Model-Based Explanation For Human-in-the-Loop Security - April 2019

PI(s), Co-PI(s), Researchers: David Garlan, Bradley Schmerl (CMU)

HARD PROBLEM(S) ADDRESSED
Human Behavior
Metrics
Resilient Architectures

PUBLICATIONS

None.

PUBLIC ACCOMPLISHMENT HIGHLIGHTS

Advanced persistent threats (APTs) are a particularly troubling threat to software systems. The adversarial nature of the security domain, and APTs in particular, poses unresolved challenges to the design of self-protecting systems, such as defending against multiple types of attackers with different goals and capabilities, and explaining these systems to security personnel. In this interaction, the observability of each side is an important and under-investigated issue in the self-* domain. We investigated a model of APT defense that elevates observability as a first-class concern. We evaluate this model by showing how an informed approach that uses observability improves the defender's utility compared to a uniform random strategy, as well as demonstrate how the approach can enable robust planning through sensitivity analysis, and can inform observability related architectural design decisions for self-protecting systems.

COMMUNITY ENGAGEMENTS (If applicable)

EDUCATIONAL ADVANCES (If applicable)