Detecting network performance anomalies with contextual anomaly detection
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Network performance anomalies can be defined as abnormal and significant variations in a network's traffic levels. Being able to detect anomalies is critical for both network operators and end users. However, the accurate detection without raising false alarms can become a challenging task when there is high variance in the traffic. To address this problem, we present in this paper a novel methodology for detecting performance anomalies based on contextual information. The proposed method is compared with the state of the art and is evaluated with high accuracy on both synthetic and real network traffic.
CitationDimopoulos, G., Barlet, P., Dovrolis, C., Leontiadis, I. Detecting network performance anomalies with contextual anomaly detection. A: IEEE International Workshop on Measurements and Networking. "2017 IEEE International Workshop on Measurements and Networking: 2017 proceedings papers". Nàpols: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-6.
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