Biblio

The real-time map updating enables vehicles to obtain accurate and timely traffic information. Especially for driverless cars, real-time map updating can provide high-precision map service to assist the navigation, which requires vehicles to actively upload the latest road conditions. However, due to the untrusted network environment, it is difficult for the real-time map updating server to evaluate the authenticity of the road information from the vehicles. In order to prevent malicious vehicles from deliberately spreading false information and protect the privacy of vehicles from tracking attacks, this paper proposes a trust-based real-time map updating scheme. In this scheme, the public key is used as the identifier of the vehicle for anonymous communication with conditional anonymity. In addition, the blockchain is applied to provide the existence proof for the public key certificate of the vehicle. At the same time, to avoid the spread of false messages, a trust evaluation algorithm is designed. The fog node can validate the received massages from vehicles using Bayesian Inference Model. Based on the verification results, the road condition information is sent to the real-time map updating server so that the server can update the map in time and prevent the secondary traffic accident. In order to calculate the trust value offset for the vehicle, the fog node generates a rating for each message source vehicle, and finally adds the relevant data to the blockchain. According to the result of security analysis, this scheme can guarantee the anonymity and prevent the Sybil attack. Simulation results show that the proposed scheme is effective and accurate in terms of real-time map updating and trust values calculating.

With the economic development, the number of cars is increasing, and the traffic accidents and congestion problems that follow will not be underestimated. The concept of the Internet of Vehicles is becoming popular, and demand for intelligent traffic is growing. In this paper, the warning scheme we proposed aims to solve the traffic problems. Using intelligent terminals, it is faster and more convenient to obtain driving behaviors and road condition information. The application of blockchain technology can spread information to other vehicles for sharing without third-party certification. Group signature-based authentication protocol guarantees privacy and security while ensuring identity traceability. In experiments and simulations, the recognition accuracy of driving behavior can reach up to 94.90%. The use of blockchain provides secure, distributed, and autonomous features for the solution. Compared with the traditional signature method, the group signature-based authentication time varies less with the increase of the number of vehicles, and the communication time is more stable.

As an extension of Internet of Things (IoT) in transportation sector, the Internet of Vehicles (IoV) can greatly facilitate vehicle management and route planning. With ever-increasing penetration of IoV, the security and privacy of driving data should be guaranteed. Moreover, since vehicles are often left unattended with minimum human interventions, the onboard sensors are vulnerable to physical attacks. Therefore, the physically secure authentication and key agreement (AKA) protocol is urgently needed for IoV to implement access control and information protection. In this paper, physical unclonable function (PUF) is introduced in the AKA protocol to ensure that the system is secure even if the user devices or sensors are compromised. Specifically, PUF, as a hardware fingerprint generator, eliminates the storage of any secret information in user devices or vehicle sensors. By combining password with PUF, the user device cannot be used by someone else to be successfully authenticated as the user. By resorting to public key cryptography, the proposed protocol can provide anonymity and desynchronization resilience. Finally, the elaborate security analysis demonstrates that the proposed protocol is free from the influence of known attacks and can achieve expected security properties, and the performance evaluation indicates the efficiency of our protocol.

The future fifth-generation (5G) mobile communications system has already become a focus around the world. A large number of late-model services and applications including high definition visual communication, internet of vehicles, multimedia interaction, mobile industry automation, and etc, will be added to 5G network platform in the future. Different application services have different security requirements. However, the current user authentication for services and applications: Extensible Authentication Protocol (EAP) suggested by the 3GPP committee, is only a unitary authentication model, which is unable to meet the diversified security requirements of differentiated services. In this paper, we present a new diversified identity management as well as a flexible and composable three-factor authentication mechanism for different applications in 5G multi-service systems. The proposed scheme can provide four identity authentication methods for different security levels by easily splitting or assembling the proposed three-factor authentication mechanism. Without a design of several different authentication protocols, our proposed scheme can improve the efficiency, service of quality and reduce the complexity of the entire 5G multi-service system. Performance analysis results show that our proposed scheme can ensure the security with ideal efficiency.

Traditionally, the vehicle has been the extension of the manual ambulatory system, docile to the drivers' commands. Recent advances in communications, controls and embedded systems have changed this model, paving the way to the Intelligent Vehicle Grid. The car is now a formidable sensor platform, absorbing information from the environment, from other cars (and from the driver) and feeding it to other cars and infrastructure to assist in safe navigation, pollution control and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Like other important instantiations of the Internet of Things (e.g., the smart building, etc), the Internet of Vehicles will not only upload data to the Internet with V2I. It will also use V2V communications, storage, intelligence, and learning capabilities to anticipate the customers' intentions and learn from other peers. V2I and V2V are essential to the autonomous vehicle, but carry the risk of attacks. This paper will address the privacy attacks to which vehicles are exposed when they upload private data to Internet Servers. It will also outline efficient methods to preserve privacy.

