计算机应用 ›› 2017, Vol. 37 ›› Issue (3): 777-781.DOI: 10.11772/j.issn.1001-9081.2017.03.777

• 网络空间安全 • 上一篇    下一篇

运用差分演化算法实现包匹配多层核心基的提取

王则林1,2, 郝水侠3   

  1. 1. 南通大学 杏林学院, 江苏 南通 226000;
    2. 南通大学 计算机科学与技术学院, 江苏 南通 226000;
    3. 江苏师范大学 数学与统计学院, 江苏 徐州 221116
  • 收稿日期:2016-08-11 修回日期:2016-10-24 出版日期:2017-03-10 发布日期:2017-03-22
  • 通讯作者: 郝水侠
  • 作者简介:王则林(1973-),男,江苏南通人,副教授,博士,主要研究方向:网络安全、智能计算;郝水侠(1973-),女,江苏徐州人,副教授,博士,主要研究方向:并行算法、智能算法。
  • 基金资助:
    国家自然科学基金资助项目(61070008);南通市科技局应用研究项目(BK2014057)。

Extracting kernel basis using differential evolution algorithm for packet matching

WANG Zelin1,2, HAO Shuixia3   

  1. 1. Xinglin College, Nantong University, Nantong Jiangsu 226000, China;
    2. School of Computer Science and Technology, Nantong University, Nantong Jiangsu 226000, China;
    3. School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou Jiangsu 221116, China
  • Received:2016-08-11 Revised:2016-10-24 Online:2017-03-10 Published:2017-03-22
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61070008), the Application Research Project of Nantong Science and Technology Bureau (BK2014057).

摘要: 针对网络防火墙、路由器等设备中包匹配的速度问题,提出运用差分演化算法实现包匹配多层核心基的提取。该算法运用多层基础基描述包的多层特征,在每层中分别运用差分演化算法进行比特基和实体基的提取,运用平均自信息和平均互信息量衡量基础基选择的优劣。这种方法可以根据规则库实际规模选择提取比特实体基的层数,非常适应规则库的增长。实验结果表明,所提算法在时间效率、空间效率方面相对于已有的递归数据流匹配算法和基于实数编码的差分演化的包匹配算法,综合性能最优。

关键词: 包匹配, 差分演化算法, 平均自信息, 平均互信息

Abstract: Aiming at the speed of packet matching in network firewall, router and other equipment, a differential evolution algorithm was proposed to extract the multi-layer core base of package matching. The multi-layer foundation was used to describe the multi-layer characteristics of the packet. In each layer, the bit basics and entitative basics were extracted using differential evolution algorithm and average self-information and the average mutual information were used to evaluate the quality of kernel basis. This method was adapt to select the number of layers of the extracted entity base according to the actual size of rule base, which is very suitable for the growth of rule base. The experimental results show that The proposed algorithm is the first known algorithm to be applied to packet matching efficiently. Compared with RFC (Recursive Flow Classification) algorithm and RDEPM (Real-based Differential Evolution Packet Matching) algorithm, the performance of the proposed algorithm is superior in terms of time efficiency and space efficiency.

Key words: packet matching, differential evolution algorithm, average self-information, average mutual information

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