Classification of Attributes and Behavior in Risk Management Using Bayesian Networks Metadata
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- Main Title Classification of Attributes and Behavior in Risk Management Using Bayesian Networks
Author: Dantu, RamCreator Type: PersonalCreator Info: University of North Texas
Author: Kolan, PrakashCreator Type: PersonalCreator Info: University of North Texas
Author: Loper, KallCreator Type: PersonalCreator Info: University of North Texas
Author: Akl, Robert G.Creator Type: PersonalCreator Info: University of North Texas
Organizer of meeting: Institute of Electrical and Electronics EngineersContributor Type: Organization
- Creation: 2007-03
- Content Description: This paper discusses issues in security.
- Physical Description: 4 p.
- Keyword: attack graphs
- Keyword: behaviors
- Keyword: risk management
- Keyword: belief networks
- Keyword: security
- Conference: Institute of Electrical and Electronics Engineers International Conference on Portable Information Devices, 2007, Orlando, Florida, United States
Name: UNT Scholarly WorksCode: UNTSW
Name: UNT College of EngineeringCode: UNTCOE
- Rights Access: public
- Archival Resource Key: ark:/67531/metadc30836
- Academic Department: Computer Science and Engineering
- Display Note: Abstract: 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. The authors 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, the athors surveyed individuals for their ability and attack intent. Using the individuals' responses, the authors 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.