• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Inventive Computing and Informatics >Multi Level Statistical Classification of Network Traffic
【24h】

Multi Level Statistical Classification of Network Traffic

机译：网络流量的多级统计分类

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Network Traffic Classification is the crucial phase of network monitoring. The network traffic once categorized per application it can be imposed with appropriate security policies to improve the performance of the network. The port and payload based traffic classification techniques used in the past decade relapsed owing to new techniques of encryption and tunneling emerging day-by-day. Recently, the statistical classification employing data mining techniques and analyzing the attributes for characterization of network traffic proved high efficiency. This proposed work characterized the network traffic based on semi-supervised machine learning approach. It initially clustered the auxiliary and content flow of application to precisely track the footprint of the application using improved k-means clustering which in turn is fed into C5.0 classifier to construct the classifier model. This system is designed to classify the network traffic accurately that resulted in high F-Score value of 0.993.
机译：网络流量分类是网络监控的关键阶段。网络流量一旦每个应用程序分类，可以使用适当的安全策略强制提高网络性能。由于日常的加密和隧道新技术，过去十年中使用的基于端口和有效载荷的流量分类技术复发。最近，采用数据挖掘技术的统计分类和分析了网络流量表征的属性证明了高效率。这项建议的工作表征了基于半监督机器学习方法的网络流量。它最初聚集了应用程序的辅助和内容流程，以精确地跟踪应用程序的占用空间，使用改进的k-means群集，又将其送入C5.0分类器以构造分类器模型。该系统旨在准确地对网络流量进行分类，导致高于0.993的F刻度值。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号