A Real-Time Network Traffic Anomaly Detection Scheme Using NetFlow Data

Autor: Koohong Kang, Kiyoung Kim, Jong Soo Jang
Rok vydání: 2005
Předmět:
Zdroj: The KIPS Transactions:PartC. :19-28
ISSN: 1598-2858
DOI: 10.3745/kipstc.2005.12c.1.019
Popis: Recently, it has been sharply increased the interests to detect the network traffic anomalies to help protect the computer network from unknown attacks. In this paper, we propose a new anomaly detection scheme using the simple linear regression analysis for the exported LetFlow data, such as bits per second and flows per second, from a border router at a campus network. In order to verify the proposed scheme, we apply it to a real campus network and compare the results with the Holt-Winters seasonal algorithm. In particular, we integrate it into the RRDtooi for detecting the anomalies in real time.
Databáze: OpenAIRE