Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/114265
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dc.date.accessioned2016-10-17T06:40:09Z-
dc.date.available2016-10-17T06:40:09Z-
dc.identifier.urihttp://hdl.handle.net/10603/114265-
dc.description.abstractData related to individual wealth, financial status and health is sensitive and to ensure confidentiality of these data special mechanism is required. For betterment of research and development, requirement is right input from authorized users. Due to personal confidentiality concerns, it is very difficult to get individuals sensitive information even if it is for mutual benefits. To get the real time data from actual users is critical to achieve extraordinary quality research outcomes. In collaborative computation participants are unwilling to provide straight answers when the questions involve personal information. The service providers who collect s data need to establish substantial trust with the parties. The confidentiality and integrity guarantees of the proposed protocols can simplify this issue. newlinePrivacy preservation is a big challenge for the data generated from various sources such as social networking sites, online transactions, weather forecast to name a few. The socialization of the internet and cloud computing generates pica bytes of unstructured data online with intrinsic values. The inflow of big data and the requirement to move this information throughout an organization has become a new target for hackers. The collaborative computation data is subject to confidentiality laws and should be protected. newlinePeople are more interested toward outsourcing work to a third party rather than maintaining their own resources, in this circumstance there is a requirement of insuring security from the service provider as it may lead to security breaches and party may not be interested in such service providers. newlineSecure multi-party computations deals with collection of challenges in which the requirement is the collaborative computation result. This computation needs input from multiple parties, but all the parties are concerned about their individual input.
dc.format.extent
dc.languageEnglish
dc.relationIEEE
dc.rightsuniversity
dc.titleDevelopment of Computational Techniques for Preserving Privacy Using Secure Multi Party Computation Protocols
dc.title.alternative
dc.creator.researcherShukla Samiksha
dc.subject.keywordComputation Security
dc.subject.keywordComputer Science
dc.subject.keywordMulti-Party Computations
dc.subject.keywordPrivacy and Confidentiality
dc.subject.keywordSecurity
dc.description.note
dc.contributor.guideG Sadashivappa
dc.publisher.placeBangalore
dc.publisher.universityCHRIST University
dc.publisher.institutionDepartment of Computer Science
dc.date.registered17-12-2012
dc.date.completed18/05/2015
dc.date.awarded19/10/15
dc.format.dimensions
dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

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02_certificate.pdf183.79 kBAdobe PDFView/Open
03_abstract.pdf189.72 kBAdobe PDFView/Open
04_declaration.pdf262.03 kBAdobe PDFView/Open
05_acknowledgement.pdf92.4 kBAdobe PDFView/Open
07_list_of_tables.pdf96.82 kBAdobe PDFView/Open
08_list_of_figures.pdf206.65 kBAdobe PDFView/Open
09_abbreivation.pdf86.69 kBAdobe PDFView/Open
10_chapter1.pdf651.39 kBAdobe PDFView/Open
11_chapter2.pdf552.33 kBAdobe PDFView/Open
12_chapter3.pdf517.18 kBAdobe PDFView/Open
13_chapter4.pdf712.63 kBAdobe PDFView/Open
14_chapter5.pdf758.99 kBAdobe PDFView/Open
15_chapter6.pdf1.62 MBAdobe PDFView/Open
16_chapter7.pdf369.65 kBAdobe PDFView/Open
17_bibliography.pdf412.95 kBAdobe PDFView/Open
18_list_of_publications.pdf200.3 kBAdobe PDFView/Open


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