Vehicular Cloud Computing Challenges and Security

With the acceleration of mobile applications, mobile cloud computing is envisioned to be the best fit solution to make a compromise between users' and service providers' benefits. An extension of mobile cloud computing, vehicular cloud computing, provides another viable solution, by consolidating the benefits of mobile cloud computing and vehicular communications. Among several challenges in this environment, privacy, service price and provision delay are the most important. In this paper, we propose a framework to address these challenges in a vehicular cloud based on a quality-of-experience (QoE) approach, discuss the drawbacks of existing architectures, and propose and validate a new architecture. This architecture is an extension of a system [1] we proposed in previous work. QoE is obtained via other mobile nodes in the vehicular cloud, and re-formulated according to a weighted combination of the three key factors: privacy, price and delay. Privacy is defined as a function of the information revealed to the service provider. We evaluate our proposal via simulations, and based on the numerical results, we show that QoE-based service provisioning in a vehicular cloud improves upon a naïve service provision approach, as well as other approaches that address only one of the factors.

Safely avoiding accident prone routes is vital to maintain safe and intelligent transportation. Real‐time crowd sourcing of accident causing factors (eg, icy roads, rain slicked road patches) combined with historical accident information can be utilized by intelligent navigation systems to avoid accident prone routes. A vehicle cloud can compute such safe routes and react faster than a centralized service given crowdsourced data such as images, sensor readings, and so on. However, in addition to the intelligent routing, the security and privacy of each data owner must be provided as well. Additionally, crowdsourced information must be validated in the vehicular cloud. In this paper, we examine approaches to ensure safe, secure, and private vehicular clouds.

The automotive industry has been continuously investing in the modernization of the vehicles by the addition of more sensors and computational power. With this evolution, Intelligent Transportation Systems (ITS) make up a services framework that seeks to mitigate problems in the road sector. Many ITS services are facilitated by creating vehicular clouds (VCs) by using the communication capabilities of other vehicles to provide cloud services closer to vehicular applications. However, often the computational resources present in the vehicles are underutilized. For this reason, we propose in this work a mechanism that efficiently allocates computational tasks to be performed in VCs. Simulation results on a realistic mobility trace show that, with our mechanism, tasks are more allocated, the reward from allocating these tasks was higher, resource waste was minimized, and less CPU is used in the allocation processing. Also, the proposed mechanism is statistically close to a globally optimal solution.

Globally, intelligent vehicles and telematics R&D through the integration of IT technologies in the vehicle are significant increasing. Real-time data communication for intelligent transportation system (ITS) is very important. It collects real-time data from the vehicle and provides the information collected from ITS center. We propose an effective and secure communication scheme for these communication procedures. In particular, our proposed SIP-based MVPN reduces signaling cost and has many advantages in security aspects. In addition, our proposed scheme performs the mobility management applying Network Mobility (NEMO) for the communication between the vehicles. In other words, we propose an ITS communication mechanism of SIP-based mobile VPN and V2V NEMO. Finally, our performance analysis show that the ITS of SIP-based MVPN is significantly reducing the handoff signaling cost.

Currently, the outbreak of COVID-19 pandemic has caused catastrophic effect on every aspect of our lives, globally. The entire human race of all countries and regions has suffered devastating losses. With its high infectiousness and mortality rate, it is of great significance to carry out effective precautions and prevention of COVID-19. Specifically, the transportation system has been confirmed as one of the crucial spreading routes. Hence, enhancing healthcare monitoring and infection tracking for high-mobility transportation system is infeasible for pandemic control. Meanwhile, due to the promising advantages in the emerging intelligent transportation system (ITS), vehicular ad hoc networks (VANETs) is able to collect and process relevant vehicular data for improving the driving experience and road safety, which provide a way for non-contact automatic healthcare monitoring. Furthermore, the proliferating cloud computing and blockchain techniques enable sufficient processing and storing capabilities, along with decentralized remote auditing towards heterogenous vehicular data. In this case, the automated infection tracking for pandemic control could be achieved accordingly. For the above consideration, in this paper we develop a practical homomorphic authentication scheme for cloud-assisted VANETs, where the healthcare monitoring for all involving passengers is provided. Notably, the integrated cloud-assisted VANET infrastructure is utilized, where the hybrid medical data acquisition module is attached. In this way, timely, non-contact measurement on all passengers’ physical status can be remotely done by vehicular cloud (VC), which could also drastically improve the efficiency and guarantee safety. Vulnerabilities of the employed dedicated-short-range-communication (DSRC) technique could be properly addressed with the applied homomorphic encryption design. Additionally, the decentralized blockchain-based vehicle recording mechanism is cooperatively performed by VC and edge units. Infection tracking on specific vehicle and individual can be offered in this way. Each signature sequence is collaboratively maintained and verified by the current roadside unit (RSU) and its neighbor RSUs. The security analysis demonstrates that the proposed scheme is secure against major attacks, while the performance comparison with the state-of-the-arts relevant methods are presented for efficiency discussion.

