Showing papers on "Wireless ad hoc network published in 2022"
TL;DR: Li et al. as mentioned in this paper proposed a trust node management method in VANETs, which aims to quantify node credibility as an assessment method and avoid assigning malicious nodes, and the experimental results demonstrate that their proposed method outperforms bassline methods, especially with respect to the packet delivery ratio and security.
Abstract: Vehicular ad hoc networks (VANETs) provide self-organized wireless multihop transmission, where nodes cooperate with each other to support data communication. However, malicious nodes may intercept or discard data packets, which might interfere with the transmission process and cause privacy leakage. We consider historical interaction data of nodes as an important factor of trust. Thus, this paper focuses on the trust node management of VANETs, which aims to quantify node credibility as an assessment method and avoid assigning malicious nodes. First, the integrated trust of each node is proposed, which consists of the direct trust and the recommended trust. The former is dynamically computed by historical interaction records and Bayesian inference considering penalty factors. The latter defines trust by third-party nodes and their reputation. Second, the process of trust calculation and data communication calls for timeliness. Therefore, we introduce a time sliding window and time decay function to ensure that the latest interaction information has a higher weight. We can sensitively identify malicious nodes and make quick responses. Finally, the experimental results demonstrate that our proposed method outperforms bassline methods, especially with respect to the packet delivery ratio and security.
53 citations
TL;DR: In this article , the improved deep convolutional neural network (IDCNN) identifies the malicious nodes and then isolates them into the malicious list box in the Malicious Nodes Detection (MND) phase.
Abstract: Wireless Sensors Networks (WSN) is the self-configured Wireless Ad hoc Networks (WANET) for Internet of Things (IoT) which consists of a huge measure of resource-restrained Sensor Nodes (SN). In WSN, the key parameters are effectual energy utilization and security. The adversary could send false information because of the Malicious Nodes’ (MNs’) presence. Thus, to shun security threats, it is vital to find and isolate those MNs. Consequently, this work proffered a solution for detecting MNs in WSN utilizing every SN's parameters. This work not only regards the security but also rendered energy-efficient data transmission (DT) by means of choosing the Cluster Head (CH) centred on the sensor's residual energy. The Improved Deep Convolutional Neural Network (IDCNN) identifies the MN and then isolates them into the malicious list box in the Malicious Nodes Detection (MND) phase. In the energy-efficient DT phase, the Extended K-Means ( EKM) algorithm clusters the Trusted Nodes (TN), and the t-Distribution based Satin Bowerbird Optimization (t-DSBO) algorithm selects an individual CH for each cluster centred on those nodes’ residual energy. The data of that cluster is transmitted to the Base Station (BS) through the CH. The t-DSBO selects an alternate CH if the current CH loses its energy. The proposed techniques effectively detect the MN and render energy-efficient DT, which is experimentally proved by comparing it with existing techniques.
40 citations
TL;DR: In this article , a scalable distributed neural-network-based adaptive platooning design approach is proposed to achieve secure platooning control in the presence of intermittent denial-of-service (DoS) attacks.
Abstract: This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) communication, is composed of a group of following vehicles subject to unknown heterogeneous nonlinearities and external disturbance inputs, and a leading vehicle subject to unknown nonlinearity and external disturbance as well as an unknown control input. Under such a platoon setting, this article aims to accomplish secure distributed platoon formation tracking with the desired longitudinal spacing and the same velocities and accelerations guided by the leader regardless of the simultaneous presence of nonlinearities, uncertainties, and DoS attacks. First, a new logical data packet processor is developed on each vehicle to identify the intermittent DoS attacks via verifying the time-stamps of the received data packets. Then, a scalable distributed neural-network-based adaptive control design approach is proposed to achieve secure platooning control. It is proved that under the established design procedure, the vehicle state estimation errors and platoon tracking errors can be regulated to reside in small neighborhoods around zero. Finally, comparative simulation studies are provided to substantiate the effectiveness and merits of the proposed control design approach on maintaining the desired platooning performance and attack tolerance.
38 citations
TL;DR: Improvements to the existing cellular network core is examined to support novel use-cases and lower the operation costs of diverse ad hoc deployments to support next-generation high-availability communications.
