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Abstract
Attack graph can simulate the possible paths used by attackers to invade the network. By using the attack graph, the administrator can evaluate the security of the network and analyze and predict the behavior of the attacker. Although there are many research studies on attack graph, there is no systematic survey for the related analysis methods. This paper firstly introduces the basic concepts, generation methods, and computing tasks of the attack graph, and then, several kinds of analysis methods of attack graph, namely, graph-based method, Bayesian network-based method, Markov model-based method, cost optimization method, and uncertainty analysis method, are described in detail. Finally, comparative study of the methods and future work are provided. We believe that this work would help the research community to understand the attack graph analysis method systematically.
Highlights
Network security breach has become a potential danger that limits the further development of network applications
Bayesian network (BN) is a kind of probabilistic graph network. It is commonly used in the field of uncertainty analysis and reasoning. e Bayesian network uses causal relationships to estimate the probability of an unknown event based on events that have occurred. e attack graph based on the Bayesian network is represented by a triple (Node, Edge, and PTable). e nodes in the attack graph denote the vulnerabilities, privileges, etc. e edges are the dependencies between the nodes
The mobile device connections are usually not kept and difficult to predict, which lead to the great uncertainty on network security. e task of uncertainty analysis based on attack graphs is to analyze the uncertain phenomena mentioned above, evaluate the influence of these uncertain factors, and attempt to conduct quantitative analysis. ese uncertainties can be solved by uncertain attack graphs. e scalable attack graph analyzes the connection probability of mobile devices in the network, evaluating security status of whole network. e zero-day attack graph can deal with the unknown vulnerabilities that may exist in the network
Summary
Network security breach has become a potential danger that limits the further development of network applications. NetSPA (https://dspace.mit.edu/handle/1721.1/29899) is an attack graph generation tool designed by Lippmann et al from MIT It builds a network model by analyzing firewall rules and vulnerability information and performs reachability analysis [10]. Erefore, several important calculation tasks to be done on the attack graph include network vulnerability analysis, node security hardening selection, attack path prediction, and uncertainty analysis. Important steps include the selection of nodes needed to be strengthened, the balance between costs and benefits, and targeted network defense methods All these tasks need rigorous modeling analysis. Probability-based analysis methods include Bayesian networks and Markov models, and the rest are based on logic Among these methods, graph-based algorithms and Markov model-based analysis methods can be used to predict attack behavior and analyze the most likely attack path. Cost-optimized algorithms have a huge advantage in balancing costs and benefits. e analysis method based on the uncertainty is used to study the influence of vulnerabilities, links, attack behaviors, and other factors on network attacks
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