VoIP Anomaly Detection - selected methods of statistical analysis

Paweł Dymora, Miroslaw Mazurek, Sławomir Jaskółka

Abstract


Self-similarity analysis and anomaly detection in networks are interesting fields of research and scientific work of scientists around the world. Simulation studies have demonstrated that the Hurst parameter estimation can be used to detect traffic anomaly. The actual network traffic is self-similar or long-range dependent. The dramatic expansion of applications on modern networks gives rise to a fundamental challenge to network security. The Hurst values are compared with confidence intervals of normal values to detect anomaly in VoIP.


Keywords


Hurst factor, anomaly detection, self-similarity, long-range dependence

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References


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DOI: http://dx.doi.org/10.17951/ai.2016.16.2.14
Date of publication: 2017-12-22 09:38:05
Date of submission: 2017-12-18 14:07:25


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Copyright (c) 2017 Paweł Dymora, Miroslaw Mazurek, Sławomir Jaskółka

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