Secure databases: protection against user influence
ACM Transactions on Database Systems (TODS)
The tracker: a threat to statistical database security
ACM Transactions on Database Systems (TODS)
Linear queries in statistical databases
ACM Transactions on Database Systems (TODS)
A fast procedure for finding a tracker in a statistical database
ACM Transactions on Database Systems (TODS)
Security in statistical databases for queries with small counts
ACM Transactions on Database Systems (TODS)
A model of statistical database their security
ACM Transactions on Database Systems (TODS)
Secure statistical databases with random sample queries
ACM Transactions on Database Systems (TODS)
A security machanism for statistical database
ACM Transactions on Database Systems (TODS)
ACM Computing Surveys (CSUR)
A study on the protection of statistical data bases
SIGMOD '77 Proceedings of the 1977 ACM SIGMOD international conference on Management of data
Even Data Bases That Lie Can Be Compromised
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
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A database that provides statistical summaries for the purpose of research, planning, and decision making must remain rich, functionally useful, and protected from fraudulent usage. Unless restrictions are placed on the types of queries and responses, protecting an individual's information in the database is impossible. Some effective inference control mechanisms that make it extremely hard for any user to control and compromise a database are discussed. For each method it is argued why the method is effective, supported by some test results.