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GENERATING ABNORMAL INDUSTRIAL CONTROL NETWORK TRAFFIC FOR INTRUSION DETECTION SYSTEM TESTING

机译:生成用于入侵检测系统测试的异常工业控制网络流量

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Industrial control systems are widely used across the critical infrastructure sectors. Anomaly-based intrusion detection is an attractive approach for identifying potential attacks that leverage industrial control systems to target critical infrastructure assets. In order to analyze the performance of an anomaly-based intrusion detection system, extensive testing should be performed by considering variations of specific cyber threat scenarios, including victims, attack timing, traffic volume and transmitted contents. However, due to security concerns and the potential impact on operations, it is very difficult, if not impossible, to collect abnormal network traffic from real-world industrial control systems. This chapter addresses the problem by proposing a method for automatically generating a variety of anomalous test traffic based on cyber threat scenarios related to industrial control systems.
机译:工业控制系统已在关键基础设施领域广泛使用。基于异常的入侵检测是一种识别潜在攻击的诱人方法,这些攻击利用工业控制系统来针对关键基础设施资产。为了分析基于异常的入侵检测系统的性能,应通过考虑特定网络威胁场景的变化来进行广泛的测试,包括受害者,攻击时机,流量和传输内容。但是,由于安全问题和对操作的潜在影响,很难(即使不是不可能)从实际工业控制系统中收集异常网络流量。本章通过提出一种基于与工业控制系统有关的网络威胁场景自动生成各种异常测试流量的方法来解决该问题。

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