Recent Advances in Machine-Learning Driven Intrusion Detection in Transportation: Survey

Vehicular ad-hoc network (VANET) technology enables communication between vehicles, or vehicles and road-side units (RSUs) through wireless communication devices installed on the vehicles. One of the most important goals of VANETs is providing safety applications for passengers. In addition, VANETs provide comfort applications to users. Guaranteeing a reliable and stable routing protocol over VANETs is a very important step. The proposed research attempts to improve routing protocols that decrease the end-to-end delay to suit VANET communication characteristics. In addition, it proposes analysis of the end-to-end delay probability distribution. More specifically, we derive a closed-form expression for the probability distribution of the re-healing delay in a VANET conditioned on the distance between two VANET clusters. Furthermore, we propose a closed-form expression for the probability distribution of the unconditional re-healing delay. Moreover, we develop a mathematical model to calculate the probability distribution of the end-to-end delay. On the other hand, using Unmanned Aerial Vehicles (UAVs) or drones in wireless communications and Vehicular Ad-hoc Networks (VANETs) has started to attract attention. We propose a routing protocol that uses infrastructure drones for boosting VANET communications to achieve a minimum vehicle-to-drone packet delivery delay. In addition, we propose a closed-form expression for the probability distribution of the vehicle-to-drone packet delivery delay on a two-way highway. Moreover, based on that closed-form expression, we can calculate the minimum drone density (maximum separation distance between two adjacent drones) that stochastically limits the worst case of the vehicle-to-drone packet delivery delay. Furthermore, we propose a drones-active service (DAS) that is added to the location service in a VANET. This service dynamically and periodically obtains the required number of active drones based on the current highway connectivity state by obtaining the maximum distance between each two adjacent drones while satisfying a probabilistic constraint for vehicle-todrone packet delivery delay. Our analysis focuses on two-way highway VANET networks with low vehicular density. The simulation results show the accuracy of our analysis and reflect the relation between the drone density, vehicular density and speed, other VANET parameters, and the vehicle-to-drone packet delivery delay. In addition, we propose a new routing protocol called multi-copy intersection-based routing (MCIR) for vehicular ad-hoc networks (VANETs) in urban areas. MCIR is an intersectionbased routing protocol that forwards multiple copies of the packets in different road segments. Moreover, it is a beacon-less routing protocol with a carry-and-forward strategy. We show via simulation that the MCIR protocol is superior to other existing routing protocols, especially in low vehicular density scenarios. The results show that MCIR achieves a shorter end-to-end delay and a higher packet delivery ratio in urban VANET communications.

A vehicular ad hoc network (VANET) is a special kind of mobile ad hoc networks (MANET) that supports cooperative driving among communicating cars on the roads. There are several technologies involved in implementation of wireless communication in VANETs. These technologies include 3G cellular systems, long-term evolution (LTE), LTE Advanced, IEEE 802.16, and IEEE 802.11. This chapter focuses on 802.11-based wireless communication in VANETs. It reviews some presented methods for vehicle movement path prediction, and explains some algorithms are explained for performance improvement in opportunistic networks based on the predicted vehicle movements. The chapter considers the fact that communication in VANETs can be infrastructure-based or infrastructureless. It also reviews some methods to apply the predicted vehicles' position for improving communication in infrastructure-based and infrastructureless VANETs, respectively. Opportunistic routing algorithms can be classified according to their dependency on roadside infrastructure. The chapter presents the taxonomy of opportunistic routing in VANETs.

Vehicular Ad hoc Networks (VANETs) that are considered as a subset of Mobile Ad hoc Networks (MANETs) can be applied in the field of transportation especially in Intelligent Transportation Systems (ITS). The routing process in these networks is a challenging task due to rapid topology changes, high vehicle mobility and frequent disconnection of links. Therefore, developing an efficient routing protocol that satisfies restriction of delay and minimum overhead is faced with many difficulties and limitations. Also, the detection of malicious vehicles is a significant task in VANETs. To address these issues, using Unmanned Aerial Vehicles (UAVs) can be helpful to cope with these limitations. In this paper, operation of UAVs in ad hoc mode and their cooperation with vehicles in VANETs are studied to help in the process of routing and detection of malicious vehicles. A routing protocol named VRU is proposed that includes two distinct ways of routing of data: (1) delivering packets of data between vehicles with the help of UAVs using a protocol named VRU_vu, and (2) routing packet of data between UAVs using a protocol named VRU_u. The NS-2.35 simulator under Linux Ubuntu 12.04 is utilized in order to appraise the performance of VRU routing components in an urban scenario. Also, VanetMobiSim generator of mobility and MobiSim are used to produce the motions of vehicles and to produce the motions of UAVs, respectively. The performance analysis displays that VRU protocol can improve the packet delivery ratio by 16% and detection ratio by 7% compared to other reviewed routing protocol. Also, VRU protocol decreases end-to-end delay by an average of 13% and overhead by 40%.

