论文标题
Indra：使用复发自动编码器在汽车嵌入式系统中使用的入侵检测
INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems
论文作者
论文摘要
当今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，这种增加的连通性使车辆容易受到可能是灾难性攻击的攻击。在这项工作中，我们提出了一种名为Indra的新型入侵检测系统（IDS），该系统利用基于封闭的复发单元（GRU）的复发自动编码器来检测控制器区域网络（CAN）基于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作品进行比较。
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 work, 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.
