Data Stream clustering for detecting misbehavior in an intelligent transportation system

Sara Ftaimi, T. Mazri
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Abstract

The security aspect represents a major challenge for the intelligent transport system, whether it is securing the system's various components such as the network and communication between the various nodes or securing the nodes themselves. In ITS, data is generated at high speed, and the data shared between the nodes of the network changes over time at a very high speed. Securing the data shared by the nodes is essential to ensure the integrity and reliable communication. In this paper, we will propose a methodology to detect packets' behavior sent between the different nodes using a data stream clustering algorithm since the data shared between the nodes verify the data stream criteria.
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用于检测智能交通系统中不当行为的数据流聚类
无论是保护系统的各个组成部分,如网络和各个节点之间的通信,还是保护节点本身,安全方面都是智能运输系统面临的主要挑战。在ITS中,数据是高速生成的,网络节点之间共享的数据随时间的变化速度非常快。保护节点共享的数据对于确保通信的完整性和可靠性至关重要。在本文中,我们将提出一种方法,使用数据流聚类算法来检测不同节点之间发送的数据包行为,因为节点之间共享的数据验证了数据流标准。
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