Abstract
Damage from DDoS attack in increasing day by day and an efficient attack detection algorithm is urgently needed. Many current DDoS algorithms are based on anomaly detections which are ineffective in real environment. Detection DDoS attack can be tackled effectively with pattern classification based on flow of packet and machine learning algorithms. In this paper three such pattern classificationsbased on flow of packet and machine learning based algorithm for detection of DDoS attack are discussed. Implementation of these algorithms gives better accuracy in limited time and memory space; hence it’s one of the highly scalable and effective in detection of DDoS attack.
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More From: Journal of University of Shanghai for Science and Technology
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