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IJSTR >> Volume 1 - Issue 7, August 2012 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Data Mining for Security Purpose & its Solitude Suggestions

[Full Text]

 

AUTHOR(S)

Shakir Khan, Dr. Arun Sharma, Abu Sarwar Zamani, Ali Akhtar

 

KEYWORDS

Index Terms— Data mining, security, safety, security suggestions, preserving data mining, data mining applications

 

ABSTRACT

Abstract- In this paper we first look at data mining applications in safety measures and their suggestions for privacy. After that we then inspect the idea of privacy and give a synopsis of the developments particularly those on privacy preserving data mining. We then present an outline for research on confidentiality and data mining.

 

REFERENCES

[1] Agrawal, R., Srikant, R.: Privacy-Preserving Data Mining. In: SIGMOD Conference,
pp. 439–450 (2000)

[2] Agrawal, R.: Data Mining and Privacy: Friends or Foes. In: SIGKDD Panel (2003)

[3] Kantarcioglu, M., Clifton, C.: Privately Computing a Distributed k-nn Classifier. In: Bou-licaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) PKDD 2004. LNCS, vol. 3202,279–290. Springer, Heidelberg (2004)

[4] Kantarcioglu, M., Kardes, O.: Privacy-Preserving Data Mining Applications in the Mali-cious Model. In: ICDM Workshops, pp. 717–722 (2007)

[5] Liu, L., Kantarcioglu, M., Thuraisingham, B.M.: The applicability of the perturbation based privacy preserving data mining for real-world data. Data Knowl. Eng. 65(1), 5–21 (2008)

[6] Liu, L., Kantarcioglu, M., Thuraisingham, B.M.: A Novel Privacy Preserving Decision Tree. In: Proceedings Hawaii International Conf. on Systems Sciences (2009)

[7] Thuraisingham, B.: One the Complexity of the Inference Problem. In: IEEE Computer Se-curity Foundations Workshop (1990) (also available as MITRE Report, MTP-291)

[8] Thuraisingham, B.M.: Privacy constraint processing in a privacy-enhanced database man-agement system. Data Knowl. Eng. 55(2), 159–188 (2005)

[9] Clifton, C.: Using Sample Size to Limit Exposure to Data Mining. Journal of Computer Security 8(4) (2000)