Safety-related Messages Research Articles

L-TCM: A Lightweight Privacy-Preserving Traffic Condition Monitoring Scheme With Source Authentication in Cloud-Assisted VANETs

In vehicular ad hoc networks (VANETs), the vehicle constantly collects traffic condition messages and uploads them to the traffic management department (TMD) for traffic analysis. Traffic condition messages usually consist of vehicle-related information as well as safety-related messages. Vehicle-related information usually contains vehicles' privacy, which cannot be broadcasted. At the same time, the safety-related message does not contain the privacy of vehicles and can be broadcasted in VANETs to ease traffic congestion. However, transmitting two types of messages separately consumes numerous computation and communication costs, which is not realistic for resource-limited vehicles. In this article, we propose a lightweight privacy-preserving traffic condition monitoring (L-TCM) scheme, where the sanitizable signature is used to enable the vehicle to broadcast safety-related messages and upload traffic condition messages by sending one message. In addition, searchable encryption is used to help the TMD retrieve traffic condition messages stored in the cloud server. Security analysis demonstrates that L-TCM satisfies security goals in VANETs. Besides, the performance of L-TCM concerning computation and communication costs makes it appropriate for traffic condition monitoring.

Efficient Conditional Privacy-Preserving Authentication Scheme for Safety Warning System in Edge-Assisted Internet of Things

With the advent of smart cities, the significance of the Internet of Things (IoT) is gaining greater prominence. At the same time, the safety early warning system in the IoT has a significant impact on real-time monitoring and the response to potential risks. Despite the advancements made in edge-assisted IoT deployments, several challenges and constraints persist. Given the potential threat to life posed by safety-related messages, ensuring the authenticity of messages in the edge-assisted IoT safety warning system is crucial. However, considering the identity privacy of devices participating in the edge-assisted Internet of Things system, directly verifying the identity of the sending device is undesirable. To address this issue, in this work, we design a linkable group signature scheme that allows devices to anonymously send safety-related messages to edge nodes, defending against Sybil attacks while ensuring the traceability of malicious device identities. Then, we present a high-efficiency conditional privacy-preserving authentication (CPPA) scheme based on the designed group signatures for the safety warning system in edge-assisted IoT. This scheme effectively protects device identity privacy while providing a reliable authentication mechanism to ensure the credibility and traceability of alert messages. The proposed scheme contributes to the field of safety warning systems in the context of edge-assisted IoT, providing a robust solution for privacy preservation and authentication.

Hybrid routing for safety data with intermittent V2I connectivity

V2I communications complement V2V safety applications by dealing with emergency situations such as crash scenarios that the V2V program cannot handle or that could be addressed more effectively. However, depending on the deployed infrastructure, we can distinguish between three situations regarding allowed communications: infrastructure-based, infrastructure-less and intermittent infrastructure. We will focus in vehicular networks with an intermittent connectivity, where the unavailability of direct communication with RSUs poses huge problems, especially when vehicles have to send safety-related messages to the infrastructure. In fact, a scattered vehicular infrastructure leads to non-homogeneous coverage, especially in highway scenarios extending over long distances; it is very expensive to set up an infrastructure across the whole road. Our objective is to address the challenges related to safety information forwarding towards the RSU in such networks by enabling vehicles to make an optimal forwarding decision based on contextual information relative to the infrastructure and the neighbourhood. In this work, we present HyRSIC (Hybrid Routing for Safety data with Intermittent V2I Connectivity), a routing approach, combining geographical and topological routing, proposed to deal with data forwarding in intermittent infrastructure-based networks. We conducted an in-depth evaluation from three different perspectives: scalability, reliability and efficiency. The results show that HyRSIC is able to scale quickly and adapt promptly to density and speed variations. Compared to GPSR and its variant ILTS+GPSR, HyRSIC offers the best packet delivery ratio for sparse networks, 12-27% higher, and the lowest End-to-End delivery delay, 25-50% less.

