I. Intelligent connected vehicles begin to cross boundaries
For example, on January 11, 2021, Baidu announced the formal establishment of a smart car company, entering the automotive industry as a vehicle manufacturer. We now know that its partner is Geely, and this joint venture is named "Jidu Automotive Co., Ltd." According to official information, Baidu will fully empower the automotive company with its existing core technologies, including artificial intelligence, Apollo autonomous driving, Xiaodu in-vehicle technology, and Baidu Maps, to improve the intelligence level of Jidu Automotive.
As domestic internet giants, Alibaba and Tencent have also partnered with several car manufacturers. Let's look at Alibaba first: SAIC Motor, Zhangjiang Hi-Tech Park, and Alibaba Group have jointly created a domestic high-end intelligent pure electric vehicle brand – Zhiji Auto. The Zhiji L7, their first model, has already been delivered, and their first SUV, the Zhiji LS7, is reportedly scheduled to officially launch in the fourth quarter, showing very rapid progress.
For Tencent, its network of partners is even broader, including well-known domestic and international automakers such as BMW, Maserati, Great Wall Motors, Changan Automobile, Geely Automobile, GAC Group, GAC Toyota, SAIC Audi, and SAIC Maxus. In terms of automotive digital intelligent cockpits, Tencent's ecosystem has achieved full integration.
Besides the traditional BAT (Baidu, Alibaba, Tencent) giants, we've also seen companies like Huawei and Xiaomi either collaborating across industries to manufacture cars or directly entering the market themselves. At Xiaomi's autumn product launch event, founder and CEO Lei Jun revealed that Xiaomi's car project is progressing very smoothly and has exceeded previous expectations. The company has assembled a technical team of over 500 people across multiple fields, including sensors, chips, simulation technology, high-precision maps, perception and control algorithms, toolchains, high-precision positioning, and training capabilities.
Therefore, in the "second revolution" of intelligent connectivity, the deep integration of Internet companies and traditional car companies, as well as the cross-border car manufacturing by traditional Internet companies and technology companies, will be an important chapter.
II. Network Attack Entry Points for Intelligent Connected Vehicles
In this section, we will mainly learn about the common entry points for cyberattacks on intelligent connected vehicles.
(1) Global Positioning System (GPS): GPS is a satellite-based navigation system. When a GPS receiver detects signals from three or more satellites, it can calculate its position. Since finding a route between two locations is a prerequisite for autonomous driving, GPS signals are crucial for self-driving cars. However, because GPS signals do not contain any data that can directly verify the source of the signal, GPS receivers are easily susceptible to interference and spoofing attacks.
(2) Cameras/Image Sensors: Autonomous and semi-autonomous vehicles rely on cameras placed in numerous locations to obtain a 360-degree field of view. Cameras provide information for important autonomous driving tasks, such as traffic sign recognition and lane detection. Cameras can also be used to replace LiDAR to perform object detection and distance measurement tasks at a lower cost, but they perform poorly in specific conditions such as rain, fog, or snow. Therefore, cameras, in conjunction with LiDAR and millimeter-wave radar, can provide richer and more diverse data for autonomous driving.
(3) V2X Communication (Vehicle to Everything, V2X): V2X communication can be divided into vehicle-to-vehicle (V2V) networks and vehicle-to-infrastructure (V2I) networks. V2V communication facilitates the exchange of data between nearby vehicles and can quickly provide additional information to the data about the surrounding environment already collected by ICVs. V2I communication facilitates the exchange of data between ICVs and road infrastructure, which provides data about the transportation system.