Abstract: Advances in the fields of networking, broadband communications and demand for high-fidelity low-latency last-mile communications have rendered as-efficient-as-possible relaying methods more necessary than ever. This paper investigates the possibility of the utilization of cellular-enabled drones as aerial base stations in next-generation cellular networks. Flying ad hoc networks (FANETs) acting as clusters of deployable relays for the on-demand extension of broadband connectivity constitute a promising scenario in the domain of next-generation high-availability communications. Matters of mobility, handover efficiency, energy availability, optimal positioning and node localization as well as respective multi-objective optimizations are discussed in detail, with their core ideas defining the structure of the work at hand. This paper examines improvements to the existing cellular network core to support novel use-cases and lower the operation costs of diverse ad hoc deployments.
37 citations
TL;DR: A unique clustering approach is described that identifies the presence of a fire zone in a forest and transfers all sensed data to a base station as soon as feasible via wireless communication, and outperforms all the considered state-of-art algorithms.
Abstract: Forest fires are a significant threat to the ecological system’s stability. Several attempts have been made to detect forest fires using a variety of approaches, including optical fire sensors, and satellite-based technologies, all of which have been unsuccessful. In today’s world, research on flying ad hoc networks (FANETs) is a thriving field and can be used successfully. This paper describes a unique clustering approach that identifies the presence of a fire zone in a forest and transfers all sensed data to a base station as soon as feasible via wireless communication. The fire department takes the required steps to prevent the spread of the fire. It is proposed in this study that an efficient clustering approach be used to deal with routing and energy challenges to extend the lifetime of an unmanned aerial vehicle (UAV) in case of forest fires. Due to the restricted energy and high mobility, this directly impacts the flying duration and routing of FANET nodes. As a result, it is vital to enhance the lifetime of wireless sensor networks (WSNs) to maintain high system availability. Our proposed algorithm EE-SS regulates the energy usage of nodes while taking into account the features of a disaster region and other factors. For firefighting, sensor nodes are placed throughout the forest zone to collect essential data points for identifying forest fires and dividing them into distinct clusters. All of the sensor nodes in the cluster communicate their packets to the base station continually through the cluster head. When FANET nodes communicate with one another, their transmission range is constantly adjusted to meet their operating requirements. This paper examines the existing clustering techniques for forest fire detection approaches restricted to wireless sensor networks and their limitations. Our newly designed algorithm chooses the most optimum cluster heads (CHs) based on their fitness, reducing the routing overhead and increasing the system’s efficiency. Our proposed method results from simulations are compared with the existing approaches such as LEACH, LEACH-C, PSO-HAS, and SEED. The evaluation is carried out concerning overall energy usage, residual energy, the count of live nodes, the network lifetime, and the time it takes to build a cluster compared to other approaches. As a result, our proposed EE-SS algorithm outperforms all the considered state-of-art algorithms.
37 citations
TL;DR: In this paper , the authors focus on UAV security and privacy issues whilst establishing flying ad hoc networks (FANETs) as well as on threats to the Internet of drones (IoD) infrastructure used to provide control and access over the Internet between UAVs and users.
Abstract: Unmanned aerial vehicles (UAVs) are a rapidly evolving technology, and being highly mobile, UAV systems are able to cooperate with each other to accomplish a wide range of different tasks. UAVs can be used in commercial applications, such as goods delivery, as well as in military surveillance. They can also operate in civil domains like search-and-rescue missions, that require multiple UAVs to collect location data as well as transmit video streams. However, the malicious use of UAVs began to emerge in recent years. The frequency of such attacks has been significantly increasing and their impact can have devastating effects. Hence, the relevant industries and standardisation bodies are exploring possibilities for securing UAV systems and networks. Our survey focuses on UAV security and privacy issues whilst establishing flying ad-hoc networks (FANETs) as well as on threats to the Internet of drones (IoD) infrastructure used to provide control and access over the Internet between UAVs and users. The goal of this survey is to categorise the versatile aspects of the UAV threat landscape and develop a classification approach based on different types of connections and nodes in FANETs and IoD. In particular, we categorise security and privacy threats on connections between UAVs, ground control stations, and personal pilot devices. All the most relevant threats and their corresponding defence mechanisms are classified using characteristics of the first four layers of the OSI model. We then analyse the conventional and novel UAV routing protocols, indicating their advantages and disadvantages from the cyber security perspective. To provide a deeper insight, the reviewed defence mechanisms have undergone a thorough examination of their security requirements and objectives such as availability, authentication, authorisation, confidentiality, integrity, privacy, and non-repudiation. Finally, we discuss the open research challenges, the limitations of current UAV standards, and provide possible future directions for research.
