The standard Kripke semantics of epistemic logics has been applied successfully to reasoning communication protocols under the assumption that the network is not hostile. This paper introduces a natural semantics of Kripke semantics called knowledge structure and, by this kind of Kripke semantics, analyzes communication protocols over hostile networks, especially on authentication protocols. Compared with BAN-like logics, the method is automatically implementable because it operates on the actual definitions of the protocols, not on some difficult-to-establish justifications of them. What is more, the corresponding tool called SPV (Security Protocol Verifier) has been developed. Another salient point of this approach is that it is justification-oriented instead of falsification-oriented, i.e. finding bugs in protocols.
A language model for information retrieval is built by using a query language model to generate queries and a document language model to generate documents. The documents are ranked according to the relative entropies of estimated document language models with respect to the estimated query language model. Two popular and relatively efficient smoothing methods, the Jelinek-Mercer method and the Absolute discounting method, are used to smooth the document language model in estimation of the document language. A combined model composed of the feedback document language model and the collection language model is used to estimate the query model. A performacne comparison between the new retrieval method and the existing method with feedback is made, and the retrieval performances of the proposed method with the two different smoothing techniques are evaluated on three Text Retrieval Conference (TREC) data sets. Experimental results show that the method is effective and performs better than the basic language modeling approach ; moreover, the method using the Jelinek-Mercer technique performs better than that using the Absolute discounting technique, and the perfomance is sensitive to the smoothing paramters.
