Executive Summary
This paper proposes a computationally tractable heuristic value function for defending computer networks against Advanced Persistent Threats (APTs) using Boolean Dynamical Systems. It addresses the intractability of optimal control solutions for large networks by leveraging mean-field analysis and entropy maximization. Numerical evaluations demonstrate the heuristic's effectiveness, especially when entropy assumptions are met, providing a practical tool for network defenders.
Why It Matters
This document is crucial for defense intelligence analysts as it provides a computationally tractable method for network defense against APTs, directly impacting national security and military cyber resilience.
Key Takeaways
- Boolean Dynamical Systems (BDS) offer a theoretical framework to model and defend against Advanced Persistent Threats (APTs) in computer networks.
Source evidence · PDF page 1
Recently, the theory of Boolean Dynamical Systems was proposed to study the decision theory surrounding the defense of computer networks against Advanced Persistent Threats (APTs). Boolean Dynamical Systems naturally capture four first principle primitives of APTs: the stealthy nature of attacks, limited and noisy information from automated systems like intrusion detection systems, lateral movement after the attacker penetrates into the network, and the defender’s ability to secure a subset of computers at any time at the loss of resources such as system uptime.
- The paper introduces a computationally tractable heuristic value function to overcome the exponential complexity of optimal control solutions for large networks.
Source evidence · PDF page 2
The core issue that this paper seeks to address is that the emergent value function in this problem domain is defined via (exponentially) large matrix operations that are computationally intractable, rendering existing optimal solutions unusable in practical settings. In this work, we provide a computationally tractable heuristic value function that enables future work to assess the best approach for optimal control in this problem domain.
- The proposed heuristic performs well when entropy assumptions are met, offering a practical approach for network defenders to evaluate control sequences.
Source evidence · PDF page 8
Numerically, we showed that our heuristic performs very well when the entropy assumptions it is based on are true. However, it does see some performance degradation as those assumptions are violated. For future work, we would like to investigate heuristic and tractable control approaches that take advantage of the heuristic value function posed in this work.
Strategic Relevance
The research provides a method for improving the defense of critical military and government networks against sophisticated cyber threats, enhancing operational resilience and reducing the impact of state-sponsored attacks.