Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IDEAS.2006.38 | IDEAS |
Keywords | Field | DocType |
database system,intrusion detection,probabilistic method,bayesian networks,database systems,database management systems,data privacy,statistical distributions | Data mining,Internet privacy,Computer science,Computer security,Probabilistic logic,Information privacy,Intrusion detection system,Privacy software,Probabilistic method,Insider,Bayesian network,Database,Probabilistic database | Conference |
ISSN | ISBN | Citations |
1098-8068 | 0-7695-2577-6 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangdong An | 1 | 64 | 13.56 |
| Dawn N. Jutla | 2 | 256 | 43.33 |
| Nick Cercone | 3 | 1999 | 570.62 |