The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume

The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume

One of the major threats to cyber security is distributed denial of service (DDoS) attacks. In this paper, we propose a new algorithm based on the persistent increment tendency of DDoS traffic. Our scheme can detect a DDoS attack in its early stages when the attacking packet's attribute value h...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Ying Huang, Xiangsheng Fu, Qiang Hou, Zifan Yu
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Computer crime
Computer security
Conference management
Data mining
DDoS
Early Detection
Geology
Intrusion detection
Persistent Increment
Remote sensing
Statistics
Telecommunication traffic
Traffic control
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Beschreibung
Zusammenfassung:One of the major threats to cyber security is distributed denial of service (DDoS) attacks. In this paper, we propose a new algorithm based on the persistent increment tendency of DDoS traffic. Our scheme can detect a DDoS attack in its early stages when the attacking packet's attribute value has no distinct features. It can differentiate DDoS from flash crowd traffic. This scheme detects DDoS attacks with on-line and distributed characteristics. Simulation shows the algorithm's validity and accuracy.
DOI:10.1109/WAINA.2008.160