As vehicles playing an increasingly important role in people’s daily life, requirements on safer and more comfortable driving experience have arisen. Connected vehicles (CVs) can provide enabling technologies to realize these requirements and have attracted widespread attentions from both academia and industry. These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications. Computation offloading techniques, such as cloud, edge, and fog computing, can help CVs process computation-intensive and large-scale computing tasks. Additionally, different cloud/edge/fog computing architectures are suitable for supporting different types of CV applications with highly different QoS requirements, which demonstrates the importance of the computing architecture design. However, most of the existing surveys on cloud/edge/fog computing for CVs overlook the computing architecture design, where they (i) only focus on one specific computing architecture and (ii) lack discussions on benefits, research challenges, and system requirements of different architectural alternatives. In this article, we provide a comprehensive survey on different architectural design alternatives based on cloud/edge/fog computing for CVs. The contributions of this article are: (i) providing a comprehensive literature survey on existing proposed architectural design alternatives based on cloud/edge/fog computing for CVs, (ii) proposing a new classification of computing architectures based on cloud/edge/fog computing for CVs: computation-aided and computation-enabled architectures, (iii) presenting a holistic comparison among different cloud/edge/fog computing architectures for CVs based on functional requirements of CV systems, including advantages, disadvantages, and research challenges, (iv) presenting a holistic overview on the design of CV systems from both academia and industry perspectives, including activities in industry, functional requirements, service requirements, and design considerations, and (v) proposing several open research issues of designing cloud/edge/fog computing architectures for CVs.

Architectural Design Alternatives Based on Cloud/Edge/Fog Computing for Connected Vehicles

The development of vehicular ad-hoc network (VANET) allows vehicle users to enjoy location-based services through the network at any time and place. However, it also raises location privacy issues. Privacy-preservation of large amounts of real-time location data is a critical issue. Existing research work, such as the mix-zone scheme, has protected users’ location privacy and driving routes to a certain extent. However, existing schemes have some deficiencies in security and efficiency. This paper presents a novel location privacy protection scheme. Vehicles can generate virtual locations dynamically based on the situation of surrounding vehicles to provide misleading information regarding the driving route and thus achieve location privacy. We use entropy of anonymity set and tracking success ratio as metrics to measure the level of privacy-preserving. Simulation experiments have been carried out to compare with other existing schemes. The results show that entropy of anonymity set in our scheme is 100% larger than the compared scheme and the tracking success ratio has decreased from 10% to 1%. So, the results illustrate that the proposed scheme offers better security and location-based services.

Efficient Privacy-Preserving Scheme for Real-Time Location Data in Vehicular Ad-Hoc Network

Vehicular networks promise features such as traffic management, route scheduling, data exchange, entertainment, and much more. With any large-scale technological integration comes the challenge of providing security. Blockchain technology has been a popular choice of many studies for making the vehicular network more secure. Its characteristics meet some of the essential security requirements such as decentralization, transparency, tamper-proof nature, and public audit. This study catalogues some of the notable efforts in this direction over the last few years. We analyze around 75 blockchain-based security schemes for vehicular networks from an application, security, and blockchain perspective. The application perspective focuses on various applications which use secure blockchain-based vehicular networks such as transportation, parking, data sharing/ trading, and resource sharing. The security perspective focuses on security requirements and attacks. The blockchain perspective focuses on blockchain platforms, blockchain types, and consensus mechanisms used in blockchain implementation. We also compile the popular simulation tools used for simulating blockchain and for simulating vehicular networks. Additionally, to give the readers a broader perspective of the research area, we discuss the role of various state-of-the-art emerging technologies in blockchain-based vehicular networks. Finally, we summarize the survey by listing out some common challenges and future research directions in this field. 

A Comprehensive Survey on the Applications of Blockchain for Securing Vehicular Networks

Vehicular cloud computing (VCC) is an improvement from conventional cloud computing to new revolutionized computing services including intelligent transportation, autonomous driving and vehicle control, Internet browsing, online documentation, and infotainment. It enables vehicles to autonomously share heterogeneous computational resources while solving unanticipated critical problems dynamically. However, in a world of black hats, technology often has a dark side as well. Therefore, the VCC is limited by considerable security and privacy challenges. The special characteristics of VCC, including the multitenancy nature of clouds, intermittent wireless communications, high mobility of vehicles, and rapid resource elasticity with decentralized operations, have promoted security solutions used in vehicular ad hoc networks and conventional cloud computing to be revised. This paper first presents a state-of-the-art study of VCC that focuses on VCC architecture, its features analysis, and extensive VCC applications. Second, the proposed threats identification taxonomy and an exhaustive survey on security and privacy issues in VCC are presented under a layered approach: physical resource layer, vehicle-to-anything (V2X) network layer, and vehicular cloud layer, as well as at a complete system level. Finally, we highlight and discuss challenges and open research issues that can be considered as future research directions.

