Data secure in horizontally distributed database using apriori algorithm

  • Authors

    • K Mariappan
    • G V. Sriramakrishnan
    • M Muthu Selvam
    • G Suseendran
    2018-05-29
    https://doi.org/10.14419/ijet.v7i2.31.13428
  • Association rules, distributed computation, frequent item sets, privacy preserving data mining.

  • Abstract

    Data mining strategies are utilized as a part of business and explore and are ending up increasingly prominent with time. Information mining can remove valuable data from substantial databases. Most proficient methodologies for mining circulated databases assume that the majority of the information at each site can be shared and conveyed database is use to designate diverse database in various area. Affiliation govern mining is a critical research territory in information mining, which shows relations among thing sets in database[1].The convention, relies upon Fast Distributed Mining (FDM), [2]which is unsecured rendition of Apriori calculation. The reason for the Apriori Algorithm is to discover relationship between various arrangements of information [3].In this undertaking, for information mining, administrator will take after FDM calculation by influencing relationship to run the show. Association of every single private subset will be finished by utilizing affiliation run the show. (In our application affiliation manage shaped for the qualification of a possibility for work)

     

     

  • References

    1. [1] Kantarcioglu M & Clifton C, “Privacy preserving distributed mining of association rules on horizontally partitioned dataâ€, IEEE Knowledge and Data Engineering, (2004).

      [2] Cheung DWL, Han J, Ng VTY, Fu AWC & Fu Y, “A fast distributed algorithm for mining association rulesâ€, PDIS, (1996.

      [3] Cheung DWL, Ng VTY, Fu AWC & Fu Y,â€Efficient mining of association rules in distributed databasesâ€, IEEE Trans. Knowl. DataEng., (1996).

      [4] Beaver D, Micali S & Rogaway P, “The round complexity of secure protocolsâ€, STOC, (1990), pp.503–513.

      [5] Tassa T & Gudes E, “Secure distributed computation of anonymized views of shared databasesâ€, Transactions on Database Systems, (2012).

      [6] Srikant R & Agrawal R, “Mining generalized association rulesâ€, VLDB, (1995), pp.407–419

      [7] Evfimievski AV, Srikant R, Agrawal R & Gehrke J, “Privacy Preserving mining of association rulesâ€, KDD, (2002), pp.217–228.

      [8] Fagin R, Naor M & Winkler P, “Comparing Information WithoutLeaking Itâ€, Communications of the ACM, (1996).

      [9] Freedman M, Ishai Y, Pinkas B & Reingold O, “Keyword search and oblivious pseudorandom functionsâ€, TCC, (2005), pp.303–324.

      [10] Yao AC, “Protocols for secure computationâ€, FOCS, (1982), pp.160–164.

      [11] Zhan J, Matwin S & Chang L, “Privacy preserving collaborative association rule miningâ€, Data and Applications Security, (20005), pp.153–165.

      [12] Zhong S, Yang Z & Wright RN, “Privacy-enhancing kanonymization of customer dataâ€, PODS, (2005), pp.139–147.

  • Downloads

  • How to Cite

    Mariappan, K., V. Sriramakrishnan, G., Muthu Selvam, M., & Suseendran, G. (2018). Data secure in horizontally distributed database using apriori algorithm. International Journal of Engineering & Technology, 7(2.31), 146-149. https://doi.org/10.14419/ijet.v7i2.31.13428

    Received date: 2018-05-29

    Accepted date: 2018-05-29

    Published date: 2018-05-29