{"title":"间谍软件检测和清除的有状态方法","authors":"Ming-Wei Wu, Yennun Huang, Yi-Min Wang, S. Kuo","doi":"10.1109/PRDC.2006.15","DOIUrl":null,"url":null,"abstract":"Spyware, a type of potentially unwanted programs (PUPs), has become a significant threat to most Internet users as it introduces serious privacy disclosure and potential security breach to the systems. Current anti-spyware tools use signatures to detect spyware programs. Over time, spyware programs have grown more resilient to this technique; they utilize critical areas of the system to survive reboots and set up mini-installers that re-install a spyware program after it's been detected and removed. Since existing anti-spyware tools are stateless in the sense that they do not remember and monitor the spyware programs that were removed, they fail to permanently remove these self-healing spyware programs. This paper proposes STARS (stateful threat-aware removal system): a tool that at run time intercepts critical system accesses and assures removed spyware does not re-install itself after a successful removal of spyware program in the system. If a re-installation (self-healing) is detected, STARS infers the source of such activities and discovers additional \"suspicious\" programs. Experimental results show that STARS is effective in removing self-healing spyware programs that existing anti-spyware tools fail to do","PeriodicalId":314915,"journal":{"name":"2006 12th Pacific Rim International Symposium on Dependable Computing (PRDC'06)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A Stateful Approach to Spyware Detection and Removal\",\"authors\":\"Ming-Wei Wu, Yennun Huang, Yi-Min Wang, S. Kuo\",\"doi\":\"10.1109/PRDC.2006.15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spyware, a type of potentially unwanted programs (PUPs), has become a significant threat to most Internet users as it introduces serious privacy disclosure and potential security breach to the systems. Current anti-spyware tools use signatures to detect spyware programs. Over time, spyware programs have grown more resilient to this technique; they utilize critical areas of the system to survive reboots and set up mini-installers that re-install a spyware program after it's been detected and removed. Since existing anti-spyware tools are stateless in the sense that they do not remember and monitor the spyware programs that were removed, they fail to permanently remove these self-healing spyware programs. This paper proposes STARS (stateful threat-aware removal system): a tool that at run time intercepts critical system accesses and assures removed spyware does not re-install itself after a successful removal of spyware program in the system. If a re-installation (self-healing) is detected, STARS infers the source of such activities and discovers additional \\\"suspicious\\\" programs. Experimental results show that STARS is effective in removing self-healing spyware programs that existing anti-spyware tools fail to do\",\"PeriodicalId\":314915,\"journal\":{\"name\":\"2006 12th Pacific Rim International Symposium on Dependable Computing (PRDC'06)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 12th Pacific Rim International Symposium on Dependable Computing (PRDC'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRDC.2006.15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 12th Pacific Rim International Symposium on Dependable Computing (PRDC'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRDC.2006.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Stateful Approach to Spyware Detection and Removal
Spyware, a type of potentially unwanted programs (PUPs), has become a significant threat to most Internet users as it introduces serious privacy disclosure and potential security breach to the systems. Current anti-spyware tools use signatures to detect spyware programs. Over time, spyware programs have grown more resilient to this technique; they utilize critical areas of the system to survive reboots and set up mini-installers that re-install a spyware program after it's been detected and removed. Since existing anti-spyware tools are stateless in the sense that they do not remember and monitor the spyware programs that were removed, they fail to permanently remove these self-healing spyware programs. This paper proposes STARS (stateful threat-aware removal system): a tool that at run time intercepts critical system accesses and assures removed spyware does not re-install itself after a successful removal of spyware program in the system. If a re-installation (self-healing) is detected, STARS infers the source of such activities and discovers additional "suspicious" programs. Experimental results show that STARS is effective in removing self-healing spyware programs that existing anti-spyware tools fail to do