Indexing Metadata

1 Title of the Article Data Mining Over Encrypted Data of Database Client Engine Using Hybrid Classification Approach
2 Author's name Bhagyashree Ambulkar: M. Tech. Scholar, Department of Computer Science and Engineering, Nagpur Institute of Technology, Nagpur, Nagpur, Maharashtra, India, 9763316989.
3 Author's name Prof. Gunjan Agre
4 Subject Computer Science and Engineering
5 Keyword(s) AES Encryption Algorithm, kNN classification, Privacy Preserving Classification, RTree.
6 Abstract

Data mining has been used in various areas, for example crime agencies, retail industries, financial data analysis, telecommunication industry, biological, among government agencies, etc. Several application handle very delicate data. So these data remains secure and private. In data mining, Classification could be the one of the major task. Going back two full decades various privacy issues are occurs so that many conceptual and feasible solutions to the classification problem have been developed. Similarly daily cloud user is increment tremendously and they have a big possibility to process the offload the information an encrypted form. The information in the cloud has been in encrypted form, recent privacy preserving classification systems are not feasible. In this paper, our proposed hybrid method provides privacy -preserving classifier for encrypted data of relational database and also achieves the marginally better performance for extracting information using k-NN algorithm from encrypted data of relational databases. This paper describes AES encryption technique which is highly secure and efficient.

7 Publisher Innovative Research Publication
8 Journal Name; vol., no. International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-5 Issue-3
9 Publication Date May 2017
10 Type Peer-reviewed Article
11 Format PDF
12 Uniform Resource Identifier https://ijircst.org/view_abstract.php?title=Data-Mining-Over-Encrypted-Data-of-Database-Client-Engine-Using-Hybrid-Classification-Approach&year=2017&vol=5&primary=QVJULTMwMw==
13 Digital Object Identifier(DOI) 10.21276/ijircst.2017.5.3.7   https://doi.org/10.21276/ijircst.2017.5.3.7
14 Language English
15 Page No 291-294

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