{"title":"使用流数据的简单安全性","authors":"Kenichi Futamura","doi":"10.1109/WOCC.2009.5312784","DOIUrl":null,"url":null,"abstract":"Malware attacks cause billions of dollars in economic damage worldwide yearly, and attackers are becoming smarter. We examine techniques for detecting worm propagation in a network using flow-level data. While worm exploits may be difficult to detect due to the wide range of payloads, the propagation phase of a worm is generally much easier to recognize. We examine this step and present one simple method for detecting network worms with no previously known signatures.","PeriodicalId":288004,"journal":{"name":"2009 18th Annual Wireless and Optical Communications Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simple security using flow data\",\"authors\":\"Kenichi Futamura\",\"doi\":\"10.1109/WOCC.2009.5312784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Malware attacks cause billions of dollars in economic damage worldwide yearly, and attackers are becoming smarter. We examine techniques for detecting worm propagation in a network using flow-level data. While worm exploits may be difficult to detect due to the wide range of payloads, the propagation phase of a worm is generally much easier to recognize. We examine this step and present one simple method for detecting network worms with no previously known signatures.\",\"PeriodicalId\":288004,\"journal\":{\"name\":\"2009 18th Annual Wireless and Optical Communications Conference\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 18th Annual Wireless and Optical Communications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOCC.2009.5312784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 18th Annual Wireless and Optical Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOCC.2009.5312784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Malware attacks cause billions of dollars in economic damage worldwide yearly, and attackers are becoming smarter. We examine techniques for detecting worm propagation in a network using flow-level data. While worm exploits may be difficult to detect due to the wide range of payloads, the propagation phase of a worm is generally much easier to recognize. We examine this step and present one simple method for detecting network worms with no previously known signatures.