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Standardized container virtualization approach for collecting host intrusion detection data

机译:用于收集主机入侵检测数据的标准化容器虚拟化方法

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Anomaly-based Intrusion Detection Systems (IDS) can be instrumental in detecting attacks on IT systems. For evaluation and training of IDS, data sets containing samples of common security-scenarios are essential. Existing data sets are not sufficient for training modern IDS. This work introduces a new methodology for recording data that is useful in the context of intrusion detection. The approach presented is comprised of a system architecture as well as a novel framework for simulating security-related scenarios.
机译:基于异常的入侵检测系统(IDS)有助于检测对IT系统的攻击。对于IDS的评估和培训,包含常见安全场景样本的数据集至关重要。现有数据集不足以训练现代IDS。这项工作介绍了一种用于记录数据的新方法,该方法在入侵检测的上下文中很有用。提出的方法包括一个系统体系结构以及一个用于模拟与安全相关的方案的新颖框架。

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