采用变量推荐和基于特征过滤的系统日志可视化分析工具

Aki Hayashi, T. Itoh, S. Nakamura
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引用次数: 5

摘要

分析和监视系统日志(如事务日志和访问日志)对于各种目标(包括趋势发现、更新工作确定和恶意行为监视)都很重要。然而,这并不总是一项容易的任务,因为这些日志可能非常庞大,由包含数十个变量的数百万条记录组成,因此发现重要的知识可能非常困难或耗时。本文提出了一个可视化的分析工具,使我们能够有效地观察系统日志。该工具推荐可以显示有趣发现的变量,并提供基于特征的过滤,从可视化结果中选择有意义的项目。本文还介绍了针对非专业用户的实验结果。
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A Visual Analytics Tool for System Logs Adopting Variable Recommendation and Feature-Based Filtering
Analysis and monitoring of system logs such as transaction logs and access logs is important for various objectives including trend discovery, update effort determination, and malicious behavior monitoring. However, it is not always an easy task because these logs may be massive, consisting of millions of records containing tens of variables, and therefore it may be difficult or time-consuming to discover significant knowledge. This paper presents a visual analytics tool which enables us to effectively observe system logs. The tool recommends variables that can reveal interesting discoveries and provides feature-based filtering that selects meaningful items from the visualization results. This paper also presents the result of experiments for non-professional users.
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