Architecture-based Self-securing Systems

Abstract

An important emerging trend in the engineering of complex software-based systems is the ability to incorporate self-adaptive capabilities. Such systems typically include a set of monitoring mechanisms that allow a control layer to observe the running behavior of a target system and its environment, and then repair the system when problems are detected. Substantial results in applying these concepts have emerged over the past decade, addressing quality dimensions such as reliability, performance, and database optimization. In particular, at Carnegie Mellon we have shown how architectural models, updated at runtime, can form the basis for effective and scalable problem detection and correction. However, to-date relatively little research has been done to apply these techniques to support detection of security-related problems and identification of remedial actions. In this project we propose to develop scientific foundations, as well as practical tools and techniques, to support self-securing systems, focusing specifically on questions of scalable assurance.