36 citations
TL;DR: A novel cryptographic approach incorporated in AODV protocol to identify and eliminate the common attack strategy, called the blackhole attack in VANET, known as Secure A ODV protocol (SAODV).
27 citations
TL;DR: In this article , a Cooperative Routing for Improving Lifetime (CRIL) algorithm is proposed to solve the route detection problem in WANETs, which aims to enhance the network lifetime and minimize the cost of route discovery.
Abstract: In Wireless Ad-hoc Networks (WANET), route detection is the main issue. In the usual route detection method, the sender itself discovers the route to the receiver based on the shortest path. In this path, the sender node does not require knowledge of the in-between nodes, and the sender node transmits the information to the in-between nodes. The in-between nodes transmit the data to the near node that receives it. This procedure will be maintained till the information reaches the receiver node. The main disadvantage of usual route detection is that the node is highly moved; thus, the transmitted data packet will be dropped. A Cooperative Routing for Improving Lifetime (CRIL) in WANET is introduced to solve these issues. This approach aims to enhance the WANET lifetime and minimize the cost of route discovery. This approach uses the fresher encounter algorithm with energy-efficient routing to improve network lifetime. It is a simple algorithm to efficiently discover the routes in WANET.
27 citations
TL;DR: In this paper , a Machine Learning (ML) mechanism that takes advantage of three new features, which are mainly related to the sender position, allowing to enhance the performances of IDS for position falsification attacks is proposed.
Abstract: Cooperative Intelligent Transport Systems (C-ITS) is an advanced technology for road safety and traffic efficiency over Vehicular Ad Hoc Networks (VANETs) allowing vehicles to communicate with other vehicles or infrastructures. The security of VANETs is one of the main concerns in C-ITS because there may be some attacks in such type of network that may endanger the safety of the passengers. Intrusion Detection Systems (IDS) play an important role to protect the vehicular network by detecting misbehaving vehicles. In general, the works in the literature use the same well-known features in a centralized IDS. In this paper, we propose a Machine Learning (ML) mechanism that takes advantage of three new features, which are mainly related to the sender position, allowing to enhance the performances of IDS for position falsification attacks. Besides, it presents a comparison of two different ML methods for classification, i.e. k-Nearest Neighbor (kNN) and Random Forest (RF) that are used to detect malicious vehicles using these features. Finally, Ensemble Learning (EL) which combines different ML methods, in our case kNN and RF, is also carried out to improve the detection performance. An IDS is constructed allowing vehicles to detect misbehavior in a distributed way, while the detection mechanism is trained centrally. The results demonstrate that the proposed mechanism gives better results, in terms of classification performance indicators and computational time, than the best previous approaches on average.
24 citations
TL;DR: The main goal of this work is to investigate the impact of attackers’ strategies to execute MITM assaults in MANETs, such as message-delayed and message-dropped assaults, and to avoid MITM attacks that intercept the communication between legal nodes.
Abstract: Mobile ad hoc networks (MANETs) are being used more and more in a variety of fields, including the environment, energy efficiency, smart transportation, intelligent agriculture, and in Internet of Things (IoT) ecosystems. They are also anticipated to play an increasingly significant role in the future of the Internet due to the strong evolution of wireless technology in recent years. Nevertheless, this inter-node communication is vulnerable to various security attacks such as Man-In-The-Middle (MITM) attacks, which are considered to be the main challenge in MANETs. This happens when a harmful node intercepts data shared by legal nodes. Therefore, the main goal of this work is to investigate the impact of attackers’ strategies to execute MITM assaults in MANETs, such as message-delayed and message-dropped assaults. The output of this work shows that these assaults have a severe impact on legal entities in MANETs as the network experiences a high number of compromised messages as well as high E2ED and PLD. Finally, by using symmetry or asymmetry cryptographies, our proposal will avoid MITM attacks that intercept the communication between legal nodes.
22 citations
TL;DR: In this paper , the authors present a comprehensive review of AI techniques that are currently being explored by various research efforts in the area of VANETs, and discuss the strengths and weaknesses of these proposed AI-based proposed approaches for the VANet environment.
TL;DR: This work demonstrates the insecurity of Ali et al.
