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Optimization and implementation of industrial control system network intrusion detection by telemetry analysis

机译:遥测分析工业控制系统网络入侵检测的优化与实现

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Industrial control systems (ICS) are related to all aspects of human life and have become the target of many cyber-attackers. Attacks on industrial control systems may not only cause monetary loss, but also damage equipment, the environment and hurt staff, such as the Stuxnet and the cyber attack on the Ukrainian power grid. So the intrusion detection of ICS has a great significance. This paper based on the intrusion detection by telemetry analysis, optimized the system model, captured the communication packets between different nodes in the system, then extracted features for machine learning to achieve malicious traffic detection, and the attack types are further distinguished. Telemetry means that it does not need to enter the industrial control system network, but by capturing data packets remotely to achieve intrusion detection.
机译:工业控制系统(ICS)与人类生活的各个方面相关,并已成为许多网络攻击者的目标。对工业控制系统的攻击不仅可能造成金钱损失,还会损坏设备,环境并伤害员工,例如Stuxnet和乌克兰电网的网络攻击。因此,ICS的入侵检测具有重要的意义。本文基于遥测分析的入侵检测,优化了系统模型,捕获了系统中不同节点之间的通信数据包,然后提取了机器学习特征以实现恶意流量检测,并进一步区分了攻击类型。遥测意味着它不需要进入工业控制系统网络,而是通过远程捕获数据包来实现入侵检测。

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