dc.contributor.advisor | Selçuk, Ali Aydın | |
dc.contributor.author | Uğurlu, Ömer Sezgin | |
dc.date.accessioned | 2016-01-08T18:11:24Z | |
dc.date.available | 2016-01-08T18:11:24Z | |
dc.date.issued | 2009 | |
dc.identifier.uri | http://hdl.handle.net/11693/14949 | |
dc.description | Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009. | en_US |
dc.description | Thesis (Master's) -- Bilkent University, 2009. | en_US |
dc.description | Includes bibliographical references leaves 60-63. | en_US |
dc.description.abstract | Malware 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.statementofresponsibility | Uğurlu, Ömer Sezgin | en_US |
dc.format.extent | xii, 75 leaves | en_US |
dc.language.iso | English | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Malware analysis | en_US |
dc.subject | Sandbox analysis | en_US |
dc.subject | Stealth analysis | en_US |
dc.subject.lcc | TK5105.59 .U48 2009 | en_US |
dc.subject.lcsh | Computer networks--Security measures. | en_US |
dc.subject.lcsh | Computer security. | en_US |
dc.subject.lcsh | Virtual computer systems. | en_US |
dc.title | Stealth sandbox analysis of malware | en_US |
dc.type | Thesis | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.publisher | Bilkent University | en_US |
dc.description.degree | M.S. | en_US |
dc.identifier.itemid | B117987 | |