Privacy Preserving Data Mining Using Random Rotation Based Data Perturbation Technique

Authors

  • AshaKatharotiya Department of Computer science &Engineering PatelInstitute OfEngineering&Science, Bhopal,India
  • Pankajkawadkar H.O.D. computer science dept., PIES, Bhopal, PatelInstitute OfEngineering&Science, Bhopal,India

Keywords:

Privacy;DataStreams;K-meansclustering

Abstract

-To preserve privacy of data, privacy preserving data mining is the study of valid mining patterns and models
which mask private information. There are many privacy preserving data mining techniques which have been studied.one
crucial concept about existing data mining privacy preserving techniques are suitable and designed for static databases and
not suitable for data streams.Recently,data streams are introduced as new type of data which are differ from traditional
static data. Various features of data streams are: with time, data distribution changes constantly; data is having time
preferences; amount of data is extensive; flow of data with fast speed; requirement of immediate response. When has been
modified, it would be necessary to rescan whole database, so it leads to more computation time and inability to respond the
user fastly.Further,it is observed that accuracy of data is decreases when transformation is carried out on data.so,there has
been need to develop the system which preserve privacy along with accuracy. So privacy preserving on data stream mining is
very crucial issue.

Published

2015-05-25

How to Cite

AshaKatharotiya, & Pankajkawadkar. (2015). Privacy Preserving Data Mining Using Random Rotation Based Data Perturbation Technique. International Journal of Advance Engineering and Research Development (IJAERD), 2(5), 231–242. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/818