Vehicular ad hoc network (VANET) plays a vital role in the intelligent transportation system (ITS). When a vehicle receives a message through network, the CRL (certificate revocation list) checking process will operate before certificate and signature verification. After successful authentication, a CRL list is created based on authentication. This CRL is used to verify whether a vehicle node can be permitted for communication in the VANET network. But when using CRL, a huge amount of storage space and checking time is needed. So we proposed a method without the CRL list. It mentions a key management list to overcome large storage space and checking time. Even it reduced the access delay. For access permission we can do an authentication system based digital novel signature authentication (DNSA) for each vehicle in the VANET with the RSU unit or with other participant node vehicles in the communication as per the topology. We can perform an efficient and secured communication in VANET.

Intelligent Transportation System (ITS) employ Vehicular Ad Hoc Network (VANET) to increase road safety and decrease thenumber of accidents. VANET uses Dedicated Short-Range Communications (DSRC) to allow drivers to obtain reasonable awareness of surrounding vehicles. VANET reliability is affected by any degradation in the communication channel or any lack of exchanged information between vehicles. Moreover, it is vulnerable to a wide range of malicious attacks due to its nature. Such issues might cause a complete failure in VANET services and hence cause accidents, injuries, or death. Thus, VANET reliability and security are very critical. This paper discusses briefly different types of malicious attacks in VANET and some of their detection techniques. It gives more attention to position falsification attack as it has a severe impact on different VANET services. Furthermore, it explores previously proposed detection approaches for this attack using either traditional or machine learning techniques. Finally, attention will be drawn to unresolved challenges and potential future research directions.

With the proliferation of vehicular technology, modern vehicles are fortified with ever more electronic maneuvers. This advancement ratifies the evolution of Intelligent Transportation Systems (ITS)to provide services like shared travel, smart driving, on-the-go Internet, etc. As a traditional application of ITS, a Vehicular Ad hoc Network (VANET) enables smart communication between vehicle nodes and network infrastructures to provide various expedient services such as road safety, data sharing, traffic management, parking assistance, entertainment, route recommendation, mobile payment, and even cloud applications. The high-speed mobile nodes (vehicles) in VANET perform very differently from other wireless communication networks and have a set of distinct features such as frequent link disconnection, highly dynamic topology, limited coverage area, and heterogeneous system architecture that may affect the performance and service quality of the VANET significantly. With this motivation, this work attempts to develop distributed cooperative cluster-based IDS to identify potential cyberattacks in VANET effectively. Firstly, this work develops a stable and reliable clustering method named Fuzzy Logic-based Clustering (FLC) to create a collaborative and reliable communication environment. A new fuzzy logic-based CH node selection algorithm is also developed based on node degree, average velocity difference, and relative velocity of the vehicle to create a more robust clustering structure with minimum cost in VANET

Vehicular ad hoc networks (VANETs) present an intriguing platform for several applications on e.g., intelligent transportation system (ITS) and infotainment applications aspire to be the main pattern of communication among vehicles while travelling. This can significantly impact on the amount of data exchanged by vehicles, increasing the contention on communication links and thus, degrading the quality of service of these applications. So, discrimination of data becomes imperative and forwarding critical information on suitable routes becomes decisive. Hence, a quality of service (QoS)-driven mechanism is needed to handle and assign network resources according to the stringent application data traffic demands. But, VANETs high node mobility and frequent link failure, stuck a big challenge in implementing an effective policy to meet and enforce these QoS requirements. A promising way to tackle this issue is to enforce QoS at the network layer, since it is the crucial point in VANETs’ communication. So, over the years, many QoS-aware routing protocols were specifically conceived for VANETs. In this paper, we present a comprehensive survey of QoS-aware routing protocols in VANETs’ literature. We examined the protocols based on their ability to support ITS infotainment services, their multi-constraint path problem (MCP), protocol’s functionality and weakness, objectives and design challenges. This way, we outline future directions for VANETs QoS-aware protocol research.

