Probabilistic Internal Privacy Intrusion Detection

Delhi, India December 11-December 14

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http://doi.ieeecomputersociety.org/10.1109/IDEAS.2006.38

10th International Database Engineeri ...

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	ASCII Text	x
	Xiangdong An, Dawn Jutla, Nick Cercone, "Probabilistic Internal Privacy Intrusion Detection," Database Engineering and Applications Symposium, International, pp. 317-318, 10th International Database Engineering and Applications Symposium (IDEAS'06), 2006.

	BibTex	x
	@article{ 10.1109/IDEAS.2006.38, author = {Xiangdong An and Dawn Jutla and Nick Cercone}, title = {Probabilistic Internal Privacy Intrusion Detection}, journal ={Database Engineering and Applications Symposium, International}, volume = {0}, year = {2006}, issn = {1098-8068}, pages = {317-318}, doi = {http://doi.ieeecomputersociety.org/10.1109/IDEAS.2006.38}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Database Engineering and Applications Symposium, International TI - Probabilistic Internal Privacy Intrusion Detection SN - 1098-8068 SP317 EP318 A1 - Xiangdong An, A1 - Dawn Jutla, A1 - Nick Cercone, PY - 2006 KW - null VL - 0 JA - Database Engineering and Applications Symposium, International ER -

Xiangdong An, Saint Mary?s University

Dawn Jutla, Saint Mary?s University

Nick Cercone, Dalhousie University

Many organizations need to maintain a lot of private data to run their businesses. Private data could be violated by both the inside and the outside intruders. In this paper, we propose a probabilistic method to detect insider privacy intrusion in database systems.

Citation:

Xiangdong An, Dawn Jutla, Nick Cercone, "Probabilistic Internal Privacy Intrusion Detection," ideas, pp.317-318, 10th International Database Engineering and Applications Symposium (IDEAS'06), 2006

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