Data Mining Over Encrypted Data of Database Client Engine Using Hybrid Classification Approach

Authors

  • Bhagyashree Ambulkar M. Tech. Scholar, Department of Computer Science and Engineering, Nagpur Institute of Technology, Nagpur, Nagpur, Maharashtra, India, Author
  • Gunjan Agre Department of Computer Science and Engineering, Nagpur Institute of Technology, Nagpur, Nagpur, Maharashtra, India, Author

Keywords:

AES Encryption Algorithm, , kNN classification, Privacy Preserving Classification, RTree

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. 

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References

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Published

2017-05-09

Issue

Vol. 5 No. 3 (2017): International Journal of Innovative Research in Computer Science & Technology(MAY)2017

Section

Articles

How to Cite

Data Mining Over Encrypted Data of Database Client Engine Using Hybrid Classification Approach . (2017). International Journal of Innovative Research in Computer Science & Technology, 5(3), 291–294. Retrieved from https://acspublisher.com/journals/index.php/ijircst/article/view/13485