Tackling Android Stego Apps in the Wild

dc.contributor.author Chen, Wenhao
dc.contributor.author Lin, Li
dc.contributor.author Wu, Min
dc.contributor.author Newman, Jennifer
dc.contributor.department Center for Statistics and Applications in Forensic Evidence
dc.contributor.department Mathematics
dc.date 2020-02-18T15:11:05.000
dc.date.accessioned 2020-06-30T01:57:57Z
dc.date.available 2020-06-30T01:57:57Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 2018
dc.date.embargo 2020-02-18
dc.date.issued 2018-11-01
dc.description.abstract <p>Digital image forensics is a young but maturing field, encompassing key areas such as camera identification, detection of forged images, and steganalysis. However, large gaps exist between academic results and applications used by practicing forensic analysts. To move academic discoveries closer to real-world implementations, it is important to use data that represent “in the wild” scenarios. For detection of stego images created from steganography apps, images generated from those apps are ideal to use. In this paper, we present our work to perform steg detection on images from mobile apps using two different approaches: “signature” detection, and machine learning methods. A principal challenge of the ML task is to create a great many of stego images from different apps with certain embedding rates. One of our main contributions is a procedure for generating a large image database by using Android emulators and reverse engineering techniques, the first time ever done. We develop algorithms and tools for signature detection on stego apps, and provide solutions to issues encountered when creating ML classifiers.</p>
dc.description.comments <p>This is an accepted manuscript published as Chen, Wenhao, Li Lin, Min Wu, and Jennifer Newman. "Tackling android stego apps in the wild." In <em>2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)</em>, pp. 1564-1573. IEEE, 2018. Posted with permission of CSAFE.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/csafe_conf/5/
dc.identifier.articleid 1004
dc.identifier.contextkey 16574730
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath csafe_conf/5
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/20334
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/csafe_conf/5/2018_TacklingAndroid.pdf|||Sat Jan 15 00:38:51 UTC 2022
dc.source.uri 10.23919/APSIPA.2018.8659525
dc.subject.disciplines Forensic Science and Technology
dc.title Tackling Android Stego Apps in the Wild
dc.type article
dc.type.genre conference
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 82295b2b-0f85-4929-9659-075c93e82c48
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