Hierarchy-Based Access Control in Distributed Environments

Access control is a fundamental concern in any system that manages resources, e.g., operating systems, file systems, databases and communications systems. The problem we address is how to specify, enforce, and implement access control in distributed environments. This problem occurs in many applications such as management of distributed project resources, e-newspaper and payTV subscription services. Starting from an access relation between users and resources, we derive a user hierarchy, a resource hierarchy, and a unified hierarchy. The unified hierarchy is then used to specify the access relation in a way that is compact and that allows efficient queries. It is also used in cryptographic schemes that enforce the access relation. We introduce three specific cryptography based hierarchical schemes, which can effectively enforce and implement access control and are designed for distributed environments because they do not need the presence of a central authority (except perhaps for set- UP).

JVM-based Techniques for Improving Java Observability

Observability measures the support of computer systems to accurately capture, analyze, and present (collectively observe) the internal information about the systems. Observability frameworks play important roles for program understanding, troubleshooting, performance diagnosis, and optimizations. However, traditional solutions are either expensive or coarse-grained, consequently compromising their utility in accommodating today’s increasingly complex software systems. New solutions are emerging for VM-based languages due to the full control language VMs have over program executions. Existing such solutions, nonetheless, still lack flexibility, have high overhead, or provide limited context information for developing powerful dynamic analyses. In this thesis, we present a VM-based infrastructure, called marker tracing framework (MTF), to address the deficiencies in the existing solutions for providing better observability for VM-based languages. MTF serves as a solid foundation for implementing fine-grained low-overhead program instrumentation. Specifically, MTF allows analysis clients to: 1) define custom events with rich semantics ; 2) specify precisely the program locations where the events should trigger; and 3) adaptively enable/disable the instrumentation at runtime. In addition, MTF-based analysis clients are more powerful by having access to all information available to the VM. To demonstrate the utility and effectiveness of MTF, we present two analysis clients: 1) dynamic typestate analysis with adaptive online program analysis (AOPA); and 2) selective probabilistic calling context analysis (SPCC). In addition, we evaluate the runtime performance of MTF and the typestate client with the DaCapo benchmarks. The results show that: 1) MTF has acceptable runtime overhead when tracing moderate numbers of marker events; and 2) AOPA is highly effective in reducing the event frequency for the dynamic typestate analysis; and 3) language VMs can be exploited to offer greater observability.