Using selective, short‐term memory to improve resilience against DDoS exhaustion attacks

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AbstractDistributed denial of service (DDoS) attacks originating from botnets can quickly bring normally effective web services to a screeching halt. This paper presents SESRAA (selective short‐term randomized acceptance algorithms), an adaptive scheme for maintaining web service despite the presence of multifaceted attacks in a noisy environment. In contrast to existing solutions that rely upon ‘clean’ training data, we presume that a live web service environment makes finding such training data difficult if not impossible. SESRAA functions much like a battlefield surgeon's triage: focusing on quickly and efficiently salvaging good connections with the realization that the chaotic nature of the live environment implicitly limits the accuracy of such detections. SESRAA employs an adaptive k‐means clustering approach using short‐term extraction and limited centroid evolution to defend the legitimate connections in a mixed attack environment. We present the SESRAA approach and evaluate its performance through experimental studies in a diverse attack environment. The results show significant improvements against a wide variety of DDoS configurations and input traffic patterns. Copyright © 2008 John Wiley & Sons, Ltd.