A Game-Theoretic Approach for Distributed Attack Mitigation in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are nowadays considered very important applications of smart cities. One of the most important technologies that are utilized to support ITS is Vehicular Ad-hoc Networks (VANETs). In VANETs, vehicles communicate with each other (V2V) or with the infrastructure (Roadside Units) (V2I). Roadside Units (RSUs) collect data from vehicles in the coverage area and send it to cloud servers through the Internet. Cloud servers have high performance computational and storage capabilities that ITS applications require for data processing. However, due to the real-time requirements of the ITS applications, cloud approach alone cannot be guaranteed to satisfy the strict time constraints due to long latency access of the centralized cloud server. Fog Computing is an emerging approach that extends the services of cloud computing to the edge of the network. Fog Computing can be utilized in VANETs through deployment of fog nodes into RSUs. One of the major challenges is identifying the optimum number, locations and computational capabilities of the RSUs particularly in urban regions where obstacles exist heavily inside the coverage area of the RSUs. In this paper, we consider the optimization problem of fog-based RSU placement where the objective is to maximize the achieved level of service quality in a cost-effective way. The problem is formulated as a Satisfiability Modulo Theories (SMT) problem and solved using Microsoft Z3. The proposed approach is able to generate a set of solutions as Pareto front. We obtained data from OpenStreetMap for Cairo city. Our approach outperforms other solutions in the literature in terms of cost.

Emerging as the effective strategy of intelligent transportation system (ITS), vehicular ad hoc networks (VANETs) have the capacity of drastically improving the driving experience and road safety. In typical VANET scenarios, high mobility and volatility of vehicles result in dynamic topology of vehicular networks. That is, individual vehicle may pass through the effective domain of multiple neighboring road-side-units (RSUs) during a comparatively short time interval. Hence, efficient and low-latency cross-domain verification with all the successive RSUs is of significance. Recently, a lot of research on VANET authentication and key distribution was presented, while the critical cross-domain authentication (CDA) issue has not been properly addressed. Particularly, the existing CDA solutions mainly reply on the acquired confidential keying information from the neighboring entities (RSUs and vehicles), while too much trustworthiness is granted to the involved RSUs. Please note that the RSUs are distributively located and may be compromised or disabled by adversary, thus vital vehicle information may be revealed. Furthermore, frequent data interactions between RSUs and cloud server are always the major requisite so as to achieve mutual authentication with cross-domain vehicles, which leads to heavy bandwidth consumption and high latency. In this paper, we address the above VANET cross-domain authentication issue under the novel RSU edge networks assumption. Please note that RSUs are assumed to be semi-trustworthy entity in our design, where critical vehicular keying messages remain secrecy. Homomorphic encryption design is applied for all involved RSUs and vehicles. In this way, successive RSUs could efficiently verify the cross-domain vehicle with the transited certificate from the neighbor RSUs and vehicle itself, while the identity and secrets of each vehicle is hidden all the time. Afterwards, dynamic updating towards the anonymous vehicle identity is conducted upon validation, where conditional privacy preserving is available. Moreover, pairing-free mutual authentication method is used for efficiency consideration. Formal security analysis is given, proving that the HCDA mechanism yields desirable security properties on VANET cross domain authentication issue. Performance discussions demonstrate efficiency of the proposed HCDA scheme compared with the state-of-the-art.

In transportation environment, Intelligent Transportation System (ITS) is being used in various stages of every transport mode (road, rail, air & sea). The aim of intelligent transportation system is to provide the On-Road Vehicles (ORVs) with reliable Internet access connectivity, emergency notification and other safety information via infrastructure-based Road Side Units (RSUs). In the past decade, intelligent transportation system has been started in many countries where RSUs are provided with all type of communication services to connect, compute, communicate and share the information between its neighboring RSUs and on-road vehicles. However, there are certain diffcuilties in which the information cannot be delivered reliably such as Line Of Sight (LOS) communication with on-road vehicles, packet loss, latency, retransmission overhead and multiple target tracking of objects over time-to-time etc. Thus, the intelligent transportation system becomes a complex network of entities. Modern intelligent transportation systems use relay-RSU nodes (i.e., small sized Unmanned Aerial Vehicles) also referred as RRSU node network deployed between satellites and on-road vehicles as they provide many advanages like coverage, reliability and information sharing without depending more on knowledge provided by satellites. In this paper, a novel Aerial Intelligent Relay-Road Side Unit (AIR-RSU) framework has been proposed to determine the network connectivity status level and analyze the communication link stability among RRSUs, and between RRSUs and on-road vehicles for every time instants Ti based on certain performance metrics discussed in this paper. The proposed AIR-RSU framework holds the precise status/information about the network connectivity needed in the transportation environment carefully and effectively accounting the frequent changes in positions. The performance of the proposed AIR-RSU framework is evaluated using rectangle waypoint mobility model for on-road vehicles and steady state random waypoint mobility model for RRSU nodes, which measures the network connectivity status and the performance metrics periodically. Furthermore, a comparative analysis is done to both individual nodes and entire network in terms of network load.

