Privacy Preserving Classification over Encrypted Data

  • Supriya Palwe

Abstract

Classification is one of the commonly used tasks in data mining applications. Data Mining has wide applications in many areassuch as banking, medicine, scientific research and amonggovernment agencies. With the recent algorithms of databasecomputing, users now have the opportunity to outsource heirdata, in encrypted form, as well as the data mining tasks to thedatabase. Since the data on the database is in encrypted form,existing privacy-preserving classification techniques are notapplicable. That’s why in this system, we will be focusing on solving the classification problem over encrypted data. Inparticular, we are going to use a secure k-NN classifier over encrypted data in the database. We can implement new “blockcipher “algorithm for new advanced Encryption Standard. Wecan also protect the confidentiality of data, privacy of user’s input query, and hide the data access patterns. Therefore byanalyzing the efficiency of the protocol we will be checkingdataset under different parameters.
Published
2016-04-06
How to Cite
PALWE, Supriya. Privacy Preserving Classification over Encrypted Data. International Journal Of Emerging Technology and Computer Science, [S.l.], v. 1, n. 1, apr. 2016. ISSN 2455-9954. Available at: <https://aspirepublishers.com/index.php/ijetcs/article/view/13>. Date accessed: 23 july 2019.