一种关键字表达式的匹配优化方法
发布时间：2018-10-12 18:36
【摘要】：随着网络安全应用需求的增加,内容检测系统中特征模式集规模不断增长,模式间的冗余重复越来越多。大量模式间的冗余重复直接影响了系统的资源使用率和检测性能。本文首先对表达式的包含关系做了分类,提出了表达式冗余消除算法,然后在BitCount算法的基础上提出了一种时间复杂度为O(1)的掩码验证算法MaskVeri。实验结果表明,改进后的算法性能更高。
[Abstract]:With the increasing demands of network security applications, the scale of feature pattern sets in content detection systems is increasing, and the redundant duplication between patterns is increasing. A large number of redundant patterns directly affect the system's resource utilization and detection performance. In this paper, the inclusion relation of expressions is classified, and an expression redundancy elimination algorithm is proposed. Then, a mask verification algorithm MaskVeri. with time complexity O (1) is proposed based on BitCount algorithm. Experimental results show that the improved algorithm has better performance.
【作者单位】： 哈尔滨工业大学计算机科学与技术学院计算机网络与信息安全技术研究中心;
【基金】：国家重点基础研究发展规划(“973”计划)基金资助项目(No.2011CB302605) 国家自然科学基金资助项目(No.61173145)
【分类号】：TP393.08
，
本文编号：2267180
[Abstract]:With the increasing demands of network security applications, the scale of feature pattern sets in content detection systems is increasing, and the redundant duplication between patterns is increasing. A large number of redundant patterns directly affect the system's resource utilization and detection performance. In this paper, the inclusion relation of expressions is classified, and an expression redundancy elimination algorithm is proposed. Then, a mask verification algorithm MaskVeri. with time complexity O (1) is proposed based on BitCount algorithm. Experimental results show that the improved algorithm has better performance.
【作者单位】： 哈尔滨工业大学计算机科学与技术学院计算机网络与信息安全技术研究中心;
【基金】：国家重点基础研究发展规划(“973”计划)基金资助项目(No.2011CB302605) 国家自然科学基金资助项目(No.61173145)
【分类号】：TP393.08
，
本文编号：2267180
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