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Online trading invariably involves dealings between strangers, so it isimportant for one party to be able to judge objectively the trustworthiness ofthe other. In such a setting, the decision to trust a user may sensibly bebased on that user's past behaviour. We introduce a specification languagebased on linear temporal logic for expressing a policy for categorising thebehaviour patterns of a user depending on its transaction history. We alsopresent an algorithm for checking whether the transaction history obeys thestated policy. To be useful in a real setting, such a language should allow oneto express realistic policies which may involve parameter quantification andquantitative or statistical patterns. We introduce several extensions of lineartemporal logic to cater for such needs: a restricted form of universal andexistential quantification; arbitrary computable functions and relations in theterm language; and a "counting" quantifier for counting how many times aformula holds in the past. We then show that model checking a transactionhistory against a policy, which we call the history-based transactionmonitoring problem, is PSPACE-complete in the size of the policy formula andthe length of the history. The problem becomes decidable in polynomial timewhen the policies are fixed. We also consider the problem of transactionmonitoring in the case where not all the parameters of actions are observable.We formulate two such "partial observability" monitoring problems, and showtheir decidability under certain restrictions.

A decidable policy language for history-based transaction monitoring