Benchmarking multilevel secure database systems using the MITRE benchmark

Multilevel secure (MLS) DBMSs are subject to a number of security-related architectural and functional factors that affect performance. These factors include, among others, the distribution of data among security levels, the session levels at which queries are run, and how the database is physically partitioned into files. In this paper, we present a benchmark methodology, a test database design, and a query suite designed to quantify this impact upon query processing. We introduce three metrics (uniformity, scale-up and speed-up) that characterize DBMS performance with varying data distributions. Finally, we provide comparisons and analysis of the results of a number of actual benchmarking experiments using DBMSs representative of the two major MLS DBMS architectures (trusted-subject and TCB-subset)