基于MapReduce的日志文件分析,用于系统威胁和问题识别

S. Vernekar, A. Buchade
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引用次数: 12

摘要

日志文件是识别系统威胁和系统在任何时间点发生的问题的主要信息来源。可以通过分析日志文件和查找可能的可疑行为的模式来识别系统中的这些威胁和问题。然后,可以向关注管理员提供有关系统中这些安全威胁和问题的适当更改或警告,这些威胁和问题是在分析日志文件后生成的。根据这些修改或警告,管理员可以采取适当的措施。有许多工具或方法可用于此目的,有些是专有的,有些是开放源码的。本文提出了一种新的方法,使用MapReduce算法对日志文件进行分析,提供适当的安全警报或警告。然后可以将该系统的结果与现有工具进行比较。
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MapReduce based log file analysis for system threats and problem identification
Log files are primary source of information for identifying the System threats and problems that occur in the System at any point of time. These threats and problem in the system can be identified by analyzing the log file and finding the patterns for possible suspicious behavior. The concern administrator can then be provided with appropriate alter or warning regarding these security threats and problems in the system, which are generated after the log files are analyzed. Based upon this alters or warnings the administrator can take appropriate actions. Many tools or approaches are available for this purpose, some are proprietary and some are open source. This paper presents a new approach which uses a MapReduce algorithm for the purpose of log file analysis, providing appropriate security alerts or warning. The results of this system can then be compared with the tools available.
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