Modeling Observability in Adaptive Systems to Defend Against Advanced Persistent Threats
Cody Kinneer,
Ryan Wagner, Fei Fang, Claire Le Goues and
David Garlan.
In Proceedings of the 17th ACM-IEEE International Conference on Formal Methods and Models for Systems Design (MEMCODE\'19), San Diego, USA, 9-11 October 2019.
Online links:   Plain Text
Abstract
| Advanced persistent threats (APTs) are a particularly troubling challenge
for software systems. The adversarial nature of the security
domain, and APTs in particular, poses unresolved challenges to
the design of self-* systems, such as how to defend against multiple
types of attackers with different goals and capabilities. In
this interaction, the observability of each side is an important and
under-investigated issue in the self-* domain. We propose 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, can enable robust planning through sensitivity
analysis, and can inform observability-related architectural
design decisions. |
Keywords: Science of Security, Self-adaptation.
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