Due to the high mobility of on-board units (OBUs) and the large-scale network topology frequency hopping-based anti-jamming techniques are not applicable in vehicular ad hoc networks (VANETs). In this paper, to improve the communication performance of VANETs against smart jamming, unmanned aerial vehicles (UAVs) are used. These unmanned aerial vehicles observe the ongoing OBU and UAV communication status and induce the UAV to use a specific relay strategy. The UAV relays the OBU message to another roadside unit (RSU) with a better radio transmission condition if the serving RSU is heavily jammed or interfered. The interactions between a UAV and a smart jammer are formulated using an anti-jamming UAV relay game. The UAV decides whether or not to relay the OBU message to another RSU based on the relay game, the jammer observes the UAV and the VANET strategy it chooses the jamming power accordingly. The proposed relay strategy can reduce the bit-error rate of the OBU message efficiently and increasing the benefit of the VANET Using Q-learning analysis.

Intelligent Transportation Systems (ITS) is an integrated approach being developed to exchange relevant information to increase the safety and efficiency of the road transportation systems. Vehicular Ad hoc Network (VANET), a variant of mobile ad hoc networks (MANET), is a core component of ITS. Performance of this smart ITS mainly owes to the design of efficient routing protocols in VANETs. Distinct features of VANETs like unsteady connectivity, high mobility and partitioning of the network have made routing of the information in VANETs difficult and challenging, hence dictating the development of efficient routing protocols. The computation of the best route measures the performance of communication whereas routing protocols takes care of communication & routing of the data. Provision of smart communication, necessitates the analysis of routing protocols in VANET. Accordingly in this paper we have reviewed various types of existing routing protocols in VANET, listing their advantages and disadvantages. Lastly possible inclinations of forthcoming research linked to VANET routing are discussed.

Wireless communication is an essential technology to unlock the full potential of unmanned aerial vehicles (UAVs) in numerous applications and has thus received unprecedented attention recently. Although technologies such as direct link, WiFi, and satellite communications are still useful in some remote scenarios where cellular services are unavailable, it is believed that exploiting the thriving 5G and beyond cellular networks to support UAV communications is the most promising and cost-effective approach, especially when the number of UAVs grows dramatically. On the one hand, to guarantee safe and efficient flight operations of multiple UAVs, it is of paramount importance to provide secure and ultra-reliable communication links between the UAVs and their ground pilots or control stations for conveying command and control signals, especially in beyond-visual-line-of-sight (BVLOS) scenarios. On the other hand, because of advances in communication equipment miniaturization as well as UAV manufacturing, mounting compact and lightweight base stations (BSs) or relays on UAVs becomes increasingly feasible. This has led to two promising research paradigms for UAV communications, namely, UAV-assisted cellular communications and cellular-connected UAVs, where UAVs are integrated into cellular networks as aerial communication platforms and aerial users, respectively. As such, integrating UAVs into cellular networks is believed to be a win-win technology for both UAV-related industries and cellular network operators, which not only creates plenty of new business opportunities but also benefits the communication performance of 3-D wireless networks. In addition, UAV related sensing and computing are also helpful for achieving efficient and reliable communication (e.g., in avoiding coverage holes) as well as smart UAV coordination, positioning, and trajectory design. However, 5G and beyond wireless networks with UAVs significantly differs from traditional communication systems, because of the high altitude and high maneuverability of UAVs, the unique UAV-ground channels, the diversified quality of service (QoS) requirements for downlink command and control (C&C) and uplink mission-related data transmission, the stringent constraints imposed by the size, weight, and power (SWAP) limitations of UAVs, as well as the new design degrees of freedom enabled by joint UAV mobility control and communication resource allocation.

Intelligent transportation system (ITS) applications may rely on the reliable infrastructure that vehicular ad hoc networks (VANETs) offer. Roadside units (RSUs) are the main component of vehicle-to-vehicle and vehicle-to-infrastructure links in VANET communication. When cognitive radio (CR) VANET investigations were analysed, two major performance problems were found: low connection stability because of the high vehicle movement and excessive energy consumption. We suggest a fresh strategy to deal with these issues: Mobility and Link Reliability Estimation Using CSS AND ML CR-VANETs, known as MLRECSS CR-VANET. MLRECSS CR-VANET consists of four main components: CR-VANET construction, Cooperative spectrum Sensing model, Speed-based mobility prediction, link-based multipath routing. First, we create CSS-based CR-VANETs to examine and address issues with power consumption and spectrum scarcity in VANETs. Vehicle speed forecasts and fluctuations are assessed via mobility prediction. Lastly, routing is made reliable and effective by utilizing the machine learning and ad hoc on-demand multipath distance vector (AOMDV) routing protocol in combination with link stability based multipath routing (LSMR). MLRECSSCR-VANET technique outperforms the previous methods by 3.69% in terms of packet delivery ratio,7.21% in terms of residual energy, 6.09% in terms of throughput, 8.33% in terms of residual node speed and 13.97% in terms of energy efficiency. Comparing it to more contemporary efforts like LMCCR-VANET, SCCR-VANET, CFCR-VANET, and MMCR-VANET, it shows improved energy efficiency, delivery rates, decreased energy consumption, end-to-end latency, and routing overhead.

