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The importance of Border Gateway Protocol (BGP) as the primary inter-Autonomous System (AS) routing protocol that maintains the connectivity of the Internet imposes stringent stability requirements on its route selection process. Accidental and malicious activities such as misconfigurations, failures and worm attacks can induce severe BGP instabilities leading to data loss, extensive delays and loss of connectivity. In this paper the authors propose an online instability detection architecture that can be implemented by individual routers. They use statistical pattern recognition techniques for detecting the instabilities and the algorithm is evaluated using real Internet data for a diverse set of events including misconfiguration, node failures and several worm attacks.
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