We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
The standard symbolic, deducibility-based notions of secrecy are in general insufficient from a cryptographic point of view, especially in presence of hash functions. In this paper...
Abstract. We describe a denotational (game) semantics for a call-byvalue functional language with multiple threads of control, which may communicate values of general type on local...
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
With the rapid growth of the Internet and pervasive computing activities, the migration of back-end legacy systems to network centric environments has become a focal point for res...