Literature Survey of Association Rule Based Techniques for Preserving Privacy

Authors

  • Patidar V ITM, Bhilwara
  • Raghuvanshi A M.Tech (MIT, Ujjain)
  • Shrivastava V Department of Information Technology, Head of Department, ITM College, Bhilwara, Rajasthan, India

Keywords:

data mining, sensitive data, cryptography

Abstract

The paper gives an overview of privacy preserving in association rule mining techniques. In this paper, all the present privacy preserving using association rule hiding techniques are discussed. This paper also proposes a classification hierarchy that sets the basis for analyzing the work which has been performed in this context. A detailed review of the work accomplished in this area is also given, along with the coordinates of each work to the classification hierarchy.

References

Nabil Adam and John C. Wortmann, Security- Control Methods for Statistical Databases: A Comparison Study, ACM Computing Surveys 21 (1989), no. 4, 515–556.

Dakshi Agrawal and Charu C. Aggarwal, On the design and quantification of privacy preserving data mining algorithms, In Proceedings of the 20th ACM Symposium on Principles of Database Systems (2001), 247–255.

Rakesh Agrawal and Ramakrishnan Srikant, Privacy-preserving data mining, In Proceedings of the ACM SIGMOD Conference on Management of Data (2000), 439–450.

Mike J. Atallah, Elisa Bertino, Ahmed K. Elmagarmid, Mohamed Ibrahim, and Vassilios S. Verykios, Disclosure Limitation of Sensitive Rules, In Proceedings of the IEEE Knolwedge and Data Engineering Workshop (1999), 45–52.

LiWu Chang and Ira S. Moskowitz, Parsimonious downgrading and decision trees applied to the inference problem, In Proceedings of the 1998 New Security Paradigms Workshop (1998), 82– 89.

LiWu Chang and Ira S. Moskowitz, An integrated framework for database inference and privacy protection, Data and Applications Security (2000), 161–172, Kluwer, IFIP WG 11.3, The Netherlands.

David W. Cheung, Jiawei Han, Vincent T. Ng, Ada W. Fu, and Yongjian Fu, A fast distributed algorithm for mining association rules, In Proceedings of the 1996 International Conference on Parallel and Distributed Information Systems (1996).

Chris Clifton, Murat Kantarcioglou, Xiadong Lin, and Michael Y. Zhu, Tools for privacy preserving distributed data mining,

SIGKDDExplorations 4 (2002), no. 2.

Chris Clifton and Donald Marks, Security and privacy implications of data mining, In Proceedings of the ACM SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery (1996), 15–19.

Elena Dasseni, Vassilios S. Verykios, Ahmed K. Elmagarmid, and Elisa Bertino, Hiding Association Rules by using Confidence and Support, In Proceedings of the 4th Information Hiding Workshop (2001), 369–383.

Wenliang Du and Mikhail J. Attalah, Secure multiproblem computation problems and their applications: A review and open problems, Tech.

Wenliang Du and Zhijun Zhan, Building decision tree classifier on private data, In Proceedings of the IEEE ICDM Workshop on Privacy, Security and Data Mining (2002).

Alexandre Ev.mievski, Ramakrishnan Srikant, Rakesh Agrawal, and Johannes Gehrke, Privacy preserving mining of association rules, In Proceedings of the 8th ACM SIGKDDD International Conference on Knowledge Discovery and Data Mining (2002).

Ioannis Ioannidis, Ananth Grama, and Mikhail Atallah, A secure protocol for computing dot products in clustered and distributed environments, In Proceedings of the International Conference on Parallel Processing (2002).

Murat Kantarcioglou and Chris Clifton, Privacypreserving distributed mining of association rules on horizontally partitioned data, In Proceedings of the ACM SIGMOD Workshop on Research Isuues in Data Mining and Knowledge Discovery (2002), 24–31.

Yehuda Lindell and Benny Pinkas, Privacy preserving data mining, In Advances in Cryptology - CRYPTO 2000 (2000), 36–54.

Ira S. Moskowitz and LiWu Chang, A decision theoretical based system for information downgrading, In Proceedings of the 5th Joint Conference on Information Sciences (2000).

Daniel E. O’Leary, Knowledge Discovery as a Threat to Database Security, In Proceedings of the 1st International Conference on Knowledge Discovery and Databases (1991), 107–516.

Stanley R. M. Oliveira and Osmar R. Zaiane, Privacy preserving frequent itemset mining, In Proceedings of the IEEE ICDM Workshop on Privacy, Security and Data Mining (2002), 43– 54.

Shariq J. Rizvi and Jayant R. Haritsa, Maintaing data privacy in association rule mining, In Proceedings of the 28th International Conference on Very Large Databases (2002).

Yucel Saygin, Vassilios Verykios, and Chris Clifton, Using unknowns to prevent discovery of association rules, SIGMOD Record 30 (2001), no. 4, 45–54.

Yucel Saygin, Vassilios S. Verykios, and Ahmed K. Elmagarmid, Privacy preserving association rule mining, In Proceedings of the 12th International Workshop on Research Issues in Data Engineering (2002), 151–158.

Jaideep Vaidya and Chris Clifton, Privacy preserving association rule mining in vertically partitioned data, In the 8th ACMSIGKDD International Conference on Knowledge Discovery and Data Mining (2002), 639–644.

Vassilios S. Verykios, Ahmed K. Elmagarmid, Bertino Elisa, Yucel Saygin, and Dasseni Elena, Association Rule Hiding, IEEE Transactions on Knowledge and Data Engineering (2003), Accepted

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Published

2024-02-26

How to Cite

Patidar, V. K., Raghuvanshi, A., & Shrivastava, V. (2024). Literature Survey of Association Rule Based Techniques for Preserving Privacy. COMPUSOFT: An International Journal of Advanced Computer Technology, 2(03), 59–64. Retrieved from https://ijact.in/index.php/j/article/view/13

Issue

Section

Review Article

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