Hybrid inferential security methods for statistical databases
| Autor: | Steven C. Hansen |
|---|---|
| Rok vydání: | 1995 |
| Předmět: |
Database
Computer science business.industry Computation Control (management) Inference Ocean Engineering Machine learning computer.software_genre Information sensitivity Statistical database Statistical inference Data mining Artificial intelligence Database security business computer Control methods |
| Zdroj: | ACM SIGAPP Applied Computing Review. 3:14-18 |
| ISSN: | 1931-0161 1559-6915 |
| DOI: | 10.1145/214310.214433 |
| Popis: | Memoryless inference control methods have been shown to provide effective means of reducing the amount of sensitive information released from a statistical database while maximizing the release of non-sensitive information. Early memoryless inference controls have the additional benefit of providing control at a low computation and storage cost. Two recent extensions to memoryless inference control allow the controls to release more non-sensitive information but do so at a greater cost in terms of computation and storage. This paper describes a proposed hybrid inference control method that can potentially maximize the release of information while holding down computation costs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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