O. Salami, I. J. Umoh, E. A. Adedokun, M. B. Mu'azu, Lukman Adewale Ajao
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引用次数: 4
摘要
由于Flash (Flash event)流和DoS (Denial of Service)流在症状上的相似性,在追踪DoS攻击源时,IP (Internet Protocol)回溯工具会将它们错误地识别为DoS (Denial of Service)攻击。IP溯源方案应该能够区分FE和DoS攻击,以避免在DoS攻击溯源过程中出现较高的错误。为了解决这一问题,在IP溯源方案中引入了鉴别策略,但是当DoS攻击的攻击报文非常大时,鉴别策略可能无法有效地发挥作用。本工作通过改进对路径上各节点攻击数据包分布的统计分析方法,对判别策略的实施提出改进,从而选择更准确的攻击路径段。不同的测试结果表明,该方案在分析非常大的攻击包识别参数方面有显著的改进。
Efficient Method for Discriminating Flash Event from DoS Attack during Internet Protocol Traceback using Shark Smell Optimization Algorithm
Internet Protocol (IP) traceback tool can wrongly identify a Flash event (FE) flow as a Denial of Service (DoS) attack when tracing a DoS attack source because of the symptomatic similarities between them. IP traceback scheme should be able to differentiate FE from DoS attack to avoid higher false error during a DoS attack traceback process. Discrimination policy was introduced into IP traceback scheme to address this challenge, but the discrimination policy may not work effectively when the attack packets from a DoS attack is very large. This work proposed improvement to the discrimination policy implementation by improving the method of the statistical analysis of the attack packets distribution on each node along the path to select a more accurate attack path segment. The results of different tests carried out show significant improvement on the scheme in analyzing very large values of the attack packets discrimination parameters.