{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90606"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90606","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Secure and practical computation on encrypted data","abstract":"This Dissertation was approved for publication on 2016-04-21 at 13:02.","abstract_html":"This Dissertation was approved for publication on 2016-04-21 at 13:02.","abstract_has_math":false,"creators":["Naveed, Muhammad"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Gunter, Carl A.","Prabhakaran, Manoj","Borisov, Nikita","Shi, Elaine","Wang, XiaoFeng"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T19:54:32Z","date_published":"2016-07-07T19:54:32Z","updated_at":"2026-07-22T22:26:34Z","subjects":["computation on encrypted data","property-preserving encryption","symmetric searchable encryption","controlled functional encryption"],"languages":["en"],"rights":["Copyright 2016 Muhammad Naveed"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/90606","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gunter, Carl A.","Prabhakaran, Manoj","Borisov, Nikita","Shi, Elaine","Wang, XiaoFeng"]},{"key":"dc:creator","label":"Author","values":["Naveed, Muhammad"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-07-07T19:54:32Z","2016-04-21","2016-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["computation on encrypted data","property-preserving encryption","symmetric searchable encryption","controlled functional encryption"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Muhammad Naveed"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90606"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This Dissertation was approved for publication on 2016-04-21 at 13:02.","Because of the importance of computing on data with privacy protections, the cryptographic community has developed both theoretical and practical solutions to compute on encrypted data. On the one hand, theoretical schemes, such as fully homomorphic encryption and functional encryption, are secure but extremely inefficient. On the other hand, practical schemes, such as property-preserving encryption, gain efficiency by accepting significant reductions in security. In this thesis, we first study the security of popular property-preserving encryption schemes that are being used by companies such as Microsoft and Google. We show that such schemes are unacceptably insecure for key target applications such as electronic medical records. Second, we propose new models to compute on encrypted data and develop efficient constructions and systems. We propose a new cryptographic primitive called Blind Storage and show how it can be used to realize symmetric searchable encryption, which is much more secure than property-preserving encryption. Finally, we propose a new cryptographic model called Controlled Functional Encryption and develop two efficient schemes in this model.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Muhammad Naveed, accepted the attached license on 2016-04-21 at 10:11.","The student, Muhammad Naveed, submitted this Dissertation for approval on 2016-04-21 at 10:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9400 on 2016-07-07 at 13:32:11","Made available in DSpace on 2016-07-07T19:54:32Z (GMT). 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On the one hand, theoretical schemes, such as fully homomorphic encryption and functional encryption, are secure but extremely inefficient. On the other hand, practical schemes, such as property-preserving encryption, gain efficiency by accepting significant reductions in security. In this thesis, we first study the security of popular property-preserving encryption schemes that are being used by companies such as Microsoft and Google. We show that such schemes are unacceptably insecure for key target applications such as electronic medical records. Second, we propose new models to compute on encrypted data and develop efficient constructions and systems. We propose a new cryptographic primitive called Blind Storage and show how it can be used to realize symmetric searchable encryption, which is much more secure than property-preserving encryption. 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