Abstract: Vehicular Ad-hoc Network (VANET) is vital for supporting intelligent transport systems, such as traffic data sharing and cooperative processing in the modern city. However, data security and privacy are the critical factors restricting the development. To address these challenges, several certificateless conditional privacy-preserving authentication (CPPA) schemes with anonymity and traceability have been proposed. These schemes avoid complicated certificate management in the PKI framework and key escrow in the ID-based protocol. However, there still exist drawbacks such as computational complexity, high communication cost or security vulnerability. Recently, Ali et al. proposed an efficient certificateless CPPA (CLCPPA) scheme for VANETs, but we have found that this scheme fails to resist a signature forgery attack. To achieve a trade-off between security and efficiency, we first demonstrate the insecurity of Ali et al.’s protocol and then introduce a security-enhanced solution. To show the feasibility and utility of our proposal, we perform a security analysis in the security model. Moreover, we evaluate the performance via comparing it with other existing schemes. From the comparison results, we can find that our scheme is more efficient than prior state-of-art solutions, in terms of signing (improving 66.75%), the verification (improving 33.19%) and bandwidth requirement (reducing 14.75%). Therefore, our proposal is more suitable to be applied in VANETs.
TL;DR: In this paper , the authors proposed a dual weighted trust evaluation technique to establish the truth of consensus, to identify the malicious nodes with no further delay, by considering the decision of each vehicle on finding the trust values.
TL;DR: In this article , a set of network metrics are described to predict behavior of malicious node in wireless network and a malicious node can cause variations in network metrics including packet dropping percentage, throughput, latency, energy consumption, and average queue duration.
Abstract: This paper describes a set of network metrics are helpful to predict behavior of malicious node in wireless network. The Network and internet is the device in which multiple people can communicate with each other through the wired or wireless media. Nowadays, Internet of Things, Mobile, vehicular, and wireless ad hoc networks all merge into one shared network. These networks are often used to send receive confidential data and information. The unauthorized or malicious node misuse these secrete information. With a rise in rogue nodes, network performance will suffer. A rogue node in the network can cause variations in network metrics including the packet dropping percentage, throughput, latency, energy consumption, and average queue duration. This behavior used to identify the malicious node.
TL;DR: The importance of the RSU to the VANET architecture with real-world data incorporating the new 5G standard is analyzed and the future research directions of mRSU are discussed, and the challenges connected to these future trends are explained.
Abstract: The number of vehicles on the road increases daily, causing many fatal accidents and wasting much time for the average commuter every day due to congestion. Vehicular ad hoc networks (VANETs) were introduced to overcome these issues by enabling vehicle-to-vehicle communication and vehicle-to-infrastructure communication. The prime challenge in VANETs is the necessity of very low communication delays, especially for safety-related applications due to the high mobility nature of vehicles. The VANET architecture introduces a network component, the Road Side Unit (RSU), to meet the required delay limitations. Even though the RSU is a critical component in VANETs, as expected, the RSUs were not deployed throughout the world because of their high investment cost. As a solution, the idea of mobile RSU (mRSU) was introduced, and, ever since, several techniques of mRSU deployment strategies have been proposed. In this survey, we first analyze the importance of the RSU to the VANET architecture with real-world data incorporating the new 5G standard. Then, we investigate the research done in the areas of mRSU and exploit the pros and cons of each mRSU deployment strategy. Finally, we also discuss the future research directions of mRSU, and we explain the challenges connected to these future trends.
TL;DR: In this paper , a secure communication architecture for the Internet of Vehicles (IoV) nodes in intelligent transportation through studying the safety of IoV in smart transportation based on Blockchain (BC).
Abstract: The present work aims to improve the communication security of Internet of Vehicles (IoV) nodes in intelligent transportation through studying the safety of IoV in smart transportation based on Blockchain (BC). An IoV DTs model is built by combining big data with Digital Twins (DTs). Then, regarding the current IoV communication security issues, a secure communication architecture for the IoV system is proposed based on the immutable and trackable BC data. Besides, Wasserstein Distance Based Generative Adversarial Network (WaGAN) model constructs the IoV node risk forecast model. Because the WaGAN model calculates the loss function through Wasserstein distance, the learning rate of the model accelerates remarkably. After ten iterations, the loss rate of the WaGAN model is close to zero. Massive in-vehicle devices in IoV are connected simultaneously to the base station, causing network channel congestion. Therefore, a Group Authentication and Privacy-preserving (GAP) scheme is put forward. As users increase during authentication, the GAP scheme performs better than other authentication access schemes. In summary, the Intelligent Transportation System driven by DTs can promote intelligent transportation management. Besides, introducing BC into IoV can improve access control’s accuracy and response efficiency. The research reported here has significant value for improving the security of the information sharing of the IoV.