A Service-Aware Latency-Relaxed uRLLC Multiplexing Strategy within eMBB Traffic for Hyperloop Communications

The train-to-ground communications for Hyperloop encounter numerous challenges compared to the previous systems as a result of ultrahigh velocity, metal confined tube, severe penetration attenuation, frequent handover, etc. Ultrareliable low latency communication (uRLLC) services are extremely pivotal to the operation of Hyperloops since they are responsible for the transmission of safety-related messages like train control system (TCS) information. Furthermore, the sporadic generated uRLLC traffic is strictly latency-sensitive and requires stringent transmission reliability, which is usually realized by multiplexing with the enhanced mobile broadband (eMBB) traffic when coexisting with heterogeneous traffic. Different from current multiplexing schemes which handle all uRLLC traffic indiscriminately, we focus on the detailed demands of different uRLLC services for Hyperloops, including the end-to-end transmission latency and bit error rate (BER). Then, we classify the safety-related uRLLC traffic into 5 levels according to the metrics and relax the multiplexing latency properly. On this basis, an optimization problem incorporating minimizing uRLLC power and maximizing the eMBB throughput is formulated. Then, a particle swarm optimization (PSO) algorithm is proposed to cope with this nondeterministic polynomial- (NP-) hard problem. Simulation results imply that our proposed service-aware latency-relaxed concept enables a flexible multiplexing of the uRLLC traffic, and the proposed PSO algorithm can obtain the suboptimal solutions with the constraints of BER and time-frequency range, which can cater to the demands of uRLLC and improve the passengers’ in-journey communication quality of services to some degree.

Conditional Anonymous Authentication With Abuse-Resistant Tracing and Distributed Trust for Internet of Vehicles

The Internet of Vehicles (IoV) was proposed as an approach to enable intelligent traffic management and enhance road safety. In order to achieve the intended objective of improving road safety, vehicles are required to constantly broadcast messages to the traffic management infrastructure as well as to other vehicles in the vicinity. Cybersecurity protection of the IoV system is critical as security attacks on IoV and safety-related messages could be life-threatening. In this connection, it is essential to ensure the authenticity of IoV messages. Whereas, from the angle of privacy protection, it is undesirable to directly authenticate the identities of vehicles that send the IoV messages. To cope with these conflicting requirements, researchers proposed the notion of conditional anonymous authentication, which aims to authenticate message senders anonymously. When necessary, a trusted third party, named tracer, will be allowed to reveal the true identities of malicious vehicles who sent fake messages. However, existing security techniques including pseudonyms and group signatures typically assume that the tracer is trusted. This assumption may not be desirable in situations when a curious tracer may reveal the identities of honest vehicles in the IoV system. To address this challenge, this paper proposes a privacy-preserving authentication scheme with abuse-resistant tracing. Compared with existing conditional anonymous authentication schemes, our scheme prevents a single tracer from revealing the identity of vehicles. Besides, the tracing key is generated in a distributed manner, and hence no single authority in the system can reveal the true identity of a vehicle.

Security: Intrusion Prevention System Using Deep Learning on the Internet of Vehicles

Internet of vehicles supports to transfer of safety-related messages, which help to mitigate road accidents. Internet of vehicles allows vehicle to cooperative communicate, share position and speed data among vehicles and road side units. The vehicular network become prone to large number of attacks including false warnings, mispositioning of vehicles etc. The authentication of messages to identify the normal message packet from attack messages packet and its prevention is a major challenging task. This paper focuses on applying deep learning approach using binary classification to classify the normal packets from malicious packets. The process starts with preparing the training dataset from the open-source KDD99 and CICIDS 2018 datasets, consisting of 1,20,223 network packets with 41 features. The one-dimensional network data is preprocessed using an autoencoder to eliminate the unwanted data in the initial stage. The valuable features are then filtered as 23 out of 41, and the model is trained with structured deep neural networks, then combined with the Softmax classifier and Relu activation functions. The proposed Intrusion prevention model is trained and tested with google Colab, an open platform cloud service, and the open-source tensor flow. The proposed prevention classifier model was validated with the simulation dataset generated in network simulation. The experimental results show 99.57% accuracy, which is the highest among existing RNN and CNN-based models. In the future, the model can be trained on different datasets, which will further improve the model's efficiency and accuracy.

