@article {20,
	title = {Network risk management using attacker profiling},
	journal = {Security and Communication Networks},
	volume = {2},
	year = {2009},
	pages = {83{\textendash}96},
	abstract = {<p>Risk management refers to the process of making decisions that minimize the effects of vulnerabilities on the network hosts. This can be a difficult task in the context of high-exploit probability and the difficult to identify new exploits and vulnerabilities. For many years, security engineers have performed risk analysis using economic models for the design and operation of risk-prone, technological systems using attack profiles. Based on the type of attacker identified, security administrators can formulate effective risk management policies for a network. We hypothesize that sequence of network actions by an attacker depends on the social behavior (e.g., skill level, tenacity, financial ability). We extended this and formulated a mechanism to estimate the risk level of critical resources that may be compromised based on attacker behavior. This estimation is accomplished using behavior based attack graphs representing all the possible attack paths to all the critical resources. The risk level is computed based on these graphs and are used as a measure of the vulnerability of the resource and forming an effective basis for a system administrator to perform suitable changes to network configuration. Copyright {\textcopyright} 2008 John Wiley \&amp; Sons, Ltd.</p>
},
	keywords = {attack graphs, behavior, risk management},
	issn = {1939-0122},
	doi = {10.1002/sec.58},
	url = {http://dx.doi.org/10.1002/sec.58},
	author = {Ram Dantu and Kolan, Prakash and Cangussu, Jo{\~a}o}
}
@conference {34,
	title = {Classification of Attributes and Behavior in Risk Management Using Bayesian Networks},
	booktitle = {2007 IEEE International Conference on Intelligence and Security Informatics (ISI) },
	year = {2007},
	month = {05/2007},
	address = {New Brunswick, NJ},
	abstract = {<p>Security administration is an uphill task to implement in an enterprise network providing secured corporate services. With the slew of patches being released by network component vendors, system administrators require a barrage of tools for analyzing the risk due to vulnerabilities in those components. In addition, criticalities in patching some end hosts raises serious security issues about the network to which the end hosts are connected. In this context, it would be imperative to know the risk level of all critical resources keeping in view the everyday emerging new vulnerabilities. We hypothesize that sequence of network actions by attackers depends on their social and attack profile (behavioral resources such as skill level, time, and attitude). To estimate the types of attack behavior, we surveyed individuals for their ability and attack intent. Using the individuals{\textquoteright} responses, we determined their behavioral resources and classified them as having opportunist, hacker, or explorer behavior. The profile behavioral resources can be used for determining risk by an attacker having that profile. Thus, suitable vulnerability analysis and risk management strategies can be formulated to efficiently curtail the risk from different types of attackers.</p>
},
	keywords = {attack behaviour, attack graphs, attack intent, Bayesian network, behavior, belief networks, explorer behavior, hacker behavior, opportunist behavior, profile behavioral resource classification, risk management, Security, security administration, vulnerability analysis},
	doi = {10.1109/ISI.2007.379536},
	author = {Ram Dantu and Kolan, Prakash and Akl, Robert and Loper, Kall}
}
