Secure Vehicular Communication Research Articles

Efficient Key Extraction for Secure Vehicular Communication Through OTFS

Efficient Key Extraction for Secure Vehicular Communication Through OTFS

Transforming Transportation: Safe and Secure Vehicular Communication and Anomaly Detection With Intelligent Cyber–Physical System and Deep Learning

Transforming Transportation: Safe and Secure Vehicular Communication and Anomaly Detection With Intelligent Cyber–Physical System and Deep Learning

Secure Vehicular Communications With Varying QoS and Environments: A Unified Cross-Layer Policy-Adaptation Approach

With the ubiquitous connectivity in internet of vehicles, secure transmission is of vital importance for intelligent vehicle-to-everything (V2X) communications. However, in order to effectively guarantee the secrecy performance, once the short-term statistics of channel quality are low, which frequently happens because of the high mobility of vehicles, the throughput performance can be weakened by using the existing either cryptography techniques or physical-layer security (PLS) technique. To improve the throughput of secure data transmission, we propose the concept of statistical security, which utilizes the time-sensitive characteristics of information, such as the position of mobile vehicles, in V2X communications. Specifically, the time-sensitive information has its own outdated rate. As long as the information leakage rate is less than the information outdated rate, the eavesdropper still cannot obtain any useful information. Then, we use a queue system to characterize the eavesdropping process, where the queue-length violation probability indicates the level of secure transmission. Under this statistical security model, we investigate the throughput maximization problem and give the optimal power allocation scheme for the legitimate vehicular users. Furthermore, since the service’s security QoS requirements and wireless environments are both varying in V2X communications, we propose a unified cross-layer policy-adaption approach to guarantee the varying security QoS requirements meanwhile improving the throughput. Simulation results verify that our proposed approach significantly outperforms the existing baseline schemes.

RIS-Enabled Secret Key Generation for Secured Vehicular Communication in the Presence of Denial-of-Service Attacks.

Wireless communication has become an integral part of modern vehicles. However, securing the information exchanged between interconnected terminals poses a significant challenge. Effective security solutions should be computationally inexpensive, ultra-reliable, and capable of operating in any wireless propagation environment. Physical layer secret key generation has emerged as a promising technique, which leverages the inherent randomness of wireless-channel responses in amplitude and phase to generate high-entropy symmetric shared keys. The sensitivity of the channel-phase responses to the distance between network terminals makes this technique a viable solution for secure vehicular communication, given the dynamic behavior of these terminals. However, the practical implementation of this technique in vehicular communication is hindered by fluctuations in the communication link between line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. This study introduces a key-generation approach that uses a reconfigurable intelligent surface (RIS) to secure message exchange in vehicular communication. The RIS improves the performance of key extraction in scenarios with low signal-to-noise ratios (SNRs) and NLoS conditions. Additionally, it enhances the network's security against denial-of-service (DoS) attacks. In this context, we propose an efficient RIS configuration optimization technique that reinforces the signals received from legitimate users and weakens the signals from potential adversaries. The effectiveness of the proposed scheme is evaluated through practical implementation using a 1-bit RIS with 64×64 elements and software-defined radios operating within the 5G frequency band. The results demonstrate improved key-extraction performance and increased resistance to DoS attacks. The hardware implementation of the proposed approach further validated its effectiveness in enhancing key-extraction performance in terms of the key generation and mismatch rates, while reducing the effect of the DoS attacks on the network.

RSU-Based Online Intrusion Detection and Mitigation for VANET.

Secure vehicular communication is a critical factor for secure traffic management. Effective security in intelligent transportation systems (ITS) requires effective and timely intrusion detection systems (IDS). In this paper, we consider false data injection attacks and distributed denial-of-service (DDoS) attacks, especially the stealthy DDoS attacks, targeting integrity and availability, respectively, in vehicular ad-hoc networks (VANET). Novel machine learning techniques for intrusion detection and mitigation based on centralized communications through roadside units (RSU) are proposed for the considered attacks. The performance of the proposed methods is evaluated using a traffic simulator and a real traffic dataset. Comparisons with the state-of-the-art solutions clearly demonstrate the superior detection and localization performance of the proposed methods by in the best case and in the worst case, while achieving the same level of false alarm probability.