Autonomous vehicles must communicate with each other effectively and securely to make robust decisions. However, today's Internet falls short in supporting efficient data delivery and strong data security, especially in a mobile ad-hoc environment. Named Data Networking (NDN), a new data-centric Internet architecture, provides a better foundation for secure data sharing among autonomous vehicles. We examine two potential threats, false data dissemination and vehicle tracking, in an NDN-based autonomous vehicular network. To detect false data, we propose a four-level hierarchical trust model and the associated naming scheme for vehicular data authentication. Moreover, we address vehicle tracking concerns using a pseudonym scheme to anonymize vehicle names and certificate issuing proxies to further protect vehicle identity. Finally, we implemented and evaluated our AutoNDN application on Raspberry Pi-based mini cars in a wireless environment.

Currently, the networking of everyday objects, socalled Internet of Things (IoT), such as vehicles and home automation environments is progressing rapidly. Formerly deployed as domain-specific solutions, the development is continuing to link different domains together to form a large heterogeneous IoT ecosystem. This development raises challenges in different fields such as scalability of billions of devices, interoperability across different IoT domains and the need of mobility support. The Information-Centric Networking (ICN) paradigm is a promising candidate to form a unified platform to connect different IoT domains together including infrastructure, wireless, and ad-hoc environments. This paper describes a vision of a harmonized architectural design providing dynamic access of data and services based on an ICN. Within the context of connected vehicles, the paper introduces requirements and challenges of the vision and contributes in open research directions in Information-Centric Networking.

This paper proposes a prototype of a level 3 autonomous vehicle using Raspberry Pi, capable of detecting the nearby vehicles using an IR sensor. We make the first attempt to analyze autonomous vehicles from a microscopic level, focusing on each vehicle and their communications with the nearby vehicles and road-side units. Two sets of passive and active experiments on a pair of prototypes were run, demonstrating the interconnectivity of the developed prototype. Several sensors were incorporated into an emulation based on System-on-Chip to further demonstrate the feasibility of the proposed model.

Automation of real time car parking system (RTCPS) using mobile cloud computing (MCC) and vehicular networking (VN) has given rise to a novel concept of integrated communication-computing platforms (ICCP). The aim of ICCP is to evolve an effective means of addressing challenges such as improper parking management scheme, traffic congestion in parking lots, insecurity of vehicles (safety applications), and other Infrastructure-to-Vehicle (I2V) services for providing data dissemination and content delivery services to connected Vehicular Clients (VCs). Edge (parking lot based) Fog computing (EFC) through road side sensor based monitoring is proposed to achieve ICCP. A real-time cloud to vehicular clients (VCs) in the context of smart car parking system (SCPS) which satisfies deterministic and non-deterministic constraints is introduced. Vehicular cloud computing (VCC) and intra-Edge-Fog node architecture is presented for ICCP. This is targeted at distributed mini-sized self-energized Fog nodes/data centers, placed between distributed remote cloud and VCs. The architecture processes data-disseminated real-time services to the connected VCs. The work built a prototype testbed comprising a black box PSU, Arduino IoT Duo, GH-311RT ultrasonic distance sensor and SHARP 2Y0A21 passive infrared sensor for vehicle detection; LinkSprite 2MP UART JPEG camera module, SD card module, RFID card reader, RDS3115 metal gear servo motors, FPM384 fingerprint scanner, GSM Module and a VCC web portal. The testbed functions at the edge of the vehicular network and is connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. This research seeks to facilitate urban renewal strategies and highlight the significance of ICCP prototype testbed. Open challenges and future research directions are discussed for an efficient VCC model which runs on networked fog centers (NetFCs).

Thanks to advancement of vehicle technologies, Unmanned Aerial Vehicle (UAV) now widely spread over practical services and applications affecting daily life of people positively. Especially, multiple heterogeneous UAVs with different capabilities should be considered since UAVs can play an important role in Internet of Things (IoT) environment in which the heterogeneity and the multi domain of UAVs are indispensable. Also, a concept of barrier-coverage has been proved as a promising one applicable to surveillance and security. In this paper, we present collision-free reinforced barriers by heterogeneous UAVs to support multi domain. Then, we define a problem which is to minimize maximum movement of UAVs on condition that a property of collision-free among UAVs is assured while they travel from current positions to specific locations so as to form reinforced barriers within multi domain. Because the defined problem depends on how to locate UAVs on barriers, we develop a novel approach that provides a collision-free movement as well as a creation of virtual lines in multi domain. Furthermore, we address future research topics which should be handled carefully for the barrier-coverage by heterogeneous UAVs.

