The basic idea for detecting abrupt changes is to continuously conduct short- term predictions and determine the difference between the prediction and the actual measurement. The higher the difference, the more unexpected and hence abrupt the change is.
On Detecting Abrupt Changes in Network Entropy Time Series
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In this paper, we propose an algorithm capable of detecting abrupt changes in network entropy time series. Abrupt changes indicate that the underlying frequency ...
In this paper, we propose an algorithm capable of detecting abrupt changes in network entropy time series. Abrupt changes indicate that the underlying frequency ...
Empirical evidence suggests that abrupt changes are often caused by malicious activity such as (D)DoS, network scans and worm activity, just to name a few.Our ...
In this paper, we propose an algorithm capable of detecting abrupt changes in network entropy time series. Abrupt changes indicate that the underlying frequency ...
Abstract. In recent years, much research focused on entropy as a metric describing the “chaos” inherent to network traffic. In particular, network.
In this paper, we propose an algorithm capable of detecting abrupt changes in network entropy time series. Abrupt changes indicate that the underlying frequency ...
Sep 22, 2014 · It contains several algorithms for change point detection. Each of them returns a score that you can use to characterize the detected changes.
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This paper proposes an entropy-based approach for detecting anomalies in network traffic. With the exponential growth of data and sophisticated cyberattacks ...
Feb 27, 2015 · The idea is to determine entropy of a "normal" time series and then compare it with other time series (this idea has an assumption of an entropy ...