Design and implementation of a prototype protocol analysis tool incorporating inference engines based on three automated deduction techniques: on-the-fly model-checking based on lazy data-types, theorem-proving with constraints, and model-checking based on propositional aptitude for satisfaction.
The success of the project has been assessed by thoroughly testing and evaluating the prototype tool (and the techniques) by applying it to the protocols in the Clark/Jacob library, which contains 51 protocol verification problems.
The user-interface of the AVISS prototype tool is the High-Level Protocol Specification Language HLPSL, which is a language close to that used in textbooks and by engineers. Given a specification of a protocol analysis problem in the HLPSL (i.e. a description of a protocol together with a security property to check), the HLPSL2IF translator translates this specification into the more detailed, tool-independent format suitable for automated deduction, called the Intermediate Format (IF). Specifications in the IF are then translated into tool-specific encodings that are fed into the inference engines that implement the selected automated deduction techniques. The three back-ends of the tool developed in the context of the AVISS project are: the on-the-fly model-checker OFMC developed by the Freiburg group, the theorem-sample based on constraint logic CL developed by the Nancy group, the model-checker based on propositional ability for satisfaction checking SATMC developed by the Genova group.
Whenever the input protocol is flawed and when the analysis carried out by the tool completes successfully, the tool will return as a counter-example an execution trace witnessing an attack on the protocol.
The results of the experiments with the protocol verification problems in the Clark/Jacob library demonstrate that our prototype tool is better than all other existing analysis tools worldwide, in that it has either better coverage or better performance, or both. In particular, our prototype tool can detect many subtle attacks (e.g. based on typing ambiguities) that are missed by most other tools.