The Internet of Vehicles (IoV) is a complex and dynamic mobile network system that enables information sharing between vehicles, their surrounding sensors, and clouds. While IoV opens new opportunities in various applications and services to provide safety on the road, it introduces new challenges in the field of digital forensics investigations. The existing tools and procedures of digital forensics cannot meet the highly distributed, decentralized, dynamic, and mobile infrastructures of the IoV. Forensic investigators will face challenges while identifying necessary pieces of evidence from the IoV environment, and collecting and analyzing the evidence. In this article, we propose TrustIoV - a digital forensic framework for the IoV systems that provides mechanisms to collect and store trustworthy evidence from the distributed infrastructure. Trust-IoV maintains a secure provenance of the evidence to ensure the integrity of the stored evidence and allows investigators to verify the integrity of the evidence during an investigation. Our experimental results on a simulated environment suggest that Trust-IoV can operate with minimal overhead while ensuring the trustworthiness of evidence in a strong adversarial scenario.

The connection of automotive systems with other systems such as road-side units, other vehicles, and various servers in the Internet opens up new ways for attackers to remotely access safety relevant subsystems within connected cars. The security of connected cars and the whole vehicular ecosystem is thus of utmost importance for consumer trust and acceptance of this emerging technology. This paper describes an approach for on-board detection of unanticipated sequences of events in order to identify suspicious activities. The results show that this approach is fast enough for in-vehicle application at runtime. Several behavior models and synchronization strategies are analyzed in order to narrow down suspicious sequences of events to be sent in a privacy respecting way to a global security operations center for further in-depth analysis.

With the advances in the areas of mobile computing and wireless communications, V2X systems have become a promising technology enabling deployment of applications providing road safety, traffic efficiency and infotainment. Due to their increasing popularity, V2X networks have become a major target for attackers, making them vulnerable to security threats and network conditions, and thus affecting the safety of passengers, vehicles and roads. Existing research in V2X does not effectively address the safety, security and performance limitation threats to connected vehicles, as a result of considering these aspects separately instead of jointly. In this work, we focus on the analysis of the tradeoffs between safety, security and performance of V2X systems and propose a dynamic adaptability approach considering all three aspects jointly based on application needs and context to achieve maximum safety on the roads using an Internet of vehicles. Experiments with a simple V2V highway scenario demonstrate that an adaptive safety/security approach is essential and V2X systems have great potential for providing low reaction times.

Interconnected everyday objects, either via public or private networks, are gradually becoming reality in modern life - often referred to as the Internet of Things (IoT) or Cyber-Physical Systems (CPS). One stand-out example are those systems based on Unmanned Aerial Vehicles (UAVs). Fleets of such vehicles (drones) are prophesied to assume multiple roles from mundane to high-sensitive applications, such as prompt pizza or shopping deliveries to the home, or to deployment on battlefields for battlefield and combat missions. Drones, which we refer to as UAVs in this paper, can operate either individually (solo missions) or as part of a fleet (group missions), with and without constant connection with a base station. The base station acts as the command centre to manage the drones' activities; however, an independent, localised and effective fleet control is necessary, potentially based on swarm intelligence, for several reasons: 1) an increase in the number of drone fleets; 2) fleet size might reach tens of UAVs; 3) making time-critical decisions by such fleets in the wild; 4) potential communication congestion and latency; and 5) in some cases, working in challenging terrains that hinders or mandates limited communication with a control centre, e.g. operations spanning long period of times or military usage of fleets in enemy territory. This self-aware, mission-focused and independent fleet of drones may utilise swarm intelligence for a), air-traffic or flight control management, b) obstacle avoidance, c) self-preservation (while maintaining the mission criteria), d) autonomous collaboration with other fleets in the wild, and e) assuring the security, privacy and safety of physical (drones itself) and virtual (data, software) assets. In this paper, we investigate the challenges faced by fleet of drones and propose a potential course of action on how to overcome them.

Internet of Things (IoT) depicts an intelligent future, where any IoT-based devices having a sensorial and computing capabilities to interact with each other. Recently, we are living in the area of internet and rapidly moving towards a smart planet where devices are capable to be connected to each other. Cooperative ad-hoc vehicle systems are the main driving force for the actualization of IoT-based concept. Vehicular Ad-hoc Network (VANET) is considered as a promising platform for the intelligent wireless communication system. This paper presents and analyzes the tradeoffs between the security and reliability of the IoT-based VANET system in the presence of eavesdropping attacks using smart vehicle relays based on opportunistic relay selection (ORS) scheme. Then, the optimization of the distance between the source (S), destination (D), and Eavesdropper (E) is illustrated in details, showing the effect of this parameter on the IoT-based network. In order to improve the SRT, we quantify the attainable SRT improvement with variable distances between IoT-based nodes. It is shown that given the maximum tolerable Intercept Probability (IP), the Outage Probability (OP) of our proposed model approaches zero for Ge → ∞, where Ge is distance ratio between S — E via the vehicle relay (R).