TL;DR: In this article , the authors proposed to enhance the interactive communication in the network by incorporating the relay nodes between BS and CH in case the CH is out of the range of the BS.
Abstract: Energy efficiency is a crucial parameter for the ad hoc wireless sensor network as it increases the life of a network. In an ad hoc wireless sensor network, every node ingests some part of energy with relaying of the remaining energy over that network. The suggested work is also directed toward elongating the life of the ad hoc wireless sensor network (WSN) achieved by increasing the energy efficiency for interactive communication in a network made up of clusters. In a clustered network, the clustered nodes are chosen randomly resulting in the probability of inconsistent disposition of these cluster heads. All the base stations communicate with the different cluster heads that in turn communicate with the different nodes. In some cases, the base station (BS) communicates with the cluster heads (CHs) with the help of other cluster heads (CHs) if the range of the base station is limited. This concept is called interactive communication within the WSN. The proposed research is to enhance the interactive communication in the network by incorporating the relay nodes between BS and CH in case the CH is out of the range of the BS. The worthwhile choice of the relay nodes, which may be located between base station and cluster head or between two cluster heads, is carried out with reference to interspace and energy. If during the communication within the network the cluster head/s die, the clustering is done again within the network resulting in the choice of new relay node/s. The work proposed is based on recognizing the relay nodes over the network. The analysis shows that the suggested work yields better network life and effective network communication. The present work has been performed on a specific routing protocol called LEACH protocol.
TL;DR: ICDRP-F-SDVN as discussed by the authors uses fog computing and SDN to overcome the drawbacks of traditional VANETs routing protocols, which is a dual-phase protocol with a 90% packet delivery ratio.
TL;DR: In this article , the authors present a survey of the existing P2P approaches in the context of VANETs including a comprehensive survey of various problems related to data sharing in VANet using P2Pe techniques, along with their proposed solutions from the perspective of data access, information lookup, routing, and message management.
TL;DR: There are several methodologies addressed in this work such as anonymous batch authentication in FANET which helps to authenticate a large group of drones at the same time, thus reducing the computational overhead and proves to be more efficient.
Abstract: As there has been an advancement in avionic systems in recent years, the enactment of unmanned aerial vehicles (UAV) has upgraded. As compared to a single UAV system, multiple UAV systems can perform operations more inexpensively and efficiently. As a result, new technologies between user/control station and UAVs have been developed. FANET (Flying Ad-Hoc Network) is a subset of the MANET (Mobile Ad-Hoc Network) that includes UAVs. UAVs, simply called drones, are used for collecting sensitive data in real time. The security and privacy of these data are of priority importance. Therefore, to overcome the privacy and security threats problem and to make communication between the UAV and the user effective, a competent anonymous mutual authentication scheme is proposed in this work. There are several methodologies addressed in this work such as anonymous batch authentication in FANET which helps to authenticate a large group of drones at the same time, thus reducing the computational overhead. In addition, the integrity preservation technique helps to avoid message alteration during transmission. Moreover, the security investigation section discusses the resistance of the proposed work against different types of possible attacks. Finally, the proposed work is related to the prevailing schemes in terms of communication and computational cost and proves to be more efficient.
01 Jan 2022
TL;DR: In this paper , the SVM-CV2X-M4 system achieves an accuracy of 99.6% in the k-fold model with different values of k, and the results show that the proposed system allows vehicles to choose the optimal route and is highly convenient for users.
Abstract: Vehicular ad-hoc networks (VANETs) are mobile networks that use and transfer data with vehicles as the network nodes. Thus, VANETs are essentially mobile ad-hoc networks (MANETs). They allow all the nodes to communicate and connect with one another. One of the main requirements in a VANET is to provide self-decision capability to the vehicles. Cognitive memory, which stores all the previous routes, is used by the vehicles to choose the optimal route. In networks, communication is crucial. In cellular-based vehicle-to-everything (CV2X) communication, vital information is shared using the cooperative awareness message (CAM) that is broadcast by each vehicle. Resources are allocated in a distributed manner, which is known as Mode 4 communication. The support vector machine (SVM) algorithm is used in the SVM-CV2X-M4 system proposed in this study. The k-fold model with different values of k is used to evaluate the accuracy of the SVM-CV2X-M4 system. The results show that the proposed system achieves an accuracy of 99.6%. Thus, the proposed system allows vehicles to choose the optimal route and is highly convenient for users.
