Show simple item record

dc.contributor.authorKhaleghimoghaddam, Amir
dc.date.accessioned2020-04-20T15:03:53Z
dc.date.available2020-04-20T15:03:53Z
dc.identifier.urihttp://hdl.handle.net/10222/78640
dc.description.abstractData security includes but not limited to, data encryption, tokenization, and key management practices that protect data across all applications and platforms. In this thesis, I aim to explore whether any data leakage takes place in data encryption when encrypted data is analyzed using supervised machine learning techniques. In the literature, researchers studied reverse engineering the encrypted data or brute forcing the attacks against encryption algorithms in order to study data leakage. However, in this research, my goal is not to reverse engineer or brute force the ciphertext, but to explore whether a supervised learning algorithm could identify a pattern that could potentially leak data in ciphertext. To this end, I analyze four encryption algorithms using five supervised learning techniques on four different datasets. The results show that as the encryption algorithms get stronger, the data leakage decreases, even though the data leakage is never zero percent.en_US
dc.language.isoenen_US
dc.subjectmachine learningen_US
dc.subjectdata miningen_US
dc.subjecttext classificationen_US
dc.subjectcyber securityen_US
dc.titleExploring data leakage via supervised learningen_US
dc.date.defence2020-04-07
dc.contributor.departmentFaculty of Computer Scienceen_US
dc.contributor.degreeMaster of Computer Scienceen_US
dc.contributor.external-examinern/aen_US
dc.contributor.graduate-coordinatorMichael McAllisteren_US
dc.contributor.thesis-readerDr. Srinivas Sampallien_US
dc.contributor.thesis-readerDr. Malcolm Heywooden_US
dc.contributor.thesis-supervisorDr. Nur Zincir-Heywooden_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.copyright-releaseNot Applicableen_US
 Find Full text

Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record