Mining anomalies using traffic feature distributions
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
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Autonomic network environments are required to be resilient. Resilience is defined as the ability for a network to provide and maintain an acceptable level of service in the face of various challenges to normal operation [1]. Traffic abnormalities are a great challenge and it is vital for any network to be supported by resilient mechanisms in order to detect and mitigate such events. In this document we present our measurement-based resilience architecture and we argue that the correct combination of already proposed theoretical methodologies and mechanisms present in our architecture compose a powerful defence mechanism that satisfies autonomic properties such as self-protection and self-optimization. In addition we refer to our intentions of testing our proposed architecture within the ANA project [2] in order to justify our hypothesis.