The adoption of vehicular cloud computing for sequential recommendation offers flexible, reliable, and scalable computing resources in intelligent transportation systems. However, it also raises privacy concerns of drivers/passengers regarding the upload of sensitive data and models to vehicular cloud servers. To address this issue, we propose a novel privacy-preserving sequential recommendation method for intelligent transportation systems (named Grapeseed) based on split learning and variational autoencoder (VAE). Specifically, the vehicular client first inputs raw data into an encoder to produce latent variables locally and uploads these variables to the vehicular cloud server. Then, the vehicular cloud server generates and returns intermediate variables derived from these latent variables. Upon receiving these intermediate variables, the vehicular client calculates the final recommendation results. Extensive experiment results and analyses demonstrate that the proposed method improves both performance and communication efficiency between vehicular cloud servers and clients while preserving privacy.

Aim. Threats of a non-physical nature have a significant effect on the security of intelligent transportation systems (ITS). They may have the form of unlawful interference in the development and implementation of ITS. The creation of a trusted framework for the development and implementation of ITS is examined as in the case of intelligent water transportation systems (IWTS). Problems. By decree of the President of the Russian Federation, ITS, telecommunications and security of information processing are among the priority areas of scientific and technological development. ITS technologies, as well as those involved in the creation of trusted, secure system and application software are among the most important critical high technologies. The operation of ITS involves wide use of computerised systems that implement the latest information and telecommunication technologies, automated and automatic control technologies, artificial intelligence that can pose security threats. ITS are to be developed and operated in a trusted environment. Methods. The paper used the methodology for ensuring the security of IWTS, development of secure hardware and software platforms for secure automated systems, methods of system analysis, dependability theory, information protection, and law. Results. The paper defines the problem of creating a trusted framework for the development and implementation of IWTS, the applicable terminology is developed. The author examined the effect of IWTS on the security of critical information infrastructure (CII) and national security, developed a model of relationships between the IWTS security domains taking into account threats of physical and non-physical origin. Examples of computer incidents within IWTS that caused consequences at the national and international levels are given. The composition of the IWTS facilities attributed to CII is defined, critical processes implemented by standard CII facilities as part of the IWTS are set forth. The author lists conceptual problems of IWTS security, defines the principles of creating a trusted framework for the development and implementation of IWTS. Conclusion. Ensuring the security of IWTS against modern threats requires solving a number of problems associated with the creation of a trusted framework for the development and implementation of IWTS. For the purpose of improving the timeliness and quality of their solution, the paper proposes an intuitive terminology that reflects the subject area and helps finding a common understanding of the security domain by experts from various industries. IWTS facilities have an effect on CII security and national security in general. That is taken into account in the model of relationships between IWTS security domains, demonstrated using cases of computer incidents within IWTS that caused consequences at the national and international level. Given the above, the paper lists IWTS facilities attributed to CII and sets forth examples of critical processes implemented by standard CII facilities as part of the IWTS. The defined list of conceptual IWTS security problems take into account the growing landscape of IWTS security threats that includes insecure software, hardware and software platforms, software and hardware systems and emerging technologies. When developing the principles for the creation of a trusted IWTS development and implementation framework, the author took into account the best practice of implementing the methodology for creating national secure hardware and software platforms of CII facilities that enables the creation of secure automated systems for various applications that are based on domestically-developed solutions. The examined matters are of a systemic nature, which allows using the findings in the development and implementation of ITS in other modes of transportation.

A survey on vehicular cloud computing

Vehicular cloud as a kind of resource aggregation can provide cloud service flexibly for intelligent transportation systems and individual users. However, the dynamicity of vehicular cloud such as dynamic multihop transmission also brings new challenges to workflow scheduling. In this paper, a heuristic dynamic workflow scheduling (HDWS) strategy is proposed to solve the problem of workflow scheduling with dynamic multihop transmission in vehicular cloud. HDWS establishes a local scheduling based on the current resource status and task sets. The makespan of local scheduling is optimized by reassigning tasks based on task interdependency. At run time of an application, HDWS estimates the makespan in real time based on the current transmission rates and the unready tasks will be rescheduled once it detects the degradation of the makespan. Experimental results show that the proposed HDWS can improve the service success ratio of vehicular cloud and decrease the makespan compared to the existing approaches.

Vehicular communication is regarded as a backbone for the development of intelligent transportation system (ITS). Recently vehicular communication has attracted researchers from both academia and industry all over the world, notably, in the United States of America, Japan and European Union. The rapid advances in wireless technologies provide opportunities to utilize them in vehicular communication in advanced road safety applications. The most important feature of vehicular communication is to improve the road traffic safety, efficiency, comfort and quality of everyday road travel. Networking in particular and communication in general are important rudiments in the development of ITS. Generally, in vehicular communication, the information exchange occurs among vehicles not only in an ad-hoc based vehicle-to-vehicle networking but also in a vehicle-to-infrastructure with possible intermediate infrastructure-to-infrastructure networking. Therefore, the infrastructure plays major role in order to realize the full potential of vehicular communications. This chapter provides an in-depth survey of the infrastructures and technologies that are recently proposed as part of future ITS developments as well as tested for vehicular communications in mobile environment. Specifically, we provide an in-depth analysis of wireless technology-applications such as ad-hoc networking and wireless local area network (WLAN), dedicated short-range communication (DSRC), cellular technology and NOTICE Architecture, and compare their characteristics in terms of their abilities to support vehicular communications for development of ITS.

