Reiko Yamagishi, T. Katayama, N. Kawaguchi, Tomohiro Shigemoto
{"title":"HOUND: Log Analysis Support for Threat Hunting by Log Visualization","authors":"Reiko Yamagishi, T. Katayama, N. Kawaguchi, Tomohiro Shigemoto","doi":"10.1109/IIAIAAI55812.2022.00130","DOIUrl":null,"url":null,"abstract":"Threat hunting is a methodology to discover threats that have already penetrated organizations without relying on existing security devices. Threat hunting has been attracting attention because the traditional cyberattack process cannot catch advanced threats. In threat hunting, an operator analyzes multiple types of logs and collects traces of attacks in terms of tactics, techniques, and procedures (TTP). While existing log visualization technology can understand the log overview and discover suspicious points, it does not upport detailed analysis in a tabular format. Therefore, analysts must read each log entry carefully during a detailed analysis. In this paper, we propose a detailed analysis support system for threat hunting using three key ideas: (i) making TTP icons to help translate events, (ii) similarity value visualization, and (iii) relevance visualization between log entries to help an operator decide which entries should be analyzed next. We propose a \" Hunting Operation Utilities for Need Decision \" (HOUND) system that implements the three key ideas.","PeriodicalId":156230,"journal":{"name":"2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAIAAI55812.2022.00130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Threat hunting is a methodology to discover threats that have already penetrated organizations without relying on existing security devices. Threat hunting has been attracting attention because the traditional cyberattack process cannot catch advanced threats. In threat hunting, an operator analyzes multiple types of logs and collects traces of attacks in terms of tactics, techniques, and procedures (TTP). While existing log visualization technology can understand the log overview and discover suspicious points, it does not upport detailed analysis in a tabular format. Therefore, analysts must read each log entry carefully during a detailed analysis. In this paper, we propose a detailed analysis support system for threat hunting using three key ideas: (i) making TTP icons to help translate events, (ii) similarity value visualization, and (iii) relevance visualization between log entries to help an operator decide which entries should be analyzed next. We propose a " Hunting Operation Utilities for Need Decision " (HOUND) system that implements the three key ideas.
威胁搜索是一种无需依赖现有安全设备即可发现已经渗透到组织中的威胁的方法。由于传统的网络攻击过程无法捕捉高级威胁,威胁搜索一直备受关注。在威胁搜索中,操作员分析多种类型的日志,并从TTP (tactics, techniques, and procedures)方面收集攻击痕迹。现有的日志可视化技术虽然可以了解日志概况,发现可疑点,但不支持以表格形式进行详细分析。因此,分析人员在详细分析期间必须仔细阅读每个日志条目。在本文中,我们提出了一个详细的威胁搜索分析支持系统,使用三个关键思想:(i)制作TTP图标来帮助翻译事件,(ii)相似值可视化,以及(iii)日志条目之间的相关性可视化,以帮助操作员决定下一步应该分析哪些条目。我们提出了一个“需求决策的狩猎操作实用程序”(HOUND)系统,该系统实现了这三个关键思想。