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dc.contributor.advisorSelçuk, Ali Aydın
dc.contributor.authorUğurlu, Ömer Sezgin
dc.date.accessioned2016-01-08T18:11:24Z
dc.date.available2016-01-08T18:11:24Z
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/11693/14949
dc.descriptionAnkara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2009.en_US
dc.descriptionIncludes bibliographical references leaves 60-63.en_US
dc.description.abstractMalware is one of the biggest problems of the world of bits and bytes. Generally malware does activities a user normally does not do, such as becoming part of a virtual army or submitting confidential data of the user to the malware author. There are publicly available analysis services for unknown binaries. Sandbox analysis is performed by execution of an untrusted binary in an isolated environment. It is a very common technique for malware research. Publicly available sandbox analysis platforms help users to see traces of the execution without harming their system. Also it helps owners of the sandbox to collect malware and makes the job of analysts easier. One major problem of the public sandbox testing is that malware authors can also benefit from analysis of sandboxes. If they can identify sandbox systems they can hide malicious behavior. This thesis presents the publicly used Anubis sandbox, detection mechanisms used against Anubis[3], further possible detection mechanisms and our efforts for hiding fingerprint of Anubis from malware and decreasing the resulting false negative rates for the malware detection.en_US
dc.description.statementofresponsibilityUğurlu, Ömer Sezginen_US
dc.format.extentxii, 75 leavesen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMalware analysisen_US
dc.subjectSandbox analysisen_US
dc.subjectStealth analysisen_US
dc.subject.lccTK5105.59 .U48 2009en_US
dc.subject.lcshComputer networks--Security measures.en_US
dc.subject.lcshComputer security.en_US
dc.subject.lcshVirtual computer systems.en_US
dc.titleStealth sandbox analysis of malwareen_US
dc.typeThesisen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB117987


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