Inference-security analysis using resolution theorem-proving
Abstract
Indirect logical inferences can provide a significant security threat to information processing systems, but
they have not been much studied. Classification of data can reduce the threat, but classification decisions are
typically left to the intuitive judgment of experts. Progress has been made on analyzing indirect statistical
inferences that may compromise security of a database system ([3], chapter 6). We describe and implement a
nonnumeric analog of these methods for proving security. Our approach involves analyzing facts and
inference rules assumed to be known to a compromiser, deriving all their possible consequences using
resolution theorem-proving, a technique which we argue is far more appropriate to this problem than rulebased
expert systems or information flow analysis. An important contribution of our work is augmentation of
resolution to handle associated time intervals and probabilities of statements being true. Our augmentation is
simple to use by domain experts untrained in computers, and we believe it will provide the first truly
practical tool for analysis of indirect logical inferences in information systems. We demonstrate capabilities
with an example from military security.
Description
This paper appeared in the Fifth International Conference on Data Engineering, Los Angeles, CA, February
1989, 410-416.
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