Today’s vehicles are complex distributed embedded systems that are increasingly being connected to various external systems. Unfortunately, this increased connectivity makes the vehicles vulnerable to security attacks that can be catastrophic. In this article, we present a novel intrusion detection system (IDS) called INDRA that utilizes a gated recurrent unit (GRU)-based recurrent autoencoder to detect anomalies in controller area network (CAN) bus-based automotive embedded systems. We evaluate our proposed framework under different attack scenarios and also compare it with the best known prior works in this area.

中文翻译：

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INDRA：在汽车嵌入式系统中使用循环自动编码器进行入侵检测

今天的车辆是复杂的分布式嵌入式系统，越来越多地连接到各种外部系统。不幸的是，这种增加的连接性使车辆容易受到可能是灾难性的安全攻击。在本文中，我们提出了一种称为 INDRA 的新型入侵检测系统 (IDS)，它利用基于门控循环单元 (GRU) 的循环自动编码器来检测基于控制器局域网 (CAN) 总线的汽车嵌入式系统中的异常。我们在不同的攻击场景下评估我们提出的框架，并将其与该领域最著名的先前工作进行比较。