Visible to the public Architecture-based Self Securing Systems

Project Details

Lead PI


Performance Period

Oct 16, 2019

Ranked 80 out of 102 Group Projects in this group.
340 related hits.

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.


Prof. David Garlan and Dr. Bradley Schmerl have been working in the area of architecture-based self-adaptation for over a decade. They have developed both foundations and tools - specifically, a platform called "Rainbow" - that are considered seminal work in this area of architecture-based adaptation. Ivan Ruchkin is a Ph.D. candidate working under the direction of Prof. Garlan in the area of formal modeling of dynamic changes in systems from an architectural perspective. His work will support assurances that operations that change a system at run-time are sound, and do not violate the properties and rules defined by the architecture.


PI: Prof. David Garlan (Faculty),

Staff: Dr. Bradley Schmerl (Research Faculty)

Students: Ivan Ruchkin (Ph.D. Student), new student to be recruited.