Security Maintenance System in Data Mining Using Distance Measure Technique

  IJCOT-book-cover
 
International Journal of Computer & Organization Trends  (IJCOT)          
 
© 2013 by IJCOT Journal
Volume-3 Issue-1                          
Year of Publication : 2013
Authors :   K Anitha , M Chandra Naik

Citation

  K Anitha , M Chandra Naik Article: Security Maintenance System in Data Mining Using Distance Measure Technique . International Journal of Computer & organization Trends (IJCOT),V3(1):37-41 Jan - Feb 2013. Published by Seventh Sense Research Group.

Abstract

Now a days Security is the main thing in the databases . In this paper we focus on distance measures applied to ensure the security of the separate sensitive information. Protecting data security is an key issue in data distribution. Security maintains system in data mining using distance measure techniques typically aim to protect separate security , with minimal impact on the quality of the released data. Now days , a few of models are proposed to ensure the security protecting and/or to reduce the information loss as much as possible. i.e. , they further improve the flexibility of the anonymous strategy to make it more close ness to reality, and then to meet the diverse needs of the people. Different proposals and algorithms have been designed for them at the same time. In this scenario we provide a survey of distanc e measure techniqu es for security preserving. We discuss the distance measure methods , the major achievement ways and the strategies of distance measure algorithms, and summarize their advantage and disadvantage. Then we give a demonstration of the work finished . Finally c onclude further research directions of distance measure techniques by analyzing the existing work.

References

[1].Adam N., Wortmann J. C.: Security - Control Methods for Statistical Databases: A Comparison Study. ACM Computing Surveys, 21(4), 1989.
[2]. Agrawal R., Srikant R. Privacy - Preserving Data Mining. Proceedings of the ACM SIGMOD Conference, 2000.
[3]. Agrawal R., Srikant R., Thomas D. Privacy - Preserving OLAP. Pr oceedings of the ACM SIGMOD Conference, 2005.
[4]. Agrawal R., Bayardo R., Faloutsos C., Kiernan J., Rantzau R., Srikant R.: Auditing Compliance via a Hippocratic database. VLDBConference, 2004.
[5]. Agrawal D. Aggarwal C.C. On the Design and Quantifica tion of Privacy - Preserving Data Mining Algorithms.ACM PODS Conference, 2002.
[6]. Aggarwal C., Pei J., Zhang B. A Framework for Privacy Preservation against Adversarial Data Mining.ACM KDD Conference, 2006.
[7]. Aggarwal C.C. On k - anonymity and the curse of dimensionality.VLDB Conference, 2005.
[8]. Aggarwal C.C.,Yu P. S.: A Condensation approach to privacy preserving data mining. EDBT Conference, 2004.
[9]. Aggarwal C. C., Yu P. S.: On Variable Constraints in Privacy - Preserving Data Mining. SIAM Conference, 2005.
[10]. Aggarwal C. C.: On Randomization, Public Information and the Curse of Dimensionality. ICDE Conference, 2007.
[11]. Bawa M., Bayardo R. J., Agrawal R.: Privacy - Preserving Indexing of Documents on the Network. VLDB Conference, 2003.
[12]. Aggarwal. G., Feder. T., Kenthapadi. K., Motwani. R., Kiran. S Approximation Algorithms for k - anonymity. Journal of Privacy Technology, paper 2005.

Keywords

Privacy, Distance measure, Closeness, Anonymity