Detection and defence method of low-rate DDoS attacks in vehicle edge computing network using information metrics. (26th August 2022)

• Record Type: Journal Article
• Authors: Bai, Xiao; Chen, Shanzhi; Shi, Yan; Liang, Chengzhi; Lv, Xiaochen; Yu, F. Richard
• Is Part Of: International journal of sensor networks. Volume 40:Number 1(2022)
• Page Start: 20
• Page End: 33
• Publication Date: 2022-08-26
• Subjects: attack detection and defence -- vehicle edge computing network -- low-rate DDoS attack -- information metrics -- road-side units -- RSU -- mobile subscriber international ISDN number -- MSISDN; Sensor networks -- Periodicals; 681.2
• Languages: English
• ISSNs: 1748-1279

Abstract

In vehicle edge computing network, the edge nodes are usually deployed at the road-side units (RSU) and exposed to the external environment, and are vulnerable to low-rate DDoS (LR-DDoS) attacks. In this article, we raise the detection and defence issue of LR-DDoS attacks based on information metrics at the edge of vehicle network, in which multiple edge nodes cooperate to meet their defence requirements while reducing resource consumption. We formulate the problem as sampling the received traffic at the edge nodes, and automatically determine the attack traffic by comparing the real-time calculation information metrics value with the preset information metrics thresholds. Then, a defence algorithm for edge nodes to detect conflicting mobile subscriber international ISDN number (MSISDN) is proposed to ensure that the network continues to provide services to normal vehicles. Finally, extensive experimental evaluation and comparison are carried out to show the effectiveness of the proposed scheme.