  This paper presents a formal framework for identifying and filtering SPIT
calls (SPam in Internet Telephony) in an outbound scenario with provable
optimal performance. In so doing, our work is largely different from related
previous work: our goal is to rigorously formalize the problem in terms of
mathematical decision theory, find the optimal solution to the problem, and
derive concrete bounds for its expected loss (number of mistakes the SPIT
filter will make in the worst case).
  This goal is achieved by considering an abstracted scenario amenable to
theoretical analysis, namely SPIT detection in an outbound scenario with pure
sources. Our methodology is to first define the cost of making an error (false
positive and false negative), apply Wald's sequential probability ratio test to
the individual sources, and then determine analytically error probabilities
such that the resulting expected loss is minimized.
  The benefits of our approach are: (1) the method is optimal (in a sense
defined in the paper); (2) the method does not rely on manual tuning and
tweaking of parameters but is completely self-contained and mathematically
justified; (3) the method is computationally simple and scalable. These are
desirable features that would make our method a component of choice in larger,
autonomic frameworks.