Connected vehicle driving safety enhancement via dynamic communication channel selection

Vehicle-to-Vehicle communication can cogently improve traffic safety because it grants drivers better situational awareness and strengthens inter-cooperation among them. However, the current policy obliges the safety-critical messages, i.e., Basic Safety Messages (BSMs) and Event Safety Messages (ESMs), to be transmitted exclusively in one single channel over the Dedicated Short-Range Communication (DSRC) spectrum, which may incur severe channel congestions, intolerable communication delays, and higher accident probabilities. To alleviate the channel congestion, popular measures focus on adaptively adjusting the transmission parameters, e.g., packet generating rate. However, due to the narrow bandwidth of a single channel, these methods can hardly ensure timely delivery of critical safety-related messages when the density of DSRC-enabled vehicles becomes high. Instead of sticking to only one single channel, this paper applies a dynamic channel selection algorithm to thoroughly exploit the entire DSRC band resource and reduce the transmission delay. To demonstrate the effectiveness of the utilized algorithm, we conduct experiments under two representative scenarios, i.e., a cooperative adaptive cruise control scenario and a run-the-red-light scenario at an intersection. Experimental results show that the transmission delays of both the BSMs and the ESMs could be effectively reduced, yielding an improved vehicle platoon control accuracy, string stability, and collision avoidance performance.

Downlink Performance of Optical Power Domain NOMA for Beyond 5G Enabled V2X Networks

In this work, we explore the potential benefits and practical challenges associated with implementation of optical power domain non-orthogonal multiple access (OPD-NOMA) scheme for visible light communications (VLC) based vehicle-to-everything (V2X) networks with a major aim of providing vehicles with reliable, ubiquitous, and massive connectivity. In the proposed framework, an installed light source (e.g., traffic lamp post or street light lamp post) broadcasts a safety related message to desired nodes through visible light. However, such VLC transmission is subject to interference originating from the vehicles in the adjacent lane. Using the stochastic geometry approach, we model the locations of vehicles on the road via Poisson point process. We investigate the applicability of downlink OPD NOMA enabled V2X network for typical infrastructure-to-vehicle (I2V) communication in presence of interference caused from concurrent vehicle-to-vehicle (V2V) transmissions with an aid of stochastic geometry. Through the obtained results, it has been shown that the downlink OPD NOMA based V2X network offers improved performance in terms of outage performance and average achievable rate as compared to the conventional RF based V2X communication.

Left-Right-Front Caching Strategy for Vehicular Networks in ICN-Based Internet of Things

In Vehicular Ad-hoc Networks (VANET), vehicles act like mobile nodes for fetching, sharing, and disseminating important information related to vehicle safety, warning messages, emergency events, and passenger infotainment. Due to continuous information sharing of vehicles with their surrounding nodes, Road Side Units (RSUs), and infrastructures, the existing host-centric IP-based network cannot fulfill the requirements of VANETs. Therefore, Information Centric Networking (ICN) architectures are the introduced to comprehensively address the problems of Internet of Things (IoT)-based VANETs, known as VANET-IoT. This paper introduces a new ICN-based proactive left-right-front (LRF) caching strategy for VANETs, which maximizes the performance of VANETs by placing content proactively at the right nodes. The proposed strategy also provides a mechanism for the timely dissemination of safety-related messages. LRF is compared with other caching strategies in the NS-3 simulator, which outperforms those schemes in terms of cache utilization, hop ratios, and resolved interest ratios with respect to 100 MB, 500 MB, and 1 GB cache sizes.

