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We present a honeynet-based collaborative defense framework and an improved highly predictive blacklisting algorithm is developed to generate highly personalized and predictive blacklists for individual networks by correlating historic attackers captured by honeynet deployed in each network. In this way, different networks can defend new attackers in a collaborative way because one network will notify...
IPv6 embraces various good features from the security perspective, but the improvements also bring us some new challenges for web content filtering. This paper presents a new framework of web content filtering in IPv6, which is helpful to purifying network environment. In this framework, using EM (Expectation maximization) algorithm, the active drift and self-learning mechanisms are proposed. Based...
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 Internet environment, software needs to be tested sufficiently before it is considered dependable. The operational profile based testing is an efficient way for both the reliability testing and the security testing. In practice, the two kinds of testing are often carried out separately to validate the dependability of the software, but it is resources consuming to develop the operational profile...
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