Vehicular wireless communication has recently generated wide interest in the area of wireless network research. Automatic Incident Detection (AID), which is the recent focus of research direction in Intelligent Transportation System (ITS), aims to increase road safety. These advances in technology enable traffic systems to use data collected from vehicles on the road to detect incidents. We develop an automatic incident detection method that has a significant active road safety application for alerting drivers about incidents and congestion. Our method for detecting traffic incidents in a highway scenario is based on the use of distance and time for changing lanes along with the vehicle speed change over time. Numerical results obtained from simulating our automatic incident detection technique suggest that our incident detection rate is higher than that of other techniques such as integrated technique. probabilistic technique and California Algorithm. We also propose a technique to maximize the number of vehicles aware of Road Side Units (RSUs) in order to enhance the accuracy of our AID technique. In our proposed Method. IEEE 802.11 standard is used at RSUs with multiple antennas to assign each lane a specific channel. To validate our proposed approach. we present both analytical and simulation scenarios. The empirical values which are obtained from both analytical and simulation results have been compared to show their consistency. Results indicate that the IEEE 802.11 standard with its beaconing mechanism can be successfully used for Vehicle to Infrastructure (V2I) communications.

An intelligent transportation System (ITS) is an unconventional application that aims to provide traffic congestion information and emergency information to other vehicles. In ITS, the compilation and distribution of traffic event information by vehicles are of the most extreme significance. To establish an effective data-sharing network in ITS, the vehicles need to share the data in a protected form in real-time. Conventional ITS system includes data streaming from On-Board Unit (OBU) sensors through Road Side Units (RSU) to centralized cloud servers. Nevertheless, it is still a challenge to distribute essential event information in a selected area under the dynamic ITS environment and in the existence of a malicious vehicle. The current fundamental issues which emerge include privacy concerns due to third party management of cloud servers, single point of failure which are a bottleneck in data flow among the vehicles.

Vehicular communication is a crucial component of intelligent transportation systems (ITS) upon which many services are based starting with relaying traffic conditions up to enabling autonomous driving. Using a backhaul link, a road side unit (RSU) is assumed to fetch content from the Internet to serve the requests of incoming vehicles while they are within its range. Unless an effective caching mechanism is employed at the RSU, popular content might be unnecessarily retrieved from the network backhaul repeatedly especially in scenarios with large number of vehicles. This incurs significant capital and operating expenditures to RSU operators due to backhaul leasing and utilization. In this work, we explore cost-effective solutions for RSU operators by leveraging the content that is readily available on vehicles within the RSU's coverage range to intelligently cache popular content and serve newly arriving vehicles. However, due to the limited RSUs storage capacity and continuous flow of contents, the problem of establishing an RSU caching strategy to maximize the serving rate of incoming vehicles in an energy-efficient manner is challenging. Thus, we propose a technique based on deep reinforcement learning and demonstrate its effectiveness compared to the state-of-the-art.