Utilizing VANETs as supplementary communication infrastructure for delay-tolerant bulky data transportation

With the advancement of connected vehicles, high-bandwidth wireless technologies such as DSRC and WiFi are envisioned to be pervasively available on vehicles. Such empowered vehicles can form large-scale vehicular ad hoc networks (VANETs), which contain rich bandwidth and storage resources. Despite their critical importance for core safety-related VANET applications, these resources are underutilized in practice due to infrequent occurrence and limited size of safety-related messages. However, for a broad range of delay-tolerant applications, which run on edge networks and demand transmission of bulky data with hours or days of delay allowance, such underutilized bandwidth and storage resources in VANETs can be highly valuable. To efficiently utilize VANET resources for delay-tolerant bulky data transmission without compromising the performance of safety-related VANET applications, we propose a Delay-tolerant Data Transportation (DDT) scheme, which aims to use minimal VANET bandwidth to accomplish long-term data transportation under certain end-to-end delay requirements. Unlike traditional VANET data dissemination schemes which prefer data forwarding, DDT primarily relies on a more bandwidth-conserving data carrying method for data transportation. This unique feature makes our proposed system suitable to serve as a supplementary communication infrastructure for offloading and thus alleviating the data transmission workload on edge networks. Extensive simulations have been conducted using a customized simulator, and the results have demonstrated DDT’s reliability and adaptability under various scenarios. Particularly, with moderate traffic density and delay requirements, the VANET bandwidth consumption of DDT is 27.3% lower than that of a naive scheme and 5.3% higher than that of a lower bound obtained from theoretical analysis, while the satisfaction ratio of delay requirements is as high as 0.965.

Hybrid conditional privacy-preserving authentication scheme for VANETs

In existing authentication schemes for vehicular ad hoc networks (VANETs), the public key infrastructure (PKI)-based pseudonym certificate, identity-based encryption and group signature technology are usually used to preserve the security and privacy. However, these schemes face some challenges, e.g., the time-consuming certificate revocation list (CRL) checking, identity revocation issue and the computation overhead of group signature, respectively. To cope with these challenges, we propose a hybrid conditional privacy-preserving authentication protocol based on the PKI certificate and identity-based signature. In our scheme, the trust authority (TA) assigns the unique long-term certificate for every registered node. Only the vehicle with valid certificate can apply the anonymous short term identity from the current RSU to sign safety-related message. The identity-based signature avoids the CRL checking and the complex bilinear paring operation. When vehicle is compromised, TA can easily revoke its identity by the only long-term certificate. To further enhance efficiency, vehicle can verify the received messages by the single or batch authentication manner. In addition, we optimize the authentication process to avoid vehicle verifying the repeated and unnecessary signatures. Compared with the current schemes, the simulation result shows that our authentication protocol can effectively reduce verified messages in the case of meeting the requirement of security and privacy.

A theoretical approach to a safety-based predictive adaptation of wireless communication channel parameters in harsh environments

This paper presents an approach to a real-time optimization of safety parameters in wireless communication systems. When considering the GEC–model (Generalized Erasure Channel) and the black channel design of a communication channel, then the PFH (Probability of Failure per Hour) value can be estimated using the parameters e – BER (bit-error-rate), φ – BLR (bit-loss-rate), v – number of safety related messages per second, n – message length and dmin – minimum distance of a linear code. The number of safety related messages per second v and the message length n, including the information block k and the checksum block r, can be varying between the permissible bounds. Accordingly, the variable parameters can be adjusted at run-time with additional assimilation of the used cyclic code. It allows the real-time prediction and optimization of the safety parameters. In this paper, the concept of the parameter estimation is discussed and based on it the optimization problem is defined.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

DANS: A Secure and Efficient Driver-Abnormal Notification Scheme With IoT Devices Over IoV