A type of ad hoc network formed among moving vehicles that come in one another’s radio transmission range is called Vehicular Ad Hoc Network (VANET). VANET may be deployed using three architectures: pure ad hoc, WLAN and hybrid. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) are the two modes in VANET used for communication among vehicles. These features not only distinguish a VANET from other ad hoc networks but also make these networks more exposed to attacks and increase their complexity. These networks being the primary mechanism for communication in VANETs, appropriate and timely delivery of information is of prime importance. Due to the existence of various vehicular traffic scenarios, a single category of routing protocols is not sufficient for the VANETs. Therefore, various categories of routing protocols have been tailored to meet specific kinds of routing requirements in this framework. Most significant ones are ad hoc/topology-based, position-based, geocast-based, cluster-based, broadcast-based protocols. There exist a number of attacks that apart from affecting various other parameters also affect the routing protocols in these VANETs. Most of these attacks may be launched in all the above-mentioned three architectures. But, one of the most dangerous attacks is the Sybil attack that may be initiated in pure ad hoc deployment of VANET where vehicles communicate with one another in one to one manner using carry forward approach. In this paper, with the help of illustrative example for each of the five categories of routing protocols, we show how Sybil attack affects these protocols. Considering the ad hoc scenarios in VANETs, we also discuss a prevention mechanism for the Sybil attack briefly.

Over the past few years, there has been significant research interest in field of vehicular ad hoc networks (VANETs). Wireless communication over VANETs supports vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) communication. Such innovation in wireless communication has improved our daily lives through road safety, comfort driving, traffic efficiency. As special version of MANETs, VANETs bring several new challenges including routing and security challenges in data communication due to characteristics of high mobility, dynamic topology. Therefore, academia and the auto mobile industry are taking interest in several ongoing research projects to establish VANETs. The work presented here focuses on communication in VANETs with their routing and security challenges along with major application of VANETs in several areas.

The swift improvement of wireless communication technology has aided the creation of vehicular ad hoc networks (VANETs) as a revolutionary option for the realization of intelligent transportation systems (ITSs). VANETs facilitate seamless communication between vehicles and infrastructure (V2I) and among the vehicles themselves (V2V). These networks can enhance safety and traffic control while providing various infotainment options. To ensure stable and efficient communication in highly dynamic and quickly changing vehicular contexts, effective data packet routing is a crucial component of VANETs. This survey delves further into the VANET routing algorithms for ITS. The study aims to evaluate the effectiveness and acceptability of various routing protocols suggested for VANETs while considering their unique requirements and difficulties. The review covers ad hoc on‐demand distance vector (AODV) and dynamic source routing (DSR), as well as more current strategies designed specifically for VANETs, such as geographic routing, cluster‐based routing, and hybrid routing protocols. The review assesses the routing algorithms based on several vital parameters, including packet delivery ratio (PDR), end‐to‐end delay, throughput, network overhead, scalability, and robustness. This detailed assessment supports aspiring researchers in acquiring a better knowledge of the benefits and drawbacks of the routing algorithms currently used in VANETs.

Vehicular ad hoc networks (VANETs) are emerging to serve various types of applications for serving smart cities and intelligent transportation systems. There are several challenging factors for ensuring reliable and stable VANETs communications. VANETs clustering is essential functionality to serve routing protocols and in enable reliable VANETs. Clustering algorithms for VANETs operate in decentralized mode, which requires incorporating additional stages before deciding the clustering decisions and might create suboptimality due to the local nature of the decentralized approach. In addition, the challenging architecture of the road environment can cause confusing clustering decisions. This problem becomes more challenging due to the evolving nature of clusters in VANETs in general and in 3D VANETs in particular. This paper tackles the problem of 3D VANETs using a centralized clustering model based on the developed Cauchy density model. The development has included a traffic generation model, mobility model for generating driving behavior, and an algorithm for enabling modeling of road curvature based on an adjacency list that defines the road’s points that define a straight-line segment. In addition, a clustering algorithm that defines mobility vector and uses Cauchy-based density for enabling adding vehicles to their respective clusters. For evaluation, conducted scenarios in three locations with 3D architecture are considered, and a comparison with benchmarks shows the superiority of our developed over the benchmarks with an improvement percentage of 1%, 10%, and 3% for average cluster head duration, average cluster member duration, and clustering efficiency respectively.