DKAL is a new expressive high-level authorization language. It has been successfully tried at Microsoft which led to further improvements of the language itself. One improvement is...
Abstract. We develop a new multi-party generalization of Naor-Nissim indirect indexing, making it possible for many participants to simulate a RAM machine with only poly-logarithmi...
Matthew K. Franklin, Mark Gondree, Payman Mohassel
Two neural networks that are trained on their mutual output synchronize to an identical time dependant weight vector. This novel phenomenon can be used for creation of a secure cr...
Our research addresses the efficient transfer of large data across wide-area networks, focusing on applications like remote visualization and real-time collaboration. To attain h...
Our system, based on a multiagent framework called collaborative understanding of distributed knowledge (CUDK), is designed with the overall goal of balancing agents' conceptu...