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Based on TCP protocol, this paper aims at TCP flows, discusses the effects of multivariate correlation analysis on network traffic, obtains the quantitative relationship between different types of TCP packets in each time unit by correlation coefficient matrix, and finally proposes an anomaly detection and analysis method based on the correlation coefficient matrix. The experimental results show that...
Intrusion detection systems (IDS) and intrusion prevention systems (IPS) are now considered a mainstream security technology. IDS and IPS are designed to identify security breaches. However, one of the most important problems with current IDS and IPS is the lack of the ldquoenvironmental awarenessrdquo (i.e. security policy, network topology and software). This ignorance triggers many false positives...
Individual anomaly-detection methods for monitoring computer network traffic have relatively high error rates. An agent-based trust-modeling system fuses anomaly data and progressively improves classification to achieve acceptable error rates.
With network intrusion and crime means becoming complex and diverse, the traditional packet feature matching cannot detect intrusion behavior completely. So it is urgent to reassemble network stream for analyzing network traffic more deeply. In this paper, we present a real-time and lossless network stream reassembly mechanism. First we detailedly explain the design policies of reassembly mechanism,...
The 3 most important issues for anomaly detection based intrusion detection systems by using data mining methods are: feature selection, data value normalization, and the choice of data mining algorithms. In this paper, we study primarily the feature selection of network traffic and its impact on the detection rates. We use KDD CUP 1999 dataset as the sample for the study. We group the features of...
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