L. Binns. Implementation considerations for inference detection: Intended vs. actual classification. In Proceedings of the IFIP WG 11.3 Seventh Annual Working Conference on Database Security, 1993. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Genie: A Database Generator for Testing Inference Detection.. - Hinke, Delugach, Wolf (1995) (Correct)
....deduction. This is called the database inference problem . A number of research groups have been working on the development of techniques and tools to detect whether a database is vulnerable to an inference attack. Researchers at TRW [7, 8] SRI International [16] the U.S. Department of Defense [1, 2] and the University of Alabama in Huntsville (UAH) under its AERIE inference research project [10, 11] have developed tools that can analyze a relational database schema to detect whether it is vulnerable to an inference attack. For example, at the schema level an inference detection tool can ....
Leonard J. Binns. Implementation considerations for inference detection: Intended vs. actual classification. In Proceedings of the IFIP WG 11.3 Seventh Annual Working Conference on Database Security, September 1993.
A Formal Approach to Detecting Security Flaws in.. - Morita, Ishihara.. (1999) (Correct)
....and a term , to find a maximal subset A 0 ae = A such that u cannot infer the value of under S, I , and A 0 . This problem is also solvable in polynomial time in practical cases. Lastly, we mention a variation of this problem. Various models of security flaws have been discussed (e.g. [3], 10] 12] 18] 19] Generally, user s attack is modeled by precise inference or imprecise inference. Precise inference means that a user can infer only the exact value of the result of an unpermitted method. Example 1 shows an example of precise inference. Ref. 18] discusses precise inference ....
L.J. Binns, "Implementation considerations for inference detection: intended vs. actual classification," Database Security, VII(A-47): Status and Prospects, Elsevier Science Publishers, pp.139--156, 1994.
Inference and Aggregation Issues In Secure Database Management.. - ? (Correct)
....data that cause inference violations. Some data may be public knowledge, and therefore, cannot be reclassified. In some cases, certain data must be made public due to legal requirements or national policy. Binns also points out that an upgraded element may open apparently new inference channels [Binns 94b] 4.2.1.2 Appropriate Labeling Integrity Constraints There are two ways of handling an explicit constraint defined over several data fields. One is to leave the constraint UNCLASSIFIED, but to identify the LOW data that, together with the constraint, will allow users to infer information about ....
L. J. Binns. Implementation Considerations for Inference Detection: Intended vs. Actual Classification. In IFIP Transactions A (Computer Science and Technology), A-47:297-306, 1994.
Dynamic Inference Control - Staddon (2003) (Correct)
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L. Binns. Implementation considerations for inference detection: Intended vs. actual classification. In Proceedings of the IFIP WG 11.3 Seventh Annual Working Conference on Database Security, 1993.
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