{"title":"d-ACTM/VT:分布式虚拟交流树检测方法","authors":"N. Kawaguchi, H. Shigeno, Ken-ichi Okada","doi":"10.2197/IPSJDC.4.79","DOIUrl":null,"url":null,"abstract":"In this paper, we propose d-ACTM/VT, a network-based worm detection method that effectively detects hit-list worms using distributed virtual AC tree detection. To detect a kind of hit-list worms named Silent worms in a distributed manner, d-ACTM was proposed. d-ACTM detects the existence of worms by detecting tree structures composed of infection connections as edges. Some undetected infection connections, however, can divide the tree structures into small trees and degrade the detection performance. To address this problem, d-ACTM/VT aggregates the divided trees as a tree named Virtual AC tree in a distributed manner and utilizes the tree size for detection. Simulation result shows d-ACTM/VT reduces the number of infected hosts before detection by 20% compared to d-ACTM.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"d-ACTM/VT: A Distributed Virtual AC Tree Detection Method\",\"authors\":\"N. Kawaguchi, H. Shigeno, Ken-ichi Okada\",\"doi\":\"10.2197/IPSJDC.4.79\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose d-ACTM/VT, a network-based worm detection method that effectively detects hit-list worms using distributed virtual AC tree detection. To detect a kind of hit-list worms named Silent worms in a distributed manner, d-ACTM was proposed. d-ACTM detects the existence of worms by detecting tree structures composed of infection connections as edges. Some undetected infection connections, however, can divide the tree structures into small trees and degrade the detection performance. To address this problem, d-ACTM/VT aggregates the divided trees as a tree named Virtual AC tree in a distributed manner and utilizes the tree size for detection. Simulation result shows d-ACTM/VT reduces the number of infected hosts before detection by 20% compared to d-ACTM.\",\"PeriodicalId\":432390,\"journal\":{\"name\":\"Ipsj Digital Courier\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ipsj Digital Courier\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2197/IPSJDC.4.79\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ipsj Digital Courier","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2197/IPSJDC.4.79","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
在本文中,我们提出了一种基于网络的蠕虫检测方法d-ACTM/VT,该方法使用分布式虚拟交流树检测来有效地检测命中列表蠕虫。为了对静默蠕虫进行分布式检测,提出了d-ACTM算法。d-ACTM通过检测由感染连接组成的树形结构作为边缘来检测蠕虫的存在。然而,一些未被检测到的感染连接可能会将树结构分成小树,从而降低检测性能。为了解决这一问题,d-ACTM/VT将划分的树以分布式的方式聚合成一棵树,命名为Virtual AC tree,并利用树的大小进行检测。仿真结果表明,与d-ACTM相比,d-ACTM/VT在检测前将感染主机的数量减少了20%。
d-ACTM/VT: A Distributed Virtual AC Tree Detection Method
In this paper, we propose d-ACTM/VT, a network-based worm detection method that effectively detects hit-list worms using distributed virtual AC tree detection. To detect a kind of hit-list worms named Silent worms in a distributed manner, d-ACTM was proposed. d-ACTM detects the existence of worms by detecting tree structures composed of infection connections as edges. Some undetected infection connections, however, can divide the tree structures into small trees and degrade the detection performance. To address this problem, d-ACTM/VT aggregates the divided trees as a tree named Virtual AC tree in a distributed manner and utilizes the tree size for detection. Simulation result shows d-ACTM/VT reduces the number of infected hosts before detection by 20% compared to d-ACTM.