Today, the Intelligent Transportation Systems (ITS) are already in deep integration phase all over the world. One of the most significant enablers for ITS are vehicle positioning and tracking techniques. Worldwide integration of ITS employing Dedicated Short Range Communications (DSRC) and European standard for vehicular communication, known as ETSI ITS-G5, brings a variety of options to improve the positioning in areas where GPS connectivity is lacking precision. Utilization of the ready infrastructure, next-generation cellular 5G networks, and surrounding electronic devices together with conventional positioning techniques could become the solution to improve the overall ITS operation in vehicle-to-everything (V2X) communication scenario. Nonetheless, effective and secure communication protocols between the vehicle and roadside units should be both analyzed and improved in terms of potential attacks on the transmitted positioning-related data. In particular, said information might be misused or stolen at the infrastructure side conventionally assumed to be trusted. In this paper, we first survey different methods of vehicle positioning, which is followed by an overview of potential attacks on ITS systems. Next, we propose potential improvements allowing mutual authentication between the vehicle and infrastructure aiming at improving positioning data privacy. Finally, we propose a vision on the development and standardization aspects of such systems.

Comprised of a broad range of diverse technologies, including information processing, communications, control, and electronics, Intelligent Transportation Systems (ITS) were first introduced as a means to solve the conflict between constantly increasing travel demand and insufficient transportation infrastructure. However, the impact of ITS on road safety was soon realized, and it became one of the major purposes of some ITS systems instead of only a side product. This paper summarizes the impacts of ITS technologies on road safety and the challenges of ITS safety evaluation. Based on the evaluation of collected ITS benefits information, this paper concludes that a variety of ITS technologies have the potential to make a substantial contribution to road safety and thereby have a substantial positive economic impact in the United States.

Emerging intelligent transportation systems (ITS) are based on several technologies. A new concept of integrating visible light communications (VLC) in ITS is introduced in this paper. VLC in ITS is a cost effective method of implementation. This paper presents a VLC broadcast system considering LED-based traffic lights. It discusses the integration of traffic light road side unit (RSUs) within the existing ITS architecture. A prototype demonstrator of the designed VLC systems is also presented. A robust modulation technique based on direct sequence spread spectrum (DSSS) sequence inverse keying (SIK) has been implemented to minimize the effect of noise sources. Experimental results show data communication range of over 40m with 200mm custom designed traffic light, even during bright sun light.

The focus of this chapter is twofold: information dissemination from infrastructure nodes deployed along the roads, the so-called Road-Side Units (RSUs), to passing-by vehicles, and content downloading by vehicular users through nearby RSUs. In particular, in order to ensure good performance for both content dissemination and downloading, the presented study addresses the problem of RSU deployment and reviews previous work that has dealt with such an issue. The RSU deployment problem is then formulated as an optimization problem, where the number of vehicles that come in contact with any RSU is maximized, possibly considering a minimum contact time to be guaranteed. Since such optimization problems turn out to be NP-hard, heuristics are proposed to efficiently approximate the optimal solution. The RSU deployment obtained through such heuristics is then used to investigate the performance of content dissemination and downloading through ns2 simulations. Simulation tests are carried out under various real-world vehicular environments, including a realistic mobility model, and considering that the IEEE 802.11p standard is used at the physical and medium access control layers. The performance obtained in realistic conditions is discussed with respect to the results obtained under the same RSU deployment, but in ideal conditions and protocol message exchange. Based on the obtained results, some useful hints on the network system design are provided.

The development of wireless vehicular networks for cooperative Intelligent Transport Systems (ITS) opened the possibility of launching cooperative applications that can improve vehicle and road safety, passenger’s comfort and efficiency of traffic management. These applications exhibit tight latency and throughput requirements, for example safety critical services such as the Emergency Electronic Brake Light require guaranteed maximum latencies lower than 100 ms, while most infotainment applications require QoS support and data rates higher than 1 Mbit/s. Current wireless communication standards such as IEEE 802.11-2012 amendment 6 and ETSI-G5 have some drawbacks in what concerns their medium access control technique, which is based in CSMA/CA, particularly for high speed and high density environments. To deal with such environments, an infrastructured based TDMA protocol, the Vehicular Flexible Time Triggered protocol was proposed. In this chapter several protocol parameters are quantified, taking in account realistic scenarios and current wireless communication standards, that are applicable in these environments. To deploy such an infrastructured based network in an entire motorway might be expensive, therefore a concept of safety zone is used whenever there is a part of the motorway that is covered by road side units that implement the protocol. A worst case approach is used in order to prove that the V-FTT protocol has a bounded delay in what concerns the time occurred between a safety event detection and the instant of time of its reception by all vehicles travelling in the safety zone. With the exception of the lowest bit rate (3 Mbps), the V-FTT protocol has a guaranteed bounded delay under the maximum allowed latency of the most common safety vehicle applications.

