多变量时序安全事件数据的可视化

A. Thomson, Martin Graham, J. Kennedy
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引用次数: 4

摘要

监控网络入侵的日志文件是很麻烦的。为了构建日志的心理模型,分析师需要从基本上仅限于有序事件列表的数据集中识别连续的时间线和攻击模式。信息可视化技术将数据排列成直接可感知的视觉模式,可以减轻与解释这些数据集相关的一些开销,并提高用户(特别是资源紧张的中小型企业(smb))理解入侵检测系统(IDS)事件日志中的活动模式的能力。为此,我们讨论了IDS日志的现有网络安全可视化,在研究了这些应用程序的优缺点之后,我们创建了一个可视化工具的原型,Pianola,它在多个时间线上安排事件,以揭示时间和网络中的模式。该工具与传统使用基于命令行界面(CLI)的工具进行了评估,用于分析网络安全事件,并在识别和检测攻击以及减少用户主观工作量方面显示出显着改善,使用NASA任务负载指数(TLX)进行测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pianola - Visualization of Multivariate Time-Series Security Event Data
Monitoring log files for network intrusions is unwieldy. To build a mental model of the log, an analyst is required to recognise continuous timelines and attack patterns from a dataset that is essentially limited to an ordered list of events. Information Visualization techniques arrange data into directly perceivable visual patterns that may alleviate some overheads associated with interpreting these datasets and improve the ability of users, especially those in resource-stretched Small and Medium sized Businesses (SMBs), to make sense of activity patterns in Intrusion Detection System (IDS) event logs. To this end, we discuss existing network security visualizations for IDS logs and after examining the strengths and drawbacks of those applications we have prototyped a visualization tool, Pianola, that arranges events on multiple timelines to reveal patterns both in time and across a network. The tool was evaluated against the traditional use of command-line interface (CLI)-based tools for analyzing network security events and displayed significant improvements in both recognition and detection of attacks and reduction in the users' subjective workload, measured using the NASA Task Load index (TLX).
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