01 Jan 2022
TL;DR: A comprehensive survey on the recent advancements in the clustering schemes for vehicular networks is presented in this article, where the authors take a holistic approach to classify the algorithms by focusing on, (i) the objective of clustering mechanisms (i.e., reliability, scalability, stability, routing overhead, and delay), (ii) general-purpose clustering algorithms, (iii) application-based (i., QoS, MAC, security, etc.) clustering, and iv) technology-based clustering (machine learning-based, nature-inspired, fuzzy logic-
Abstract: Vehicular networks are on the verge of deployment, thanks to the advancements in computation and communication technologies. This breed of ad hoc networks leverages vehicles as nodes with Vehicle-to-anything (V2X) communication paradigm. Clustering is considered one of the most important techniques used to enhance network stability, reliability, and scalability. Furthermore, clustering employs bandwidth optimization by reducing the overhead and transmission delay and helps in mitigating the hidden node problem. To date, extensive research has been done to address clustering issues in vehicular networks, and several surveys have also been published in the literature. However, a holistic approach towards clustering in vehicular networks is still lacking. In this regard, we conduct a comprehensive survey on the recent advancements in the clustering schemes for vehicular networks. We take a holistic approach to classify the algorithms by focusing on, (i) the objective of clustering mechanisms (i.e., reliability, scalability, stability, routing overhead, and delay), (ii) general-purpose clustering algorithms, (iii) application-based (i.e., QoS, MAC, security, etc.) clustering, and iv) technology-based clustering (machine learning-based, nature-inspired, fuzzy logic-based and software-defined networking-based clustering). We investigate the existing clustering mechanisms keeping in mind the factors such as cluster formation, maintenance, and management. Additionally, we present a comprehensive set of parameters for selecting cluster heads and the role of enabling technologies for cluster maintenance. Finally, we identify future research trends in clustering techniques for vehicular networks and their various breeds. This survey will act as a one-stop shop for the researchers, practitioners, and system designers to select the right clustering mechanism for their applications, services, or for their research. As a result of this survey, we can see that clustering is heavily dependent on the underlying application, context, environment, and communication paradigm. Furthermore, clustering in vehicular networks can greatly benefit from enabling technologies such as artificial intelligence.
TL;DR: A simple reputation-based scheme is proposed which uses the consumption and contribution information for selfish node detection and cooperation enforcement and outperforms the benchmark scheme in terms of NRL, routing load, PDF, and packet drop in the presence of malicious and selfish attacks.
Abstract: A mobile ad hoc network (MANET) is a group of nodes constituting a network of mobile nodes without predefined and pre-established architecture where mobile nodes can communicate without any dedicated access points or base stations. In MANETs, a node may act as a host as well as a router. Nodes in the network can send and receive packets through intermediate nodes. However, the existence of malicious and selfish nodes in MANETs severely degrades network performance. The identification of such nodes in the network and their isolation from the network is a challenging problem. Therefore, in this paper, a simple reputation-based scheme is proposed which uses the consumption and contribution information for selfish node detection and cooperation enforcement. Nodes failing to cooperate are detached from the network to save resources of other nodes with good reputation. The simulation results show that our proposed scheme outperforms the benchmark scheme in terms of NRL (normalized routing load), PDF (packet delivery fraction), and packet drop in the presence of malicious and selfish attacks. Furthermore, our scheme identifies the selfish nodes quickly and accurately as compared to the benchmark scheme.
TL;DR: Wang et al. as discussed by the authors proposed a multidomain vehicular authentication architecture by introducing blockchain technique to build distributed trust and share cross-domain information among multiple administrative domains to guarantee the anonymity and traceability.
