{"id":160039,"date":"2008-08-01T00:00:00","date_gmt":"2008-08-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/spysaver-using-incentives-to-address-spyware\/"},"modified":"2018-10-16T22:32:39","modified_gmt":"2018-10-17T05:32:39","slug":"spysaver-using-incentives-to-address-spyware","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/spysaver-using-incentives-to-address-spyware\/","title":{"rendered":"SpySaver: Using Incentives to Address Spyware"},"content":{"rendered":"

Despite the many solutions proposed by industry and the research community to address spyware, this problem continues to grow. Many of today\u2019s anti-spyware approaches are inspired by techniques used against related security problems, such as worms, DoS attacks, computer viruses, and spam. Although these techniques have been retrofitted to address spyware, they remain ineffective because they rely on the compromised host to detect and remove spyware. Once a host is compromised, attackers often find simple ways to escape spyware detection and removal. This paper presents SpySaver \u2013 a novel anti-spyware approach that reduces the incentive to deploy spyware. Our approach does not prevent spyware installations, nor does it recover from them. Instead, SpySaver decreases the value of the information spyware collects by creating counterfeit information. Our goal is to generate enough counterfeit information to devalue the information gathered by spyware to the point that we eliminate the incentive to collect it in the first place. In this paper, we present our approach and an initial design of a tool that produces realistic counterfeit information about the browsing patterns of Web users.<\/p>\n","protected":false},"excerpt":{"rendered":"

Despite the many solutions proposed by industry and the research community to address spyware, this problem continues to grow. Many of today\u2019s anti-spyware approaches are inspired by techniques used against related security problems, such as worms, DoS attacks, computer viruses, and spam. Although these techniques have been retrofitted to address spyware, they remain ineffective because […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-160039","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the 2008 Workshop on the Economics of Networks, Systems, and Computation 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