Biblio

With the increasing number of electric vehicles, the scale of the market also increases. In the past, the electric vehicle market had problems such as opaque information, numerous levels and data leakage, which were criticized for the impact of the overall development and policies of the electric vehicle industry. In view of the problems existing in the transparency and security of big data management transactions of the Internet of vehicles, this paper combs the commercial operation framework of the Internet of Vehicles Platform, analyses the feasibility and necessity of establishing the token system of the Internet of Vehicles Platform, and constructs the token economic system architecture of the Internet of Vehicles Platform and its development path.

Vehicular networks have been considered as a hopeful technology to enhance road safety, which is a crossing area of Internet of Things (IoT) and Intelligent Transportation Systems (ITS). Current Internet architecture using the TCP/IP model and based on host-to-host is limited when it comes to vehicular communications which are characterized by high speed and dynamic topology. Thus, using Named Data Networking (NDN) in connected vehicles may tackle the issues faced with the TCP/IP model. In this paper, we investigate the security concerns of applying NDN in vehicular environments and discuss the remaining challenges in order to guide researchers in this field to choose their future research direction.

Vehicles play an integral part in the life of a human being by facilitating in everyday tasks. The major concern that arises with this fact is that the rate of vehicle thefts have increased exponentially and retrieving them becomes almost impossible as the responsible party completely alters the stolen vehicles, leaving them untraceable. Ultimately, tracking and monitoring of vehicles using on-vehicle sensors is a promising and an efficient solution. The Internet of Things (IoT) is expected to play a vital role in revolutionizing the Security and Safety industry through a system of sensor networks by periodically sending the data from the sensors to the cloud for storage, from where it can be accessed to view or take any necessary actions (if required). The main contributions of this paper are the implementation and results of the prototype of a vehicle tracking and monitoring system. The system comprises of an Arduino UNO board connected to the Global Positioning System (GPS) module, Neo-6M, which senses the exact location of the vehicle in the form of latitude and longitude, and the ESP8266 Wi-Fi module, which sends the data to the Application Programming Interface (API) Cloud service, ThingSpeak, for storage and analyzing. An Android based mobile application is developed that utilizes the stored data from the Cloud and presents the user with the findings. Results show that the prototype is not only simple and cost effective, but also efficient and can be readily used by everyone from all walks of life to protect their vehicles.

As modern vehicles are complex IoT devices with intelligence capable to connect to an external infrastructure and use Vehicle-to-Everything (V2X) communication, there is a need to secure the communication to avoid being a target for cyber-attacks. Also, the organs of the car (sensors, communication, and control) each could have a vulnerability, that leads to accidents or potential deaths. Manufactures of cars have a huge responsibility to secure the safety of their costumers and should not skip the important security research, instead making sure to implement important security measures, which makes your car less likely to be attacked. This paper covers the relevant attacks and threats to modern vehicles and presents a security analysis with potential countermeasures. We discuss the future of modern and autonomous vehicles and conclude that more countermeasures must be taken to create a future and safe concept.

A new round of scientific and technological revolution and industrial reform promote the intelligent development of automobile and promote the deep integration of automobile with Internet, big data, communication and other industries. At the same time, it also brings network and data security problems to automobile, which is very easy to cause national security and social security risks. Intelligent vehicle Ethernet intrusion detection can effectively alleviate the security risk of vehicle network, but the complex attack means and vehicle compatibility have not been effectively solved. This research takes the vehicle Ethernet as the research object, constructs the machine learning samples for neural network, applies the self coding network technology combined with the original characteristics to the network intrusion detection algorithm, and studies a self-learning vehicle Ethernet intrusion detection algorithm. Through the application and test of vehicle terminal, the algorithm generated in this study can be used for vehicle terminal with Ethernet communication function, and can effectively resist 34 kinds of network attacks in four categories. This method effectively improves the network security defense capability of vehicle Ethernet, provides technical support for the network security of intelligent vehicles, and can be widely used in mass-produced intelligent vehicles with Ethernet.

The Internet of vehicles is emerging as an exciting application to improve safety and providing better services in the form of active road signs, pay-as-you-go insurance, electronic toll, and fleet management. Internet connected vehicles are exposed to new attack vectors in the form of cyber threats and with the increasing trend of cyber attacks, the success of autonomous vehicles depends on their security. Existing techniques for IoV security are based on the un-realistic assumption that all the vehicles are equipped with the same hardware (at least in terms of computational capabilities). However, the hardware platforms used by various vehicle manufacturers are highly heterogeneous. Therefore, a security protocol designed for IoVs should be able to detect the computational capabilities of the underlying platform and adjust the security primitives accordingly. To solve this issue, this paper presents a technique for algorithm-hardware separation for IoV security. The proposed technique uses an iterative routine and the corresponding execution time to detect the computational capabilities of a hardware platform using an artificial intelligence based inference engine. The results on three different commonly used micro-controllers show that the proposed technique can effectively detect the type of hardware platform with up to 100% accuracy.

With the gradually popular high-speed wireless networks and 5G environments, the quality and reliability of network services will be suited for mobile vehicles. In addition to communicating information between vehicles, they can also communicate information with surrounding roadside equipment, pedestrians or traffic signs, and thus improve the road safety of passers-by.Recently, various countries have continuously invested in research on autonomous driving and unmanned vehicles. The open communication environment of the Internet of Vehicles in 5G will expose all personal information in the field of wireless networks. This research is based on the consideration of information security and personal data protection. We will focus on how to protect the real-time transmission of information between mobile vehicles to prevent from imbedding or altering important transmission information by unauthorized vehicles, drivers or passers-by participating in communications. Moreover, this research proposes a multi-level security key management agreement based on a dynamic M-tree structure for Internet of Vehicles to achieve flexible and scalable key management on large-scale Internet of Vehicles.

With advantages of low cost, high mobility, and flexible deployment, unmanned aerial vehicle (UAVs) are employed to efficiently detect abnormal vehicle behaviors (AVBs) in the internet of vehicles (IoVs). However, due to limited resources including battery, computing, and communication, UAVs are selfish to work cooperatively. To solve the above problem, in this paper, a game theoretical UAV incentive scheme in IoVs is proposed. Specifically, the abnormal behavior model is first constructed, where three model categories are defined: velocity abnormality, distance abnormality, and overtaking abnormality. Then, the barging pricing framework is designed to model the interactions between UAVs and IoVs, where the transaction prices are determined with the abnormal behavior category detected by UAVs. At last, simulations are conducted to verify the feasibility and effectiveness of our proposed scheme.

The transportation system is becoming tremendously important in today's human activities and the number of urban vehicles grows rapidly. The vehicle theft also has become a shared concern for all vehicle owners. However, the present anti-theft system which maybe high reliable, lack of proper mechanism for preventing theft before it happens. This work proposes the internet of things based smart vehicle security staring system; efficient security provided to the vehicle owners relies on securing car ignition system by using a developed android application running on smart phone connected to the designed system installed in vehicle. With this system it is non- viable to access the vehicle's functional system in case the ignition key has been stolen or lost. It gives the drivers the ability to stay connected with their vehicle. Whenever the ignition key is stolen or lost, it is impossible to start the vehicle as the ignition system is still locked on the vehicle start and only the authorized person will be able to start the vehicle at convenient time with the combination of ignition key and smart phone application. This study proposes to design the system that uses node MCU, Bluetooth low energy (BLE), transistors, power relays and android smartphone in system testing. In addition, it is cost effective and once installed in the vehicle there is no more cost of maintenance.