Security and Privacy Challenges in Connected Vehicular Cloud Computing

The concept of Intelligent Transportation Systems (ITS) was developed in the 1980s when then upcoming technologies and cognitive information were incorporated into the road infrastructures and vehicles. The ITS infrastructure is critical yet not immune to both physical and cyber threats. Vehicles are cyber-physical systems which are a core component of ITS, can be either a target or a launching point for an attack on the ITS network. Unknown vehicle security vulnerabilities trigger a race among adversaries to exploit the weaknesses and security experts to mitigate the vulnerability. In this study, we identified opportunities for adversaries to take control of the in-vehicle network, which can compromise the safety, privacy, reliability, efficiency, and security of the transportation system. This study contributes in three ways to the literature of ITS security and resiliency. First, we aggregate individual risks that are associated with hacking the in-vehicle network to determine system-level risk. Second, we employ a risk-based model to conduct a qualitative vulnerability-oriented risk assessment. Third, we identify the consequences of hacking the in-vehicle network through a risk-based approach, using an impact-likelihood matrix. The qualitative assessment communicates risk outcomes for policy analysis. The outcome of this study would be of interest and usefulness to policymakers and engineers concerned with the potential vulnerabilities of such critical infrastructures.

Intelligent Transportation System Security: Impact-Oriented Risk Assessment of in-Vehicle Networks

Vehicular Ad-hoc Networks (VANETs) are sought to control traffic, avoid accidents, and control other aspects of traffic. It (VANET) is a piece of critical infrastructure that bolsters traffic management efficiency and road safety. Nowadays, VANET applications have received a great deal of attention by the research community due to the important role that such networks can play. However, security in VANETs still remains a big challenge due to its nature. This survey paper sheds some light on VANETs’ vulnerabilities and attacks. It surveys and examines some recent security solutions along with their achievements and limitations. As a result, we conclude that security is the key to success for VANET applications, but still some critical challenges remain. Moreover, when designing a sufficient security solution; privacy preservation, productivity, and usability should be taken into account. Therefore, the door for future research is open for a lot more contributions in this filed.

VANETs Security Issues and Challenges: A Survey

Due to the rapid growth in number of different protocols over the internet, internet protocols have become an ideal vehicle for covert communications. They represent a high bandwidth for such communications. Moreover, new highspeed network technology has significantly amplified the network’s covert channel capacity. Certainly, a covert channel bandwidth of only one bit size can easily allow transmission of a system bin code which can lead to tremendous risk. This paper presents a brief overview of network protocols-based covert channels, and surveys some recent and relevant work on covert channels detection and elimination techniques along with their achievements and limitations. In sum, the covert channel countermeasures—detection, elimination, mitigation, and capacity reduction—are still real challenges and lag behind an acceptable level of network security. Therefore, the research door is wide open for more contributions in this field. Keywords— covert channel, security; detection, prevention, elimination, capacity reduction, network protocols.

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Survey on Covert Storage Channel in Computer Network Protocols: Detection and Mitigation Techniques

advanced developments in intrusion detection systems (IDS) and computer network technology encourage hackers to find new ways to leak confidential information without being detected. When the interpretation of a security model adopted by a system is violated by a communication between two users, or processes operating on their behalf, it is said that the two users are communicating indirectly or covertly. A network covert channel refers to any communication channel that can be exploited by a process to transfer information in a manner that violates a system's security policy. Loopholes in network protocols attract covert channel exploitation. This paper sheds light on network covert channel countermeasures and the most recent detection and prevention methods of such channels. The achievements and limitations of these countermeasures are discussed. The paper further introduces the concept of network covert channel triangle (DSM - Development, Switching, and Micro-protocol); three elements that have the most direct positive impact in a network covert channel environment. In addition, the paper reflects on the challenges such covert channels impose.

Network Protocol Covert Channels: Countermeasures Techniques

A covert channel is a communication channel that is subjugated for illegal flow of information in a way that violates system security policies. It is a dangerous, invisible, undetectable, and developed security attack. Recently, Packet length covert channel has motivated many researchers as it is a one of the most undetectable network covert channels. Packet length covert channel generates a covert traffic that is very similar to normal terrific which complicates the detection of such type of covert channels. This motivates us to introduce a machine learning based detection scheme. Recently, a machine learning approach has proved its capability in many different fields especially in security field as it usually brings up a reliable and realistic results. Based in our developed content and frequency-based features, the developed detection scheme has been fully trained and tested. Our detection scheme has gained an excellent degree of detection accuracy which reaches 98% (zero false negative rate and 0.02 false positive rate).

Packet Length Covert Channel: A Detection Scheme

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Mobile Ad Hoc Network Routing Protocols: Performance Evaluation and Assessment

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