Privacy Preserving Search Techniques over Encrypted Outsourced Data

Salmani, Khosro

Privacy Preserving Search Techniques over Encrypted Outsourced Data

dc.contributor.advisor	Barker, Ken
dc.contributor.author	Salmani, Khosro
dc.contributor.committeemember	Jacobson, Michael
dc.contributor.committeemember	Reardon, Joel
dc.date	2020-11
dc.date.accessioned	2020-07-24T22:23:32Z
dc.date.available	2020-07-24T22:23:32Z
dc.date.issued	2020-07-24
dc.description.abstract	During the last decade, various type of cloud services have encouraged individuals and enterprises to store personal data in the cloud. Despite its flexibility, cost efficiency, and convenient service, protecting security and privacy of the outsourced data has always been a primary challenge. Although data encryption retains the outsourced data's security and privacy to some extent, it does not permit traditional plaintext keyword search mechanisms, and it comes at the cost of efficiency. Hence, proposing an efficient encrypted cloud data search service would be an important step forward. To address this challenge scholars introduced Searchable Symmetric Encryption (SSE) in which a client is able to perform searches over encrypted documents. However, these schemes suffer from private information leakage such as access pattern, search pattern, and co-occurrence leakage. Several recent papers show that how this critical information can be exploited to collapse the whole security system and an adaptive attacker can reveal plaintext data. In this thesis, we address the challenging problems of access pattern, search pattern, and co-occurrence private information leakage. We design and construct three schemes to tackle the above challenges. We formally prove that all of our schemes are secure and achieve a higher level of privacy by preventing and obfuscating the private information leakages. Moreover, our performance analyses demonstrate the practicality and efficiency of our approaches.	en_US
dc.identifier.citation	Salmani, K. (2020). Privacy Preserving Search Techniques over Encrypted Outsourced Data (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.	en_US
dc.identifier.doi	http://dx.doi.org/10.11575/PRISM/38039
dc.identifier.uri	http://hdl.handle.net/1880/112329
dc.language.iso	eng	en_US
dc.publisher.faculty	Science	en_US
dc.publisher.institution	University of Calgary	en
dc.rights	University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.	en_US
dc.subject	Data Privacy	en_US
dc.subject.classification	Computer Science	en_US
dc.title	Privacy Preserving Search Techniques over Encrypted Outsourced Data	en_US
dc.type	doctoral thesis	en_US
thesis.degree.discipline	Computer Science	en_US
thesis.degree.grantor	University of Calgary	en_US
thesis.degree.name	Doctor of Philosophy (PhD)	en_US
ucalgary.item.requestcopy	true	en_US