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Clustering Algorithms and Its Application in Log Data Processing

Author: ZhangZhuYu
Tutor: LiuPeiYu
School: Shandong Normal University
Course: Computer Software and Theory
Keywords: Clustering algorithm Journal Data Mining Grid clustering Event correlation
CLC: TP393.092
Type: Master's thesis
Year: 2011
Downloads: 75
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Abstract


With the rapid progress of science and technology, the development and popularity of the cause of China's computer network has been greatly. The network our work, life and learning everywhere, brought us a very convenient and fast. However, the computer network at the same time has brought us convenience, but also caused a variety of computer network security issues. In response to these security issues, a variety of methods and techniques based on log data processing to become the consensus of everyone. Log data for the study of data mining methods - clustering algorithm in log scale compression is a useful application play space. Traditional clustering algorithm can not be directly applied to the field of log data first in-depth study on the clustering algorithm. Explore the definition of a clustering algorithm to generate the course as well as the data type of the clustering algorithm, several branches of traditional clustering algorithm: divide the clustering, hierarchical clustering, density-based clustering, grid-based clustering based the model clustering were doing a general description. Summary and analysis of the the clustering algorithm current problems and areas for improvement. To solve the above problem, combined with the characteristics of the network log and system log, the major work done in this paper include: 1. Proposed a secondary clustering algorithm based on grid network log on multi-protocol network log data partitioning grid grid inside and outside, respectively, for the two clusters, generate clustering of clusters recorded. The algorithm does not require a preset number of cluster k, can decide the number of cluster. The algorithm to handle the actual dynamic data, incremental clustering has clustering data, you can delete, processing new network log. The experiments show that the algorithm on a log scale compression effect, but does not destroy the integrity and reliability of the network log, and does not affect the normal user network access. Design and operating system logs, security logs and application logs an event-based mapping system log clustering algorithm, design a unified clustering algorithm its done processing, unified user operating behavior generalization to describe . The mapping between visits logging events, design and system log clustering algorithm proposed event-based mapping relationship. Reference to the thinking of the events associated experimental summary, to establish a mapping between the logging event. The algorithm makes full use of a priori knowledge of the operating system logs, security logs and application logs to simplify the complexity of clustering algorithm is easy to implement, fast time low complexity clustering event information generated description is accurate, complete, easy to understand and to identify and become the source of the late safety study of high-quality data.

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