Towards Evasive Attacks: Anomaly Detection Resistance Analysis on the Internet

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dc.contributor.advisorOffutt, Jeff
dc.contributor.authorJin, Jing
dc.creatorJin, Jing
dc.date.accessioned2014-08-28T03:17:39Z
dc.date.available2014-08-28T03:17:39Z
dc.date.issued2013-08
dc.description.abstractThe Internet is rapidly improving as a platform for deploying sophisticated interactive applications especially in Web 2.0. Although the shift from desktop-centric applications brings many benefits to web-based computing and cloud computing, such as efficient com- munication with ubiquitous access and availability, the way that Internet users share and exchange information also opens their own information to security problems. Today, attack- ers conduct malicious activities to routinely track the identities of internet-connected users, steal privacy data, abuse users personal information, and expose the users unwanted data or programs. Although these attackers can also accomplish these goals by other means, the In- ternet has made it much easier for attackers to locate victims, discover sensitive information and initiate unsolicited communication with the victims.
dc.format.extent97 pages
dc.identifier.urihttps://hdl.handle.net/1920/8805
dc.language.isoen
dc.rightsCopyright 2013 Jing Jin
dc.subjectComputer science
dc.subjectCovert Channel Detection
dc.subjectEvasive Attacks
dc.subjectInformation Security
dc.subjectMachine learning
dc.subjectSimilarity Measurement
dc.subjectWeb Bots Detection
dc.titleTowards Evasive Attacks: Anomaly Detection Resistance Analysis on the Internet
dc.typeDissertation
thesis.degree.disciplineComputer Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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