Vehicular ad hoc networks have played a key role in intelligent transportation systems that considerably improve road safety and management. This new technology allows vehicles to communicate and share road information. However, malicious users may inject false emergency alerts into vehicular ad hoc networks, preventing nodes from accessing accurate road information. In order to assure the reliability and trustworthiness of information through the networks, assessing the credibility of nodes has become a critical task in vehicular ad hoc networks. A new scheme for malicious node detection is proposed in this work. Multiple factors are fed into a fuzzy logic model for evaluating the trust for each node. Vehicles are divided into clusters in our approach, and a road side unit manages each cluster. The road side unit assesses the credibility of nodes before accessing vehicular ad hoc networks. The road side unit evicts a malicious node based on trust value. Simulations are used to validate our technique. We demonstrate that our scheme can detect and evict all malicious nodes in the vehicular ad hoc network over time, lowering the ratio of malicious nodes. Furthermore, it has a positive impact on selfish node participation. The scheme increases the success rate of delivered data to the same level as the ideal cases when no selfish node is present.

Intelligent transportation system (ITS) is becoming an important part of our society. Vehicular ad hoc networks (VANETs), as one of the most fundamental technologies in ITS, have attracted great interests in both industry and academia. Due to ever-increasing data demands in VANETs, it is challenging to meet the requirements of ITS, especially for safety-critical applications. Fog computing is an emerging paradigm with the vision of supporting low communication latency, enhancing quality of service, and improving efficiency of network. Meanwhile, collision warning (CW) is critical for enhancing driving safety, which has stringent timing requirement. This work is dedicated to addressing safety issues in VANETs by designing and implementing a fog computing based collision warning system. Distinguishing from conventional cloud-based solutions, where vehicles have to communicate with servers resided in the backbone network via cellular network, the fog computing based system offloads communication and computation workloads to the infrastructures which are closer to end users (i.e., vehicles). In particular, the road-side unit (RSU) with dedicated short range communication (DSRC) interface and local computation unit is acted as the fog node, and it is installed at the road intersection. Then, vehicles approaching to the intersection will periodically report their status including positions, speed, driving direction and acceleration, to the RSU via DSRC. Based on the collected real-time status of surrounding vehicles, a collision prediction algorithm is designed and implemented in the computation unit of the fog node. The warning message will be triggered if potential collision is detected, and it will be transmitted to corresponding vehicles. For performance evaluation, we have implemented the system in realistic VANETs scenario. In addition, we have also implemented a cloud computing based CW system for performance comparison, where the LTE interface is adopted for transmitting messages to the cloud server, where the collision prediction algorithm is executed. Based on the field testing, we have demonstrated the superiority of the fog computing based CW system in terms of enhancing driving safety by providing real-time communication and distribute computation capabilities.

Vehicle ad hoc network is the key technology for a future Internet of vehicles and intelligent transport system. However, involvement of vast number of vehicles in Internet of vehicles limits the performance of vehicle ad hoc network. To tackle this problem, a novel vehicle ad hoc network architecture with two different technologies such as software-defined networking and named-data networking is proposed in this article. In the proposed software-defined networking controlled vehicular named-data networking, IP addressing issue is resolved by named-data networking and global view of the network is attained by software-defined networking. Emergency data dissemination is initiated with packet classification. For packet classification, policy-based bifold classifier is proposed in roadside unit and supported by evolved interest packet. Subsequently, best disseminator selection is carried out by trustworthy weighted graph scheme based on novel weight value, which is computed by considering significant metrics. Content retrieval is accomplished by roadside unit and assisted by a controller. Location of content producer is obtained from a controller and optimal route is selected by roadside unit. Optimal route selection is performed by roadside unit for both content retrieval and vehicle-to-vehicle communication using novel region-based hybrid cuckoo search algorithm. Hybrid algorithm combines cuckoo search and particle swarm optimization algorithm to perform efficient route selection. Involvement of software-defined networking controller supports numerous users by providing a global view of the network, which includes network status and traffic information. Extensive simulation in NS-3 assures better interest satisfaction rate, interest satisfaction delay, forwarder interest packets, average hop count, and gain of scalability in software-defined networking controlled vehicular named-data networking than traditional vehicle ad hoc network.

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.