# Anomaly Detection of CAN Bus Messages Using a Deep Neural Network for Autonomous Vehicles
## 1 Introduction  
With the development of automotive electronic technology, lots of advanced electronic components are installed on intelligent vehicles, which leads to more complex information shuttling on the vehicle bus. On the other hand, intelligent vehicles are developing toward the direction of unmanned and networked. How to guarantee the security of information flowing among many components will be one of the focuses of intelligent vehicles in the future. The in-vehicle controller area network (CAN) bus is a standardized serial communication protocol widely used in automobile internal control systems [1]. Because of its good reliability, real-time performance and easy wiring, it has been favored by major automobile manufacturers. The CAN bus collects branch data flow from various core control systems of automobiles, such as the engine, transmission system, body system and other electrical equipment, as shown in Figure 1. All branch data are transmitted to the CAN bus in the form of broadcasting, and any node can send messages to the network at any time. This also indicates that any node in the vehicle CAN network may be attacked by malicious internal or external information at any time [2]. Nowadays, automobiles are equipped with a large number of electronic devices. In addition to basic electronic control and media systems, there are intelligent, advanced driving aids, such as automaticstart-stop, parking, Accessory system, and information entertainment systems that can be connected with smart devices such as mobile phones. These systems will obtain data from the CAN bus network on the vehicle. From the perspective of intelligent development, it is inevitable for automobiles to connect to the Internet, and these electronic devices and intelligent information systems may become a way for hackers to intrude into the automobile network system. Once hackers invade these systems and successfully connect to the car CAN bus network, the driver may lose control of the vehicle [3]. At the Black Hat conference in 2014, researchers released a report on the network security of more than 20 models on the market, assessing the ability of different car manufacturers to withstand malicious attacks on different models [4]. In addition, the (Identity Document) ID in the CAN bus protocol only represents the priority of the message, and there is no original address information in the protocol. The receiving electronic control unit (ECU) cannot confirm whether the received data is the original data or not; that is, the authenticity of the received message cannot be confirmed under the existing mechanism, which easily leads to forgery and tampering of the CAN bus message by injecting false information. What makes this worse is that the priority-based arbitration mechanism in the CAN bus protocol makes it possible for hackers to carry out denial of service attacks on bus messages. An attacker can replay or flood the vehicle bus by means of sniffing or listening, which could cause the ECU to fail to send and receive messages normally. Imagine the serious consequences of an intelligent vehicle full of passengers driving automatically when the steering control node is maliciously attacked. For another example, a malicious attacker will set an attack in a target frame of the CAN bus, which will cause the driver to lose control of the throttle position and thus prevent the car from moving. Although these will not necessarily be dangerous, a money-oriented attacker will take advantage of the loopholes in the car's entertainment system to stop the car and display messages on the entertainment system screen. The owner will have to pay a ransom in order to regain control of the car. Therefore, the establishment of a real-time vehicle information security detection system is very important for intelligent vehicles [5; 6; 7]. Figure 1: Controller area network (CAN) bus in an intelligent vehicle. Date information from control electronic units is collected on the CAN bus through CAN nodes.