SIEM系统的用户和实体行为分析:计算机应急响应团队数据集的预处理

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Yasin Görmez, Halil Arslan, Y. Işık, İbrahim Ethem Dadaş
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引用次数: 0

摘要

为了防止来自外部的攻击,已经做了大量的工作,并取得了很大的成功。然而,目前检测内部攻击的研究还不够。用户和实体行为分析(UEBA)是内部攻击检测中最重要的研究之一。在这封信中,回顾了文献中的UEBA研究,并分析了计算机应急响应团队数据集(CERT)。为此,对CERT数据集进行了预处理和特征提取。根据用户和每个用户在指定时间间隔内的活动数量组合了几个日志文件。这些预处理和特征提取步骤的python代码在GitHub平台上开源共享。最后,对未来的分析进行了描述,并对计划设计的UEBA系统进行了说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A User and Entity Behavior Analysis for SIEM Systems: Preprocessing of The Computer Emergency and Response Team Dataset
A lot of work has been done to prevent attacks from external sources and a great deal of success has been achieved. However, studies to detect internal attacks aren’t sufficient today. One of the most important studies for the detection of insider attacks is User and Entity Behavior Analysis (UEBA). In this letter, UEBA studies in the literature were reviewed and The Computer Emergency and Response Team Dataset was analyzed (CERT). For this purpose, preprocessing and feature extraction steps were applied on CERT datasets. Several log files combined with respect to user and for each user the number of activities in the specified time interval were obtained. The python code of these preprocessing and feature extraction steps were shared as open source in GitHub platform. In the final phase, future analysis was described and UEBA system planned to be designed was explained.
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来源期刊
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
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