A Brief Survey of Secrecy Protective Data Mining (SPDM)

V. Uthaman

Abstract


The secrecy protective data mining is assuming urgent part go about as rising innovation to perform different data mining operations on private data and to pass on data in a secured approach to ensure delicate data. Many sorts of system, for example, randomization, secured aggregate calculations and k-anonymity have been recommended with a specific end goal to execute secrecy protective data mining. In this overview paper, on ebb and flow examines made on secrecy protective data mining strategy with fuzzy logic, neural network learning, secured total and different encryption calculation is displayed. This will empower to get a handle on the different difficulties confronted in secrecy protective data mining and furthermore help us to discover best reasonable procedure for different data condition.

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References


Mi Wen, Rongxing Lu, Jingshen Lei, Xiaohui Liang, 2013, “ECQ: An Efficient Conjunctive Query Scheme Over Encrypted Multidimensional Data in Smart Grid”, Global Communications Conference (GLOBECOM), 2013 IEEE, 796 – 801.

Mittal D, Kaur D, Aggarwal A. 2014, “Secure Data Mining in Cloud Using Homomorphic Encryption” IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), 2014, pp: 1 – 7.

Mukkamala R., Ashok V.G, 2011 “Fuzzy-based Methods for Privacy-Preserving Data Mining” Eighth International Conference on Information Technology: New Generations (ITNG), pp: 348 – 353.

Inan A, Richardson TX, Kantarcioglu M., Bertino E., 2009, “Using Anonymized Data for Classification”, IEEE 25th International Conference on Data Engineering, 2009. ICDE '09., pp : 429-430.

Pathak F.A.N, Pandey S.B.S., 2013, “An Efficient Method For Privacy Preserving Data Mining In Secure Multiparty Computation”, Nirma University International Conference on Engineering (NUiCONE), 2013, pp: 1 – 3 Pathak, F.A.N., Pandey, S.B.S., 2013.

Pathak F.A.N, Pandey S.B.S, 2013, “Distributed Changing Neighbors K-Secure Sum Protocol For Secure Multiparty Computation”, Nirma University International Conference on Engineering (NUiCONE), 2013, pp: 1 – 3.

Shweta Taneja, Shashank Khanna, Sugandha Tilwalia, Ankita, 2014, “A Review on Privacy Preserving Data Mining: Techniques and Research Challenges”, International Journal of Computer Science and Information Technologies, Vol. 5 (2), 2014, pp: 23102315.

Shu Qin Ren, Khin Mi Mi Aung, Jong Sou Park, 2010, “A Privacy Enhanced Data Aggregation Model”, Computer and Information Technology (CIT), 2010 IEEE 10th International Conference on, pp: 985 – 990.

SathiyaPriya K, Sadasivam G.S, Celin N. 2011, “A New Method For Preserving Privacy In Quantitative Association Rules Using DSR Approach With Automated Generation Of Membership Function”, World Congress on Information and Communication Technologies (WICT), 2011, pp: 148-153.

Honda K, Kawano A, Nots A, Ichihashi H., 2012, “A fuzzy variant of k-member clustering for collaborative filtering with data anonymization”, Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on, pp: 1-6.

Hasan O, Bertino E, Brunie L. 2010, “Efficient privacy preserving reputation protocols inspired by secure sum”, Privacy Security and Trust (PST), 2010 Eighth Annual International Conference on, pp: 126 – 133.

Jian Wang, Yongcheng Luo, Yan Zhao, Jiajin Le, 2009, “A Survey on Privacy Preserving Data Mining”, First International Workshop on Database Technology and Applications, 2009, pp: 111-114.

Jiang, J. and Umano, M. 2014, “Privacy preserving extraction of fuzzy rules from distributed data with different attributes”, Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on Soft Computing and Intelligent Systems (SCIS), 2014, pp : 1180-1185.

Kabir S.M.A, Youssef A.M, Elhakeem, A.K., 2007, “On Data Distortion for Privacy Preserving Data Mining”, Canadian Conference on Electrical and Computer Engineering, 2007. CCECE 2007. pp : 308 – 311.




DOI: https://doi.org/10.23956/ijarcsse.v7i8.40

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