a self-configuring network connecting vehicles in-order to achieve unified management. It helps in monitoring vehicles and provide communication among them. IoV offers several benefits such as travel comfort, safe driving, road optimization, traffic analysis etc. The number of vehicles are increasing day by day, so the network is growing very fast. The dynamic topology of the network add complexity to it. Authentication of vehicle nodes should be provided. Another security requirement is the privacy of the data in this network, the network should be trustworthy. Since it is an open network, attacks such as data falsification, Man in the Middle attack, replay attack etc may occurs. So efficient encryption techniques are needed to ensure privacy. Since we are living in an internet era, the data in this network become large in terms of size and dimension, hence scalability of this IoV is a big question. The existing IoT protocols fails to provide scalability for storing this Big data in large scale IoV. So a reliable and secure mechanism for Big data collection, processing and storing in Internet of Vehicles is to be developed.
一种安全的车联网数据管理方案
车联网(Internet of Vehicles, IoV)是一种自配置网络,将车辆连接起来,实现统一管理。它有助于监控车辆并提供车辆之间的通信。车联网提供了许多好处,如出行舒适、安全驾驶、道路优化、交通分析等。车辆的数量日益增加,因此网络发展非常迅速。网络的动态拓扑结构增加了网络的复杂性。应提供车辆节点认证。另一个安全要求是这个网络中数据的私密性,这个网络应该是值得信赖的。由于它是一个开放的网络,因此可能会发生数据伪造、中间人攻击、重放攻击等攻击。因此,需要有效的加密技术来确保隐私。由于我们生活在互联网时代,这个网络中的数据在规模和维度上变得越来越大,因此这种车联网的可扩展性是一个大问题。现有的物联网协议无法为大规模物联网存储这些大数据提供可扩展性。因此,需要建立一种可靠、安全的车联网大数据采集、处理和存储机制。
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来源期刊
CiteScore
2.50
自引率
46.20%
发文量
57
期刊介绍: IJCNDS aims to improve the state-of-the-art of worldwide research in communication networks and distributed systems and to address the various methodologies, tools, techniques, algorithms and results. It is not limited to networking issues in telecommunications; network problems in other application domains such as biological networks, social networks, and chemical networks will also be considered. This feature helps in promoting interdisciplinary research in these areas.
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