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A review study on the privacy preserving data mining techniques and approaches

A review study on the privacy preserving data mining techniques and approaches
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  A review study on the privacy preserving datamining techniques and approaches Injamul Islam (12-22101-2) American International University Bangladesh Abstract.  With the highest amount of data stored in databases is veryimportant to develop effective mean for analysis and interpretation of such data for extract interesting knowledge that helps to make decision.Data mining is such a technique which releases the important informationfrom the large repositories. In this paper we review accomplishments pri-vacy database , data modification followed by the future research work. Keywords:  Data Mining, Privacy Preserving, privacy preserving techniques,data modification 1 Introduction Security and privacy protection have been common policy for many years. How-ever, system changes the first development of the internet and electronic com-merce and the improvement of more sensitive methods of collecting analyzingand using personal data have made privacy a serious global issues. In today’sglobal map e-commerce, e-government and personal data is distributed online,privacy of information has become more important topic. Information in miningis sensitive. For example, medical institute wish to make a medical thesis whilepreserving the privacy record of their patient.In this situation , it is necessary topreserve the sensitive information and as well as enable its use for future the commercial terms privacy preserving big data technology is still inthe research paper. However the research may have had impact on privacy vsdata mining debate throw the reseacher it is found that the debate has becomemore reasoned[1]. 2 Concern related to privacy throw data mining As we know that big data is widely used technique large institution data min-ing is incorporate in day to day operational works of every institution duringthe process of data mining to get the data. This data may content sophisti-cated information of individual person. Disclosure of search information resultsbreakdown of personal privacy. Personal information can also be disclosed byconnecting various databases under to big data warehouse and accessing webdata[2].  3 Misuse of data does not require data mining Most higher level incidents of misuse of personal data does not have correlationwith data is problem with security of the database. The USACM letterquestioning the total data awareness program recognized this. It is most higherlevel privacy branches are similar. It is poor security of the database the leadsto the breach[3]. 4 Using sophisticated business data Privacy preserving data mining technology can be used to protect sophisticateddata that is not related with personal privacy . institution may need saturatedata secret from collaborators but still wished to use correlated data from com-mon analytical purpose. One department where this has been investigated is insupply chain management[4], other departments surely exist where a businessincident can be made for use of privacy preserving data analysis. 5 Privacy preserving data mining Due to excellent benefit of big data and large public concern regarding personaldata privacy implementation of privacy preserving data mining has become de-mand of todays nature. This technique provides personal privacy while at thesame time allowing release of useful information form of data. High data qualitywith security is the top requirement of good privacy preserving techniques.Thereare couple of techniques of privacy preserving. 5.1 Data modification Existing privacy preserving techniques method for centralized databases can becategorized in three main groups based on the approaches they take, such asquery restriction, output perturbation and data modification [5]. From all thesetechniques data modification is a straightforward technique to implement. 5.2 Data swapping Data swapping technique were first introduced by Splenius and Remiss in 1982,for categorical values modification in the context of secure statistical databases.To keep the srcinal value of data set is the main idea of this method. Thismethod actually replace the srcinal data set by another one where some srci-nal values belonging to a sensitive attributes are exchanged between them. Anintroduction to existing data swapping technique can be found in [6].  5.3 Suppression In this technique sensitive data value are deleted or suppressed prior to the re-lease of a micro data. Suppression is used to protect an individual privacy fromintruders attempt to accurately predict a suppressed value [7]. 6 Conclusion In this paper we present the detailed study about the privacy preserving datamining and briefly review the techniques Data Modification. To prove this methodefficiency an algorithm and experiment must be needed which can provided theefficiency of that particular techniques.This is a challenge and an opportunity;while must has been done ,the new problems that are arising are even greater. References 1. Shanthi, a.S., Karthikeyan, M.: A review on privacy preserving data mining. Iccic 5 (2) (2012) 1–42. Clifton, C., Clifton, C., Jiang, W., Jiang, W., Muruguesan, M., Muruguesan, M.,Lafayette, W., Lafayette, W., Nergiz, M.E., Nergiz, M.E.: Is Privacy Still an Issuefor Data Mining? Evaluation (C) (2008) 2005–20083. Lindell, Y., Pinkas, B.: Privacy-preserving data mining. Advances in CryptologyCRYPTO 2000  29 (2) (2000) 36–544. Clifton, C., Kantarcioglu, M., Vaidya, J., Lin, X., Zhu, M.Y.: Tools for privacypreserving distributed data mining. ACM SIGKDD Explorations Newsletter  4 (2)(2002) 28–345. Sharma, M., Chaudhary, A., Mathuria, M., Chaudhary, S.: A Review Study on thePrivacy Preserving Data Mining Techniques and Approaches.  4 (9) (2013)6. Prof-it, A.: An Empirical Study on Privacy Preserving Data Mining.  3  (2012)687–6937. Rao, K.S., Rao, B.S.: An Insight in to Privacy Preserving Data.  1 (3) (2013) 100–104
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