Two Scalable Approaches to Analyzing Network Security Using Compact Attack Graphs

The compact attack graphs can implicitly reveal the potential threat of sophisticated multi-step attacks by enumerating possible sequences of exploits leading to the compromising given critical resources in enterprise networks with thousands of hosts. For security analysts, the challenge is how to analyze the complex attack graphs with possible ten thousands of nodes for defending the security of network. In the paper, we will essentially discuss two issues about it. The first is to compute non-loop attack paths with the distance less than the given number that the real attacker may take in realistic attack scenarios. The second is how to measure security risk. Two scalable approaches are proposed to solve the above two issues respectively. These approaches are proved to have a polynomial time complexity and can scale to the attack graphs with ten thousands of nodes corresponding to large enterprise networks.

I. Introduction

In defending a network with critical resources, certain vulnerabilities may seem to be insignificant when considered in isolation. An attacker can often infiltrate a seemingly well-guarded network using multi-step attacks by exploiting sequences of related vulnerabilities. Attack graphs can reveal such potential threats by enumerating all possible sequences of exploits that an attacker can follow to compromise given critical resources. Since the earlier methods can only generating state-based attack graphs for the small target network with the size of ten hosts in [1]–[2], [6][13], the scalability of generation attack graphs is a serious issue until the researchers recently proposed novel approaches to construction compact attack graphs based on monotonicity assumption, i.e., an attacker never relinquishes any obtained capabilities [14]–[17]. The Ou's method even can generate compact attack graphs for the enterprise network with the size of thousands of host in [15].