Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Toward a tool to detect and eliminate inference problems in the design of multilevel databases
Results of the Sixth Working Conference of IFIP Working Group 11.3 on Database Security on Database security, VI : status and prospects: status and prospects
Query answering via cooperative data inference
Journal of Intelligent Information Systems
Design and implementation of a database inference controller
Data & Knowledge Engineering
CoBase: a scalable and extensible cooperative information system
Journal of Intelligent Information Systems - Special issue on intelligent integration of information
Selectivity estimation using probabilistic models
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Wizard: A Database Inference Analysis and Detection System
IEEE Transactions on Knowledge and Data Engineering
Data Level Inference Detection in Database Systems
CSFW '98 Proceedings of the 11th IEEE workshop on Computer Security Foundations
Learning probabilistic relational models
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Informed recognition in software watermarking
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Privacy preserving via tree augmented naïve Bayesian classifier in multimedia database
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
An information theoretic framework for web inference detection
Proceedings of the 5th ACM workshop on Security and artificial intelligence
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Access control mechanisms are commonly used to provide control over who may access sensitive information. However, malicious users can exploit the correlation among the data and infer sensitive information from a series of seemingly innocuous data access. In this paper, we proposed a detection system that utilizes both the user’s current query and past query log to determine if the current query answer can infer sensitive information. This detection system is being extended to the cases of multiple collaborative users based on the query history of all the users and their collaborative levels for specific sensitive information.