Probabilistic Internal Privacy Intrusion Detection

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Xiangdong An Articles by Dawn Jutla Articles by Nick Cercone

10th International Database Engineering and Applications Symposium (IDEAS'06)

Delhi, India

December 11-December 14

ISBN: 0-7695-2577-6

	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

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

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

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.