# Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges
## 4 Smart Mobility Services and Applications
### Mobility-as-a-Service
#### 4.1.2 Analysis of Security Threats  
Autonomous vehicles use technologies such as Internet of Things, Wireless Sensor Networks, Artificial Intelligence, and Machine Learning, among others, to collect, analyze and share data and eventually make informed decisions. These autonomous vehicles form a part of a larger network comprising thousands of interconnected entities. These types of connected environments consisting of heterogeneous devices are highly dependent on the individual device's security protocols. This makes autonomous vehicles vulnerable to several types of security threats and attacks. These attacks can take place at various levels such as the network level, device level and software level [68]. Table 4 shows the various types of vulnerabilities in autonomous vehicles at different levels.  
The vulnerabilities at different levels pose serious security and privacy concerns related to the use of autonomous vehicles. Some of the major security concerns include data security, network security, vehicle security and financial security [69].  
The main types of security threats include:  
1. **Data Theft**: Autonomous vehicles and self-driving cars form a part of a larger network of connected entities which continuously share data to provide a seamless user experience. Some of the data generated through different entities consist of personal user information such as financial details, contact details, travel habits and history. With this type of personal data at disposal, there are vulnerabilities related to data theft that can be used by attackers.
2. **Identity Theft**: The concept of autonomous vehicles focuses on the transfer of control from the human drivers to the vehicles. In such scenarios, the connected vehicles become easy targets of cyber criminals and hackers. These vehicles are prone to identity theft where the hackers can obtain the vehicle identification information and misuse it.
3. **Device Hijacking**: Vehicle hijacking is one of the biggest threats to autonomous vehicles. The attackers can gain control of the vehicle system and software and modify the algorithms to remotely control the vehicle. Once hijacked, the hackers can modify the important functioning units such as the navigation control unit, engine, brakes, heating systems, communication systems, vehicle camera and vision systems.
4. **Denial of Service**: Attackers can take advantage of the vulnerabilities of the least secured devices on the network to gain control of the entire network and overwhelm the connected entities. These types of attacks can be launched on an individual node or vehicle-to-vehicle or vehicle-to-infrastructure, resulting in a communication system disruption.
5. **Privacy Infringement**: Autonomous vehicles continuously generate data such as the vehicle location. These data provide personal information related to the user's travel history and navigation, which can be misused to track the user's current location and other whereabouts.
6. **Financial Fraud**: In countries such as India where toll taxes are automatically detected using RFID tags on the vehicles, there are serious concerns related to the  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Levels** & **Target Systems** & **Disrupted Services** \\ \hline
**Sensors** & Camera, GPS, LiDAR, Radar, proximity sensors, ultrasonic sensors & Parking assistance, object identification, navigation, collision avoidance, traffic signal identification, cruise control \\ \hline
**Device** & Access control systems & Anti-theft system, keyless entry systems, signal jamming, replay attack \\ \hline
**Software** & In Vehicle protocols: LIN, CAN, FlexRay & Communication system \\ \hline \hline \end{tabular}
\end{table}
Table 4: Vulnerabilities in Autonomous Vehicles [68].  
financial security of the linked bank accounts. Any insecure network or device may result in banking frauds and other related attacks such as ransomware.