一种基于信用的综合蠕虫检测算法

摘要

This paper presents a new comprehensive worm detection algorithm based on credit. Firstly, the parameters of connection success probability are optimized and set through detection contrast experiments. Secondly, the response strategy of the credit-based connection rate limiting algorithm is redesigned, and consequently the event response process of the algorithm is improved. On the basis of the above study, the new credit-based comprehensive worm detection (CBCWD) algorithm is designed to monitor network traffics, execute response strategy for monitoring events, and give the detection results through attack condition judge and comprehensive analysis. Five different frequencies attacks detection experiments on the NUST 2011 open dataset were conducted. The experiment results demonstrate that proposed algorithm has a higher detection rate and lower false positive rate.%提出一种基于信用的综合蠕虫检测算法(CBCWD)。首先，通过检测对比实验对连接成功概率参数进行优化设定；其次，在对基于信用的连接率限制算法响应策略进行了重新设计，以此为基础对该算法的响应处理过程进行了改进。在上述研究基础上，设计一种基于信用的综合蠕虫检测算法。该算法通过监测网络流量信息，对监测事件执行响应策略，通过攻击条件判定和综合分析得出检测结果。采用NUST 2011开放数据集进行5种不同频率的攻击检测对比实验，实验结果表明该算法具有更高的检测率和更低的误报率。