Abstract: Vehicular ad-hoc network enhances driving safety and enables various intelligent transportation applications by adopting the revolutionary vehicular wireless communication technology. This has attracted a lot of attentions from both academia and industry in recent years. Given the sophistication of vehicular manufacturing and the heterogeneity of intelligent transport terminals, performing vehicular authentication is of great importance. The existing schemes have largely considered vehicle security and authentication within a single administrative domain, which lacks supervision of the authority and entity in the intelligent transportation system. In this article, we propose a multidomain vehicular authentication architecture by introducing blockchain technique to build distributed trust and share cross-domain information among multiple administrative domains. To guarantee the anonymity and traceability, a pseudonym-based privacy-preserving authentication method is proposed. Specifically, considering the supervision of authority and the resilience to key escrow, we design a two-phase pseudonym distribution mechanism with the assistance of a roadside unit (RSU) proxy. We conduct in-depth security analysis by comparing with existing works and deploy experiments to show the efficiency and feasibility of the proposed scheme in the multidomain scenario.
01 Jan 2022
TL;DR: This research study suggested the important metrics be concentrated on designing the efficient routing protocol for Flying Ad Hoc Networks and on improving the quality of services.
Abstract: Flying Ad Hoc Network is derived from the mobile ad hoc network and it consists of unmanned aerial vehicles (UAV) for high-speed communication. Flying Ad Hoc Network has high mobility, and the users can communicate without the help of human intervention. Due to high mobility in FANET, network performance is to be concentrated more. Designing a routing protocol is the most important metric for continuous monitoring, analyzing the network performance, and improve efficient network communication. Design of routing protocol should fulfill the important criteria like neighbor nodes selection, shortest path, traffic control, high scalability, high reliability, high data delivery, low drop rate, lesser delay, and high throughput. Due to the high speed in FANET, routing protocols are to be focused on the improvement of network performance and quality of services. This research work studies the detailed review of suitable routing protocols for Flying Ad hoc Networks and discussed the possible outcomes of the different routing strategies such as source-initiated data-centric, table-driven, hybrid, multipath, location-aware, multicast, geographical multicast, power-aware, and energy-aware. This research study suggested the important metrics be concentrated on designing the efficient routing protocol for Flying Ad Hoc Networks and on improving the quality of services.
TL;DR: A comprehensive survey of available TCAs for FANET, and a novel taxonomy of TCAs based on the flying ad hoc network (FANET) topology architectures and underlying mathematical models are provided in this article .
TL;DR: This paper provides a thorough analysis of the influence of using the different SUMO’s traffic demand generation tools on mobility and node connectivity and proposes an automatized tool that facilitates researchers the generation of synthetic traffic based on real data.
TL;DR: Wang et al. as mentioned in this paper proposed a Sybil attack detection scheme using proofs of work and location, where each road side unit issues a signed time-stamped tag as a proof for the vehicle's anonymous location.
Abstract: Vehicular Ad Hoc Networks (VANETs) have the potential to enable the next-generation Intelligent Transportation Systems (ITS). In ITS, data contributed by vehicles can build a spatio-temporal view of traffic statistics, which can improve road safety and reduce slow traffic and jams. To preserve drivers’ privacy, vehicles should use multiple pseudonyms instead of only one identity. However, vehicles may exploit this abundance of pseudonyms and launch Sybil attacks by pretending to be multiple vehicles. Then, these Sybil (or fake) vehicles report false data, e.g., to create fake congestion or pollute traffic management data. In this article, we propose a Sybil attack detection scheme using proofs of work and location. The idea is that each road side unit (RSU) issues a signed time-stamped tag as a proof for the vehicle’s anonymous location. Proofs sent from multiple consecutive RSUs are used to create a trajectory which is used as vehicle anonymous identity. Also, contributions from one RSU are not enough to create trajectories, rather the contributions of several RSUs are needed. By this way, attackers need to compromise an infeasible number of RSUs to create fake trajectories. Moreover, upon receiving the proof of location from an RSU, the vehicle should solve a computational puzzle by running proof of work (PoW) algorithm. Then, it should provide a valid solution (proof of work) to the next RSU before it can obtain a proof of location. Using the PoW can prevent the vehicles from creating multiple trajectories in case of low-dense RSUs. To report an event, the vehicle has to send the latest trajectory to an event manager. Then, the event manager uses a matching technique to identify the trajectories sent from Sybil vehicles. The scheme depends on the fact that the Sybil trajectories are bounded physically to one vehicle, and therefore, their trajectories should overlap. Extensive experiments and simulations demonstrate that our scheme achieves high detection rate of Sybil attacks with low false negative and acceptable communication and computation overhead.