论文信息 - An Integrated Framework for Database Privacy Protection

An Integrated Framework for Database Privacy Protection

One of the central objectives of studying database privacy protection is to protect sensitive information held in a database from being inferred by a generic database user. In this paper, we present a framework to assist in the formal analysis of the database inference problem. The framework is based on an association network which is composed of a similarity measure and a Bayesian network model.

Ira S. Moskowitz | LiWu Chang

[1] 田村藤嗣彦,et al. C-4-5 屈折率分布型ポリマー光ファイバーレーザーの発振特性 , 1999 .

[2] Judea Pearl,et al. Probabilistic reasoning in intelligent systems , 1988 .

[3] David Heckerman,et al. Bayesian Networks for Knowledge Discovery , 1996, Advances in Knowledge Discovery and Data Mining.

[4] Bhavani Thuraisingham,et al. Data Mining: Technologies, Techniques, Tools, and Trends , 1998 .

[5] Jun S. Liu,et al. Sequential Imputations and Bayesian Missing Data Problems , 1994 .

[6] D.G. Marks,et al. Inference in MLS Database Systems , 1996, IEEE Trans. Knowl. Data Eng..

[7] Tsau Young Lin,et al. Security and Data Mining , 1995, DBSec.

[8] Randall P. Wolf,et al. Protecting databases from inference attacks , 1997, Comput. Secur..

[9] H FriedmanJerome. On Bias, Variance, 0/1Loss, and the Curse-of-Dimensionality , 1997 .

[10] E Hansen. HIPAA (Health Insurance Portability and Accountability Act) rules: federal and state enforcement. , 1997, Medical interface.

[11] Ira S. Moskowitz,et al. Bayesian Methods Applied to the Database Inference Problem , 1999 .

[12] W. Jason Owen,et al. Statistical Data Analysis , 2000, Technometrics.