Hybrid Privacy Preserving Mechanism: An Approach to ProtectHealth Care DataAuthor : M.Rameshkumar and V. Lakshmipraba
Volume 7 No.1 January-June 2018 pp 71-78
With a lot of clinical information produced regularly, efficient methods have to be used to unearth significant data. Securing the information from the unapproved clients is also a major task to be achieved. Though lot of research has been carried out in these areas separately, a Hybrid architecture which combines both the features – efficiency and security is not widely found. The proposed architecture has been built taking these aspects into consideration. A proficient strategy for cross breed information mining method is applied here which incorporates the combination of Navie Bayesian classifier and Homomorphic encryption calculation.
Homomorphic, Bayesian classifier, Privacy preserving, Prediction of cancer
 Mehrnoosh, Monshizadeh and Zheng Yan, “Security Related Data Mining”, IEEE International Conference on Computer and Information Technology, pp. 775 – 782, 2014.
 Dileep Kumar Singh and Vishnu Swaroop, “Data Security and Privacy in Data Mining: Research Issues & Preparation”, International Journal of Computer Trends and Technology, Vol. 4, No.2, pp. 194-200, 2013.
 E Bertino, I.N. Fovino and L.P Provenza, , “A Framework for Evaluating Privacy Preserving Data Mining Algorithms”, Data Min Knowledge Disc, Vol. 11, No. 2, pp. 121–154, 2005.
 Kemal polat and Salih Gunes, “A novel hybrid intelligent method based on C4.5 decision tree classifier and one-against-all approach for multi-class classification problems”, Expert Systems with Applications, Elsevier, Vol. 36, No. 2, Part 1, pp. 1587-1592, 2009.
 R.W.K Leung, H.C.W. Lau and C.K. Kwong, “On a responsive replenishment system: a fuzzy logic approach”, Expert Systems, Vol. 20, pp. 20-32, 2003.
 A Inokuchi, T Washio and H Motoda, “An apriori-based algorithm for mining frequent substructures from graph data,” Proceedings of the Fourth European Symposium on the Principle of Data Mining and Knowledge Discovery, Lyon, France, pp.13-23, 2000.
 Mohammad Khubeb, Siddiqui and Shams Naahid, International Journal of Database Theory and Application, Vol. 6, No. 5, pp. 23-34, 2013.
 CC Aggarwal and PS Yu, “A General Survey of Privacy-Preserving Data Mining Models and Algorithms”, Springer, Boston,MA Vol. 34, pp. 11-52, 2008.
 J.B. Awotunde, O.E. Matiluko and O.W Fatai , “Medical Diagnosis System Using Fuzzy Logic”, Afr J Comp and ICT, Vol. 7. No.2, pp. 99-106, 2014.
 S Das, D Guha, and B Dutta, “Medical diagnosis with the aid of using fuzzy logic and intuitionistic fuzzy logic”, Appl. Intell., Vol. 45, No. 3, pp. 850–867, 2016.
 K.M. Al-Aidaroos, A.A. Bakar and Z. Othman, “Medical Data Classification with Naive Bayes Approach”, Information Technology Journal, Vol. 11, pp.1166-1174, 2012.
 Tung-Shou Chen, Jeanne Chen and Yuan-Hung Kao, “A Novel Hybrid Protection Technique of Privacy-Preserving Data Mining and Anti-Data Mining”, Information Technology Journal, Vol. 9, pp. 500-505, 2010.
 V. Subramaniyaswamy and S. Chenthur Pandian, “A Complete Survey of Duplicate Record Detection Using Data Mining
Techniques”, Information Technology Journal, Vol. 11 pp. 941-945, 2012.
 S Dhanashree Medhekar, Mayur P Bote, Shruti D and Deshmukh, “Heart Disease Prediction System using Naive Bayes”, International Journal of Enhanced Research in Science Technology and Engineering, Vol. 2, No. 3, pp. 1-5, 2013.
 J Jossinet and Physiol Meas, “The impedivity of freshly excised human breast tissue”, Vol. 19, No. 1, pp. 61-75, 1998.
 K Julie, MD Taitsman, Christi Macrina, M.P.A Grimm and MD Shantanu Agrawal, “Protecting Patient Privacy and Data Security”, The New England Journal Of Medicine, Vol. 14, pp. 977-979, 2013.
 Adriana Lopez-Alt, Eran Tromer and Vinod Vaikuntanathan, “On-the-Fly Multiparty Computation on the Cloud via Multikey Fully Homomorphic Encryption”, ISBN: 978-1-4503-1245-5NY, USA, : Proceeding STOC ’12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing Pp. 1219-1234, 2013.
 Mohammad Khubeb Siddiqui and Shams Naahid, “Analysis of KDD CUP 99 Dataset using Clustering based Data Mining”, International Journal of Database Theory and Application, Vol. 6, No. 5, pp. 23-34, 2013.
 Y. Dhanalakshmi and Dr I, Ramesh Babu, “Intrusion Detection Using Data Mining Along Fuzzy Logic and Genetic Algorithms”, IJCSNS International Journal of Computer Science and Network Security, Vol. .8, No. 2, pp. 27-32, 2008.
 Rahul Deo Sah and Dr Jitendra Sheetalani, “Review of Medical Disease Symptoms Prediction Using Data Mining Technique”, IOSR Journal of Computer Engineering (IOSR-JCE), Vol. 19, No. 3, Ver. I, pp. 59-70, 2017.
 J Kamber, M. Han and J Pei, “Data Mining Concepts and Techniques. Morgan Kaufmann Publishers”, San Francisco. 2012.
 Mevlut Ture, “Using Kaplan–Meier analysis together with decision tree methods (C&RT, CHAID, QUEST, C4.5 and ID3) in determining recurrence-free survival of breast cancer patients”, Elsevier, Vol. 36, No. 2, pp. 2017-2026, 2009.
 Pradeep Kumar, Kishore Indukuri Varma and Ashish Sureka,“Fuzzy based clustering algorithm for privacy preserving data mining”, Int. J. Business Information Systems, Vol. 7, No. 1, pp 27-40, 2011.
 A.R. Aronson, “Effective mapping of biomedical text to the UMLS Meta thesaurus: the Meta Map program”, Proc. AMIA Symp., pp.17–21, 2001.
 A. Sung and S. Mukkamala, “Identifying important features for intrusion detection using SVM and neural networks”, in symposium on application and the Internet, pp. 209-216, 2003.