Vehicular Clouds introduces a new paradigm that addresses and potentially enhances underutilization of on-board computing resources through aggregation to solve several computational tasks in Intelligent Transportation System. The most challenging issue in Vehicle Cloud is the task allocation among the dynamically changing amount of available resources. For further research towards this issue, a realistic road traffic system models which could generate traffic flow with high accuracy must be designed. In this paper, we conduct a study on short-term traffic flow predictions for our envisioned road traffic prediction system. Five prediction models, including double exponential smoothing (DES), seasonal autoregressive moving average (SARIMA), K-nearest neighbor (KNN), back-propagation neural network (BP-NN) and support vector regression (SVR), are implemented. Then, three different error metrics are used to evaluate the performance of these models. Finally, the results shows that SARIMA and BP neural network are two precise and stationary prediction models and thus are the best candidates to be embedded in an road traffic load prediction system.

A novel block-chain based secure cross-domain interaction approach for intelligent transportation systems

This paper examines the relationship between public and private investments in intelligent transportation system (ITS) technology and the effects on transportation performance through the highway system. ITS technology is an infrastructure that promotes integrated information sharing that can be used to improve system performance. ITS combines better infrastructure with information and control technologies to ( a) reduce traffic congestion by maintaining traffic flow, ( b) reduce transportation-generated pollution, ( c) improve transport efficiency, and ( d) produce economic benefits. A statistical analysis of partial least squares structural equation modeling was used to test three hypothesized relationships. Primary data were collected from U.S.-based commercial vehicle transportation service providers. Respondents were parceled with a geographic information system analysis of secondary data from the U.S. Department of Transportation National ITS Deployment Tracking Survey. On the basis of their level of regional ITS experience, primary data respondents were matched to regions and split between regions with low ITS experience and high ITS experience as a proxy for regional public investments in ITS. Performance measures were based on efficiency, reliability, responsiveness, quality, carbon emissions reduction, and equipment utilization for commercial vehicle operators. Results indicate that private investments in ITS significantly positively affect the responsiveness performance measure for commercial vehicle operators in regions with high public ITS investments. The same relationship is not significant in regions with low public ITS investments, which indicates at least some transportation performance improvements for regions with higher investments in ITS. Implications for research and practice are discussed.

Impact factor as an indicator of efficiency or sustainability is entirely correlated with the continuous development of the smart city concept technology application. Intelligent transportation systems (ITSs) and particularly autonomous vehicles are expected to play an important role in this challenging environment. Fast and secure connections will be pivotal in order to achieve this new vehicular communications’ application era. The use of millimeter-wave (mmWave) frequency range is the most promising approach to allow these real-time, high-demand applications that require higher bandwidth with the minimum possible latency. However, an in-depth mmWave-channel characterization of the environment is required for a proper mmWave-based solution deployment. In this work, a complete radio wave propagation channel characterization for a mmWave smart parking solution deployment in a complex outdoor environment was assessed at a 28 GHz frequency band. The considered scenario is a parking lot placed in an open free university campus area surrounded by inhomogeneous vegetation. The vehicle and vegetation density within the scenario, in terms of inherent transceivers density and communication impairments, leads to overall system operation challenges, given by multiple communication links operation at line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. By means of an in-house developed 3D ray launching (3D-RL) algorithm, the impact of variable vegetation density is addressed, providing precise modelling estimations of large-scale multipath propagation effects in terms of received power levels and path loss. The obtained results along with the proposed simulation methodology can aid in an adequate characterization of an mmWave communication channel for new vehicular communications networks, applications, and deployments, considering the outdoor conditions as well as the impact of different vegetation densities, for current as well as for future wireless technologies.

As vehicular communications for beyond fifth‐generation (B5G) and sixth‐generation (6G) is picking up interests from academia and industry recently, more and more research and development have been devoted towards the establishment of vehicular communications for B5G and 6G that is capable of supporting the ever more intelligent transportation systems. One key facilitating the design and improvement of vehicular communications for B5G and 6G is channel modelling, which is widely regarded as the foundation of all communication and networking systems. In this paper, the authors focus on the research and analysis of B5G and 6G vehicular channel measurements and modelling. By emphasising the new requirements and challenges that the emerging B5G and 6G technologies and frequency bands bring to vehicular communication channel measurements and modelling, they present an overview of the existing work and identify the limitations therein, and provide guidelines on the channel model development and adoption for various system development and verification objectives. Finally, future challenges related to vehicular channel measurements, modelling, and their application for B5G and 6G are addressed.