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您的检索式：作者名="LIU Sunjun"
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| 1 | Multi-Agent Network Intrusion Active Defense Model Based on Immune Theory显示文摘Inspired by the immune theory and multi-agent sys- tems, an immune multi-agent active defense model for network intrusion is established. The concept of immune agent is intro- duced, and its running mechanism is established. The method, which uses antibody concentration to quantitatively describe the degree of intrusion danger, is presented. This model implements the multi-layer and distributed active defense mechanism for net- work intrusion. The experiment results show that this model is a good solution to the network security defense. | LIU Sunjun LI Tao WANG Diangang HU Xiaoqing XU Chun | 2007 | Wuhan University Journal of Natural Sciences2007，12，1： | 2 |
| 2 | Anomaly Detection with Artificial Immune Network显示文摘Inspired by the immune network theory,an adaptive anomaly detection paradigm based on artificial immune network,referred as APAI,is proposed. The implementation of the para-digm includes:initially,the first is to create the initial antibody network;then,through the learning of each training antigen,the antibody network is evolved and updated by the optimal antibod-ies. Finally,anomaly detection process is accomplished by major-ity vote of the k nearest neighbor antibodies in the network. The experiments used the famous Sonar Benchmark dataset in our study,which is taken from the UCI machine learning database. The obtained detection accuracy of APAI was 97.7%,which was very promising with regard to the other classification applications in the literature for this problem. In addition to its nonlinear classi-fication properties,APAI possesses biological immune network properties such as clonal selection,immune network,and immune memory,which can be applied to pattern recognition,classifica-tion,and etc. | PENG Lingxi LI Tao LIU Xiaojie CHEN Yuefeng LIU Caiming LIU Sunjun | 2007 | Wuhan University Journal of Natural Sciences2007，12，5： | 0 |
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