The vision of Internet of Vehicles (IoV) is to make the dream of zero traffic accident come true. However, the problems of drivers’ poor fitness and distraction go from bad to worse on account of the increase of chronical patients and the prosperity of mobile phones. Most of the security-related literatures aimed to offer a better efficiency, protection, or scalability on safety-related message verification, but few security protocols were suitable for the transmission of the drivers’ abnormal reports because of low latency requirement. In this paper, we propose a secure notification scheme [driver-abnormal notification scheme (DANS)] based on edge-fog computing to offer real-time response. After passing two-factor authentication, vehicles serve as the edge nodes to download and to real-time compare the sensing parameter for reducing the long-distance communication latency. By means of hash-chain-based public key cryptosystem, DANS can omit the certificate overhead to keep short latency, and also holds the benefits of driver authentication, mutual authentication, integrity for abnormal reports, conditional privacy preservation, non-repudiation, fast verification, and good scalability. Performance evaluations and simulation demonstrate that DANS earns outstanding results in terms of verification delay and communication overhead. To the best of our knowledge, this paper is the first attempt to design a notification scheme to real-time detect the driver-abnormal issues over IoV.

A cooperative V2X MAC protocol for vehicular networks

In support of traffic safety applications, vehicular networks should offer a robust Medium Access Control (MAC) layer protocol that can provide a reliable delivery service to safety-related messages. As the safety applications generally use broadcasting to propagate their messages, a reliable broadcast protocol is essential. In general, however, broadcast is considered as unreliable by nature in contrast to unicast. This paper introduces a novel MAC protocol, called a Hybrid Cooperative MAC (HCMAC), which can substantially enhance the reliability of broadcast in vehicular networks by employing a notion of channelization. HCMAC introduces a hybrid protocol that combines a time slot allocation of Time Division Multiple Access (TDMA) and a random-access technique of Carrier Sense Multiple Access (CSMA) and thus minimizes the probability of data collisions. In addition, its feedback strategy further enhances the system performance by preventing transmissions during time slots that experience collisions. Through analysis and simulations, we compare the performance of HCMAC with VeMAC, an existing TDMA protocol. The results demonstrate that HCMAC can offer substantially faster channel access and lower collision rate compared with VeMAC.

Beacon trust management system and fake data detection in vehicular ad‐hoc networks

A vehicular ad-hoc network is an emerged technology, where vehicles communicate with one another and Road Side Units. Vehicular ad-hoc networks are categorised as a sub-branch of mobile ad-hoc networks, and they help in enhancing traffic efficiency and safety. Vehicular ad-hoc networks facilitate communication by dissemination of messages relaying through vehicles. However, malicious nodes can propagate false safety alert in a network due to its malicious behaviour or selfishness. False messages in vehicular ad-hoc networks can change drivers behaviour and create a disastrous situation in the network. Therefore, it is more important to thwart these false messages. The article presents a beacon trust management system and fake data detection (BTMS-FDD) scheme. The trust management system uses speed and density information to establish a relationship with vicinity vehicles. The false safety event detection scheme uses relative safety and beacon messages to detect false safety event more accurately. For false safety events, a scheme uses position and speed information of beacon and safety-related messages. To analyse the performance of proposed detection scheme, it is compared with ELIDV and host IDS schemes. The simulation results demonstrate that proposed malicious data detection scheme is better in terms of true positive, false positive and overhead.

Reliability and Connectivity Analysis of Vehicluar Ad Hoc Networks for a Highway Tunnel

Vehicular ad-hoc network (VANET) uses ‘mobile internet’ to facilitate the communication between vehicles and with the goal to ensure road safety and achieve secure communication. Thus the reliability of this type of networks is of paramount significance. The safety-related messages are disseminated in VANETs, on the wireless medium through vehicle to vehicle (V2V) and Vehicle to roadside (V2R) communications. Hence, the Reliability of network is an essential requirement. This paper considers the effect of vehicle transmission range R_tran and vehicle density ρ on the connectivity probability. In addition, a reliability model which takes into account minimal safe headway S_h among nearby vehicles at highway tunnel is specified. The reason is that under the tunnel Global Positioning System (GPS), a component of onboard unit (OBU) needs a rich line of sight for perfect services, because due to signal interference, the GPS does not work properly. Though, in the case of a fully connected network, there are chances of danger between vehicles which are close to each other. Therefore, the network is not safe, as accidents and collision can happen at any time. Hence, maintaining the minimal safe headway distance under the tunnel is interesting and useful for VANET. The obtained results show that the little difference of the minimal safe headway under the tunnel can cause a serious change in the entire network reliability. Suggesting that while designing the network reliability models the safe headway S_h cannot be ignored.

