Research Article

A Novel Algorithm for Privacy Preserving Distributed Data Mining

by  Ehsan Molaei, Mehrdad Jalali, Hossein Vadiatizadeh
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 76 - Issue 8
Published: August 2013
Authors: Ehsan Molaei, Mehrdad Jalali, Hossein Vadiatizadeh
10.5120/13271-0800
PDF

Ehsan Molaei, Mehrdad Jalali, Hossein Vadiatizadeh . A Novel Algorithm for Privacy Preserving Distributed Data Mining. International Journal of Computer Applications. 76, 8 (August 2013), 43-47. DOI=10.5120/13271-0800

                        @article{ 10.5120/13271-0800,
                        author  = { Ehsan Molaei,Mehrdad Jalali,Hossein Vadiatizadeh },
                        title   = { A Novel Algorithm for Privacy Preserving Distributed Data Mining },
                        journal = { International Journal of Computer Applications },
                        year    = { 2013 },
                        volume  = { 76 },
                        number  = { 8 },
                        pages   = { 43-47 },
                        doi     = { 10.5120/13271-0800 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2013
                        %A Ehsan Molaei
                        %A Mehrdad Jalali
                        %A Hossein Vadiatizadeh
                        %T A Novel Algorithm for Privacy Preserving Distributed Data Mining%T 
                        %J International Journal of Computer Applications
                        %V 76
                        %N 8
                        %P 43-47
                        %R 10.5120/13271-0800
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

With the development of data mining science and information technology, distributed data mining was considered. Distributed data mining was submitted with different purposes, such as increasing the accuracy of result and using data from multiple sources. With the development of distributed data mining, challenges in this field were introduced soon. The main challenge was the issue of privacy preserving. In the past few years, solutions for this problem have been proposed but each one has had a weakness. Given the importance of knowledge, today's organizations need to Distributed Data Mining, Our goal in this article is to provide an approach that able to preserve the privacy in distributed mining. Our approach can be implemented on most of the algorithms. Proposed approach has been useed data encryption and some of techniques that used in security.

References
  • Dua, S. , Du, X. , Data Mining and Machine Learning in Cybersecurity, CRC press, 2011
  • Jiawei, H. n, Micheline K. , data mining: concepts and techniques, second edition, Elsevier, 2006
  • Lindell, Y. , Pinkas, B. , " privacy preserving data mining", journal of cryptology, springer, 2002
  • Aggarwal C. , C. , Yu, P. S. , Privacy-Preserving Data Mining-Models and Algorithms, springer, 2008
  • Winn, P,A. , Confidentiality in Cyberspace: The HIPAA Privacy Rules and the Common Law, 33 Rutgers L. J. 617 (2001-2002)
  • Giannotti, F. , Pedreschi, D. , Mobility Data Mining and Privacy, springer, 2007
  • Evfimievski, A. , Gehrke, J. , Srikant, R. , "Limiting Privacy Breaches in Privacy Preserving DataMining", ACM sigmod record, 2003
  • Brankovic, L. , Islam, Md. Z. , Giggins, H. , "privacy preserving data mining", security, privacy, and trust in modern data management, springer, 2007
  • FUNG, B. C. M. , WANG, K. , CHEN,R. , YU,PH. S. , " Privacy-Preserving Data Publishing: A Survey of Recent Developments", ACM, ACM Computing Surveys, Vol. 42, No. 4, Article 14, 2010
  • Magkos, E. , Maragoudakis, M. , Chrissikopoulos, V. , Gritzalis, S. ," Accurate and large-scale privacy-preserving data mining using the election paradigm",ELSEVIER, Data & Knowledge Engineering 68 ,1224–1236, 2009
  • Mukherjee, S. , Banerjee, M. , Chen,Zh. , A. Gangopadhyay, " A privacy preserving technique for distance-based classification with worst case privacy guarantees", Data & Knowledge Engineering 66, 264–288, 2008
  • Yi, X. , Zhang, Y. , "Privacy preserving Naive Bayes classificationon distributed data via semi-trusted mixers", Elsevier, Information Systems34, 371–380, 2009
  • Kantarc?oglu, M. , Vaidya, J. , "Privacy Preserving Naive Bayes Classifier for Horizontally Partitioned Data", ICDM Workshop on privacy preserving data mining, 2003
  • Yu, H. , Vaidya, J. , Jiang, X. , "Privacy-Preserving SVM Classification on Vertically Partitioned Data", springer, Volume 3918/2006, 647-656, 2006
  • Kantarcioglu, M. , Clifton, C. , Privacy-preserving distributed mining of association rules on horizontally partitioned data, IEEE Transanctions on Knowledge and Data Engineering 16 (9) (2004) 1026–1037
  • Shaneck, M. , Kim, Y. , Kumar, Vipin, " Privacy Preserving Nearest Neighbor Search" springer, 2009, Machine Learning in Cyber Trust, pp 247-276
  • Inan, A. , Kaya, S. V. , Saygin, Y. , Savas, E. , Hintoglu, A. A. , Levi, A. , privacy preserving clustering on horizontally partitioned data, Elsevier, 2007, Data & Knowledge Engineering 63 (2007) 646–666
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Privacy preserving data mining cryptography ID3 Bayesian classification

Powered by PhDFocusTM