Traditionally, authentication and authorization (A&A) in computer systems guard only user interfaces, thus providing only a perimeter defense against attacks. We search for an A&A approach that satisfies the requirements of multiple lines of defense and defense in depth. After reviewing and classifying a variety of security paradigms, we propose the paradigm of pervasive trust. It is analogous to a social model of interaction, where trust is constantly --if often unconsciously-- applied. In an initial study performed in our lab, we investigated using trust for the perimeter-defense A&A model, in which the capability to use trust ratings for users was applied for enhancing the role-based access control mechanism.

Speaker: Dr. Leszek Lilien received his Ph.D. in Computer Science from the University of Pittsburgh, Pennsylvania. His research at Purdue University concentrates on trusted computing and computer security.

Data Grids provide geographically distributed resources for large-scale data-intensive applications that generate large data sets. However, ensuring efficient access to such huge and widely distributed data is hindered by the high latencies of the Internet. We address these challenges by employing intelligent replication and caching of objects at strategic locations. In our approach, replication decisions are based on a cost-estimation model and driven by the estimation of the data access gains and the replica's creation and maintenance costs. These costs are in turn based on factors such as runtime accumulated read/write statistics, network latency, bandwidth, and replica size.

To support large numbers of users who continuously change their data and processing needs, we introduce scalable replica distribution topologies that adapt replica placement to meet these needs. In this talk, we present the design of our dynamic memory middleware and replication algorithm as well as its evaluation via a Data Grid simulator, called the GridNet that we developed for this purpose. Simulation results demonstrate that replication improves the data access time in Data Grids, and that the gain increases with the size of the datasets involved.