Views for Multilevel Database Security
IEEE Transactions on Software Engineering - Special issue on computer security and privacy
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Probabilistic knowledge and probabilistic common knowledge
Methodologies for intelligent systems, 5
Knowledge, probability, and adversaries
Journal of the ACM (JACM)
Reasoning about knowledge
Security of Statistical Databases - Compromise through Attribute Correlational Modeling
Proceedings of the Second International Conference on Data Engineering
A Logical Model for Privacy Protection
ISC '01 Proceedings of the 4th International Conference on Information Security
Quantifying Privacy Leakage through Answering Database Queries
ISC '02 Proceedings of the 5th International Conference on Information Security
An epistemic framework for privacy protection in database linking
Data & Knowledge Engineering
Granulation as a privacy protection mechanism
Transactions on rough sets VII
Medical privacy protection based on granular computing
Artificial Intelligence in Medicine
Measuring the privacy of user profiles in personalized information systems
Future Generation Computer Systems
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We propose two models to quantitatively measure the degree of privacy invasion based on the granular computing methodology. The total cost model measures the privacy invasion in light of the effort needed for an investigator to find individual's private information. The average benefit model measures the privacy invasion in light of the benefit an investigator gets when his investigation improves the assessment of individuals private information. These two models can remedy the inadequacy of the deterministic formulation of privacy proposed in [4]. These two measurements have been implemented in CellSecu 2.0, and a more relaxed generalization procedure, called external generalization, has also been implemented.