The Vision of Autonomic Computing
Computer
AModified O(n) Leader Election Algorithm for Complete Networks
PDP '07 Proceedings of the 15th Euromicro International Conference on Parallel, Distributed and Network-Based Processing
Risk and Vulnerability Assessment of Secure Autonomic Communication Networks
AUSWIRELESS '07 Proceedings of the The 2nd International Conference on Wireless Broadband and Ultra Wideband Communications
Elections in a Distributed Computing System
IEEE Transactions on Computers
Denial of service attack and prevention on SIP VoIP infrastructures using DNS flooding
Proceedings of the 1st international conference on Principles, systems and applications of IP telecommunications
Network patterns in cfengine and scalable data aggregation
LISA'07 Proceedings of the 21st conference on Large Installation System Administration Conference
Dynamic dependencies and performance improvement
LISA'08 Proceedings of the 22nd conference on Large installation system administration conference
OVM: an ontology for vulnerability management
Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies
Improving IT Change Management Processes with Automated Risk Assessment
DSOM '09 Proceedings of the 20th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Integrated Management of Systems, Services, Processes and People in IT
Supporting vulnerability awareness in autonomic networks and systems with OVAL
Proceedings of the 7th International Conference on Network and Services Management
Change Priority Determination in IT Service Management Based on Risk Exposure
IEEE Transactions on Network and Service Management
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Autonomic computing has become an important paradigm for dealing with large scale network management. However, changes operated by administrators and self-governed entities may generate vulnerable configurations increasing the exposure to security attacks. In this paper, we propose a novel approach for supporting collaborative treatments in order to remediate known security vulnerabilities in autonomic networks and systems. We put forward a mathematical formulation of vulnerability treatments as well as an XCCDF-based language for specifying them in a machine-readable manner. We describe a collaborative framework for performing these treatments taking advantage of optimized algorithms, and evaluate its performance in order to show the feasibility of our solution.