基于规则的铁路信号网络异常检测
Rule-based Anomaly Detection for Railway Signalling Networks
摘要：
我们提出了一个基于规则的铁路信号异常检测系统，减轻了Dolev-Yao攻击者谁是能够注入控制命令，并执行语义攻击的攻击。该系统还减轻了攻击者用来发出合法但时间错误的控制消息的受损信号盒的影响。我们认为，如果我们的对策不被采用，攻击者可能会导致训练脱轨和碰撞。我们将铁路运营的安全原则应用于分布式异常检测系统，该系统检查信号和点上的传入命令。所提出的异常检测系统检测我们的模型的所有攻击，而不产生误报，而它只需要少量的开销相比，正常的训练操作的网络通信和延迟。
英文摘要：
We propose a rule-based anomaly detection system for railway signalling that mitigates attacks by a Dolev-Yao attacker who is able to inject control commands and to perform semantic attacks. The system as well mitigates the effects of a compromised signal box that an attacker uses to issue licit but mistimed control messages. We consider an attacker that could cause train derailments and collisions, if our countermeasure is not employed. We apply safety principles of railway operation to a distributed anomaly detection system that inspects incoming commands on the signals and points. The proposed anomaly detection system detects all attacks of our model without producing false positives, while it requires only a small amount of overhead in terms of network communication and latency compared to normal train operation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