Joint Optimization of Message Transmissions With Adaptive Selection of CCH Interval in VANETs

In vehicular networks, the safety-related messages (emergency and periodic messages) and non-safety message (RFS: request for service message) should share the scarce wireless resource. Emergency messages deliver time-critical information with guaranteed reliability, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> road-safety information, whereas periodic ones convey normal status update information, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> vehicular positions, show that is less time- and loss-critical. The RFS message is used for reserving Internet data service through the infrastructure on the road. In the channel access for vehicles, the synchronization interval (SI) is repeated every 100 ms and each SI is divided by one control channel interval (CCHI) for the transmission of safety-related messages and RFS message and by one service channel interval (SCHI) for the Internet service from the roadside infrastructure. It is crucial to set the length of CCHI appropriately in the SI because of the dynamic environment of VANETs. In this paper, we consider two optimization problems of message transmissions depending on whether the length of CCHI is flexible or not: 1) a fixed CCHI (non-adaptive) and 2) a variable CCHI (adaptive), respectively, and obtain the optimal MAC parameters where we adopt the IEEE 802.11e enhanced distributed channel access (EDCA) protocol with a “strict” priority for the emergency message. Finally, we conduct extensive simulations to validate our analytical findings.

A Comparative Experimental Analysis of Channel Access Protocols in Vehicular Networks

The deployment of vehicular networks is considered crucial for traffic safety of future vehicles. Thus, researchers are making extensive efforts to improve the performance of the IEEE802.11p standard. Many researchers have proposed various MAC protocols to mitigate the chronicle problems of the IEEE802.11p – for example, the unreliable transmission of safety-related messages. However, most of the previous evaluations of the reliability problem have been done either via mathematical analysis or simulations. In this paper, we conducted actual experiments and analyzed the performance of two MAC protocols: IEEE802.11p and HCMAC, a hybrid MAC protocol recently reported. Using commercial V2X devices, we measured the performance in terms of received signal strength indicator (RSSI), packet delivery ratio (PDR), and packet inter-reception time (PIR). We tested the connectivity performance under various mobility scenarios. In addition, this paper investigates the impact of collisions on the overall performance. For a range of collision levels, an extensive set of experiments demonstrate that HCMAC outperforms the MAC of IEEE802.11p in terms of PDR and PIR up to 88% and 47%, respectively.

FAGA: Feedback-Aided Greedy Algorithm for Periodic Messages in LTE V2V Communications

Vehicle-to-vehicle (V2V) communication based on the device-to-device (D2D) communication in long term evolution (LTE) system is emerging as a key enabler for connected vehicles today. In this paper, we consider safety-related messages periodically transmitted by vehicle to announce its current status to other neighboring vehicles. The current state-of-the-art LTE V2V communication uses greedy algorithm for the transmission of such periodic messages. Greedy algorithm is known to have decent performance, but the performance is limited due to the lack of a collision–detection mechanism. In this paper, we propose feedback-aided greedy algorithm (FAGA) to complement the drawback of greedy algorithm. We evaluate FAGA via realistic simulations to show that it outperforms comparison schemes in terms of overall message reception ratio (MRR). As a result, it is shown that FAGA operates well even with small amount of feedback and its performance is close to the performance of centralized scheduling method. Moreover, FAGA outperforms greedy algorithm by up to 23.7% in terms of MRR performance.