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  • 标题:Anomaly Extraction in Networks
  • 本地全文:下载
  • 作者:Mr. Naushad Mujawar ; Mr. Sohan Patil ; Mr. Amit Kanase
  • 期刊名称:International Journal of Computer Trends and Technology
  • 电子版ISSN:2231-2803
  • 出版年度:2014
  • 卷号:9
  • 期号:6
  • 页码:327-330
  • DOI:10.14445/22312803/IJCTT-V9P160
  • 出版社:Seventh Sense Research Group
  • 摘要:The application detects anomaly in network using techniques like histogram, cloning voting, filtering. To extract anomalous flows, one could build a model describing normal flow characteristics and use the model to identify deviating flows. We can compare flows of packets on network with previous flows, like new flows that were not previously observed or flows with significant increase/decrease in their volume. Identify an anomalous flow that combines and consolidates information from multiple histogrambased anomaly detectors [1] [4] [8]. Compared to other possible approaches. Build a histogram based detector that (i) applies histogram cloning[1][4], i.e., maintains multiple randomized histograms to obtain additional views of network traffic[3]; and (ii) uses the KullbackLeibler (KL) distance to detect anomalies.
  • 关键词:Anomaly extraction; Apriori Algorithm; Association rules; Flow pre-filtering; Histogram cloning [1]; voting.
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