Show simple item record

dc.contributor.authorParameswaran, Rupaen_US
dc.date.accessioned2006-09-01T19:05:07Z
dc.date.available2006-09-01T19:05:07Z
dc.date.issued2006-05-10en_US
dc.identifier.urihttp://hdl.handle.net/1853/11459
dc.description.abstractPrivacy is defined as the freedom from unauthorized intrusion. The availability of personal information through online databases, such as government records, medical records, and voters and #146; lists, pose a threat to personal privacy. The concern over individual privacy has led to the development of legal codes for safeguarding privacy in several countries. However, the ignorance of individuals as well as loopholes in the systems, have led to information breaches even in the presence of such rules and regulations. Protection against data privacy requires modification of the data itself. The term {em data obfuscation} is used to refer to the class of algorithms that modify the values of the data items without distorting the usefulness of the data. The main goal of this thesis is the development of a data obfuscation technique that provides robust privacy protection with minimal loss in usability of the data. Although medical and financial services are two of the major areas where information privacy is a concern, privacy breaches are not restricted to these domains. One of the areas where the concern over data privacy is of growing interest is collaborative filtering. Collaborative filtering systems are being widely used in E-commerce applications to provide recommendations to users regarding products that might be of interest to them. The prediction accuracy of these systems is dependent on the size and accuracy of the data provided by users. However, the lack of sufficient guidelines governing the use and distribution of user data raises concerns over individual privacy. Users often provide the minimal information that is required for accessing these E-commerce services. The lack of rules governing the use and distribution of data disallows sharing of data among different communities for collaborative filtering. The goals of this thesis are (a) the definition of a standard for classifying DO techniques, (b) the development of a robust cluster preserving data obfuscation algorithm, and (c) the design and implementation of a privacy-preserving shared collaborative filtering framework using the data obfuscation algorithm.en_US
dc.format.extent3739541 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectData privacyen_US
dc.subjectData obfuscation
dc.subjectData mining
dc.subjectCollaborative filtering
dc.subject.lcshData miningen_US
dc.subject.lcshInformation storage and retrieval systemsen_US
dc.subject.lcshCluster analysis Computer programsen_US
dc.subject.lcshDatabase securityen_US
dc.titleA Robust Data Obfuscation Technique for Privacy Preserving Collaborative Filteringen_US
dc.typeDissertationen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.advisorCommittee Chair: Blough, Douglas; Committee Member: Fekri, Faramarz; Committee Member: Navathe, Sham; Committee Member: Schimmel, David; Committee Member: Wills, Lindaen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record