Cyber threat assessment via attack scenario simulation using an integrated adversary and network modeling approach. (January 2018)

• Record Type: Journal Article
• Authors: Moskal, Stephen; Yang, Shanchieh Jay; Kuhl, Michael E
• Other Names: Kott Alexander guest-editor.
• Is Part Of: Journal of defense modeling and simulation. Volume 15:Number 1(2018:Jan.)
• Page Start: 13
• Page End: 29
• Publication Date: 2018-01
• Subjects: Cyber attack simulation -- adversary behavior modeling -- fuzzy logic; Military art and science -- Computer simulation -- Periodicals; 355.0011305
• DOI: 10.1177/1548512917725408
• Languages: English
• ISSNs: 1548-5129

Abstract

Existing research on cyber threat assessment focuses on analyzing the network vulnerabilities and producing possible attack graphs. Cyber attacks in real-world enterprise networks, however, vary significantly due to not only network and system configurations, but also the attacker's strategies. This work proposes a cyber-based attacker behavior model (ABM) in conjunction with the Cyber Attack Scenario and Network Defense Simulator to model the interaction between the network and the attackers. The ABM leverages a knowledge-based design and factors in the capability, opportunity, intent, preference, and Cyber Attack Kill Chain integration to model various types of attackers. By varying the types of attackers and the network configurations, and simulating their interactions, we present a method to measure the overall network security against cyber attackers under different scenarios. Simulation results based on four attacker types on two network configurations are shown to demonstrate how different attacker behaviors may lead to different ways to penetrate a network, and how a single misconfiguration may impact network security.