Coping with Instant Messaging Worms - Statistical Modeling and Analysis

Zhijun Liu, David Lee
{"title":"Coping with Instant Messaging Worms - Statistical Modeling and Analysis","authors":"Zhijun Liu, David Lee","doi":"10.1109/LANMAN.2007.4295998","DOIUrl":null,"url":null,"abstract":"Due to the real time nature and presence information of instant messaging (IM) system, worms spread over IM networks more rapidly than Internet/E-mail worms. Modeling is an indispensable process for coping with them. Most of existing worm modeling techniques are based on deterministic biological epidemiology. Epidemic models only capture the expected worm behavior quantitatively and may not be adequate to model the early phase of worm propagation when the number of infected hosts is small. In this paper, we present a statistical branching process for modeling IM worms. By introducing stochastic variables for user response time in IM worm modeling, we are able to conduct more accurate and sophisticated analysis of worm's behaviors, especially for the early phase of worm propagation. The analysis provides a guideline on how to defend against IM worms.","PeriodicalId":347028,"journal":{"name":"2007 15th IEEE Workshop on Local & Metropolitan Area Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 15th IEEE Workshop on Local & Metropolitan Area Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LANMAN.2007.4295998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

Due to the real time nature and presence information of instant messaging (IM) system, worms spread over IM networks more rapidly than Internet/E-mail worms. Modeling is an indispensable process for coping with them. Most of existing worm modeling techniques are based on deterministic biological epidemiology. Epidemic models only capture the expected worm behavior quantitatively and may not be adequate to model the early phase of worm propagation when the number of infected hosts is small. In this paper, we present a statistical branching process for modeling IM worms. By introducing stochastic variables for user response time in IM worm modeling, we are able to conduct more accurate and sophisticated analysis of worm's behaviors, especially for the early phase of worm propagation. The analysis provides a guideline on how to defend against IM worms.
应付即时通讯蠕虫-统计建模和分析
由于即时通讯系统的实时性和存在信息,蠕虫在即时通讯网络中的传播速度比Internet/E-mail蠕虫更快。建模是应对这些问题不可或缺的过程。现有的蠕虫建模技术大多基于确定性生物流行病学。流行病模型只能定量地捕捉蠕虫的预期行为,可能不足以模拟蠕虫传播的早期阶段,因为受感染的宿主数量很少。在本文中,我们提出了一个统计分支过程来建模IM蠕虫。通过在IM蠕虫建模中引入用户响应时间的随机变量,我们可以对蠕虫的行为进行更精确和复杂的分析,特别是对蠕虫传播的早期阶段。该分析为如何防御IM蠕虫提供了指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信