Adjacent Contiguous Categorization over Semantically Secured Records
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 3
Abstract
Data Mining has large applications in many areas such as banking, medicine, scientific research and among government agencies. But due to the rise of many security issues, many theoretical and practical solutions to the classification problem have been proposed under different security models. However, users now have the opportunity to outsource their data, in encrypted form, to the cloud. Since the data on the cloud is in encrypted form, existing privacy-preserving classification techniques are not applicable. This model focus on solving the classification problem over encrypted data. In particular, propose a secure k-NN classifier over encrypted data in the cloud. The proposed protocol protects the confidentiality of data, privacy of user’s input query, and hides the data access patterns. The secure k-NN classifier over encrypted data is developed under the semi- honest model.
Authors and Affiliations
C. Subathra, M. S. VijayKumar
Keywords
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