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Our network infrastructure is exposed to persistent threats of DDoS and many unknown attacks. These threats threaten the availability of ISP's network and services. This paper proposes network-based anomalous traffic detection method and presents an anomalous traffic detection system, its architecture and main function blocks. Every five minutes, traffic information and security events are gathered...
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...
This paper describes a forensic logging system that collects fine-grained evidence from target servers and networks. For the logging system, we developed a TCSEC-B1 level secure operating system and a dedicated network processor that collects network traffic. The logging system is also capable of protecting servers from malicious attacks as well as allowing security managers to obtain forensic evidences...
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...
In this paper, a method combining Bayesian statistical model with function of time slicing is presented, which is used for network anomaly detection. By using Bayesian statistical model with time function, the method is intended to find and determine anomaly in the computer network. Combining the advantages of Bayesian theorem when solving uncertain problems with the function whose network traffic...
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