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
International audienceThe goals of the present contribution are twofold. First, we propose the use o...
The main requirement for modern systems of intrusion detection is the possibility of identifying dev...
Network traffic anomalies stand for a large fraction of the Internet traffic andcompromise the perfo...
In this paper we present methodological advances in anomaly detection, which, among other purposes, ...
The optimal computer network performance models require accurate traffic models, which can capture t...
We present a new method to estimate the Hurst pa-rameter of the increment process in network traffic...
In this paper we present methodological advances in anomaly detection, which, among other purposes, ...
Internet utilisation has steadily increased, predominantly due to the rapid recent development of in...
Abstract—We study the parameters (knobs) of distribution-based anomaly detection methods, and how th...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic self-similar...
We present a new method to estimate the Hurst parameter of the increment process in network traffic ...
This work proposes a detection scheme that identifies non-conforming behavior in a VoIP network, bas...
This paper presents results of the Hurst parameter for digital signature of network segments. It's a...
We present a new method to estimate the Hurst parameter. The method exploits the form of the autocor...
The hypothesis for the existence of a process with long term memory structure, that represents the i...
International audienceThe goals of the present contribution are twofold. First, we propose the use o...
The main requirement for modern systems of intrusion detection is the possibility of identifying dev...
Network traffic anomalies stand for a large fraction of the Internet traffic andcompromise the perfo...
In this paper we present methodological advances in anomaly detection, which, among other purposes, ...
The optimal computer network performance models require accurate traffic models, which can capture t...
We present a new method to estimate the Hurst pa-rameter of the increment process in network traffic...
In this paper we present methodological advances in anomaly detection, which, among other purposes, ...
Internet utilisation has steadily increased, predominantly due to the rapid recent development of in...
Abstract—We study the parameters (knobs) of distribution-based anomaly detection methods, and how th...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic self-similar...
We present a new method to estimate the Hurst parameter of the increment process in network traffic ...
This work proposes a detection scheme that identifies non-conforming behavior in a VoIP network, bas...
This paper presents results of the Hurst parameter for digital signature of network segments. It's a...
We present a new method to estimate the Hurst parameter. The method exploits the form of the autocor...
The hypothesis for the existence of a process with long term memory structure, that represents the i...
International audienceThe goals of the present contribution are twofold. First, we propose the use o...
The main requirement for modern systems of intrusion detection is the possibility of identifying dev...
Network traffic anomalies stand for a large fraction of the Internet traffic andcompromise the perfo...