Randy Browne
ABSTRACT
Covert channel analysis typically involves study of individual covert channels in isolation, and determining the thoroughness of such case-by-case analysis can be difficult. To help address this problem, this paper formally defines the notion of a “complete” set of covert channels. Informally, a set of covert channels is “complete” when those channels in the set can operate in tandem to produce the maximum possible covert information flow out of a system. More formally, a “complete” set of covert channels is defined as a solution to an equation called the Maximum Information Flow Equation. An alternate way of expressing “completeness” for sets of covert channels is that all “complete” convert channel sets, and only “complete” sets, always satisfy a certain Entropy Conservation Law, which is given in different forms. One form of the Entropy Conservation Law is that any “complete” set of covert channels can be used to represent overall system behavior in what the author calls Covert Channel Normal Form. Although this paper is mainly theoretical in nature, the author also discusses some possible ways of using the theory, along with open issues.
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Index Terms
- An entropy conservation law for testing the completeness of covert channel analysis
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