Detection of known and unknown DDoS attacks using Artificial Neural Networks

Author:

Saied Alan,Overill Richard E.,Radzik Tomasz

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference27 articles.

1. M. Reed Denial of Service attacks and mitigation techniques: Real time implementation with detailed analysis. [Online] SANS Institute InfoSec Reading Room 2011. Available from: 〈http://www.sans.org/reading-room/whitepapers/detection〉.

2. Troj/Flood-IM. Backdoor DDoS Trojan. Detected by Sophas. Available from: 〈https://secure2.sophos.com〉

3. Botnet-based distributed denial of service (DDoS) attacks on web servers: classification and art;Alomari;Int. J. Comput. Appl.,2012

4. Machine Learning;Mitchell,1997

5. Prolexic. Global Leader in DDoS Protection and Mitigation 2003–2014. [Online] Available from: 〈http://www.prolexic.com〉.

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