Quality of Information Assurance- Assessment, Management and Use

Information Assurance (IA) is of growing concern to the field of distributed systems. However, IA cannot be considered in isolation, as it interacts with Quality of Service (QoS); in the presence of limited resources, the security mechanisms employed for IA (e.g., firewalls, antivirus, encryption) usually adversely affect QoS levels delivered by a system. The system therefore needs to make a tradeoff between IA and QoS. This tradeoff is complicated by the fact that users' relative preferences over QoS/IA aspects change based on the situation, the interests of different users con ict, and tradeoff decisions made at one node in the distributed system typically affect other nodes as well. We address the problem of distributed computation of tradeoffs among various aspects of QoS and IA in a way that maximizes the satisfaction of all stakeholders. Specifically, we want the nodes in the system to make coordinated decisions as to what local actions to take to optimize QoS/IA levels delivered by the system.

Our first contribution is formulating this problem as a Distributed Constraint Optimization Problem (DCOP). This entails quantifying various aspects of the system in order to be able to compare options in the course of optimization, as well as encoding the effects of various decisions on the quantities we want to optimize. The DCOPs we obtain have cost functions with many local configurations that result in the same cost. In addition, the corresponding factor graphs contain many cycles. To deal with these issues, our second contribution is a value propagation phase that helps nodes reach a consistent set of decisions even in cyclic factor graphs with non-unique local minimizers.