An Efficient Certificateless Ring Signcryption Scheme With Conditional Privacy-Preserving in VANETs

As an ever-increasing ingredient of intelligent transportation systems, vehicular ad hoc networks (VANETs) can be leveraged to improve road safety and driving convenience. However, the extreme mobility and volatility of VANETs can arouse serious concerns about vehicle identity privacy leakages as well as the authenticity and confidentiality of safety messages in vehicular communication. To cope with these issues, we propose a certificateless ring signcryption scheme with conditional privacy-preserving based on elliptic curve cryptography, which can provide secure vehicular communication with low transmission latency and communication overhead. Besides, by integrating a tracking mark into the safety message, we design a tracking algorithm that enables the trusted party to distinguish malicious vehicles from the ring member list. It realizes conditional privacy while avoiding the huge cost of vehicular storage resources. Through security analysis, this scheme is proven to be secure under the Elliptic curve discrete logarithm and Elliptic curve computational Diffie–Hellman assumptions in the random oracle model. Finally, we implement the performance evaluations in terms of the computational overhead, the communication bandwidth and the packet loss rate. By utilizing the MIRACL cryptography library and the Veins simulation framework, the results illustrate that the proposed scheme can support an efficient and highly reliable communication protocol for safety-related applications in VANETs environment.

Secure vehicular data communication in Named Data Networking

Vehicular data misuse may lead to traffic accidents and even loss of life, so it is crucial to achieve secure vehicular data communications. This paper focuses on secure vehicular data communications in the Named Data Networking (NDN). In NDN, names, provider IDs and data are transmitted in plaintext, which exposes vehicular data to security threats and leads to considerable data communication costs and failure rates. This paper proposes a Secure vehicular Data Communication (SDC) approach in NDN to supress data communication costs and failure rates. SCD constructs a vehicular backbone to reduce the number of authenticated nodes involved in reverse paths. Only the ciphtertext of the name and data is included in the signed Interest and Data and transmitted along the backbone, so the secure data communications are achieved. SCD is evaluated, and the data results demonstrate that SCD achieves the above objectives.

Detection, control and mitigation system for secure vehicular communication

The increase in the safety and privacy of automated vehicle drivers against hazardous cyber-attacks will lead to a considerable reduction in the number of global deaths and injuries. In this sense, the European Commission has focused attention on the security of communications in high-risk systems when receiving a cyber-attack such as automated vehicles. The project SerIoT comes up as an possible solution, providing a useful open and reference framework for real-time monitoring of the traffic exchanged through heterogeneous IoT platforms. This system is capable of recognize suspicious patterns, evaluate them and finally take mitigate actions. The paper presents a use case of the SerIoT project related to rerouting tests in vehicular communication. The goal is to ensure secure and reliable communication among Connected Intelligent Transportation Systems (C-ITS) components (vehicles, infrastructures, etc) using the SerIoT's system capabilities to detect and mitigate possible network attacks. Therefore, fleet management and smart intersection scenarios were chosen, where vehicles equipped with On Board Units (OBU) interact with each other and Road Side Units (RSU) to accomplish an optimal flow of traffic. These equipments use the SerIoT systems to deal with cyber-attacks such as Denial of Service (DoS). Tests have been validated in different scenarios under threats situations. It shows the great performance of the SerIoT system taking the corresponding actions to ensure a continuous and safety traffic flow.

An efficient authentication scheme with strong privacy preservation for fog-assisted vehicular ad hoc networks based on blockchain and neuro-fuzzy

Privacy, security and efficiency are important performance issues in vehicular ad hoc network (VANET), which researchers have tried to address in recent years. This research article proposes a lightweight and privacy-preserving certificateless authentication scheme in fog-assisted VANET using blockchain technology and neuro-fuzzy machine learning technique. A new authentication scheme is designed using certificateless signature based on elliptic curve cryptography (ECC) and hash function operation. The scheme utilizes two blockchains to achieve decentralized and transparent transactions and revocation process. In order to prevent denial-of-service attack, in which a roadside unit (RSU) is flooded with a massive amount of fake authentication requests so as to prevent legitimate nodes from being authenticated, a neuro-fuzzy algorithm is implemented to proactively detect and discard any anomalous requests prior to an authentication process. Moreover, the scheme is demonstrated to be semantically secure in the random oracle model (ROM) based on the intractability of the discrete logarithm problem (DLP). A panoptic analysis shows that the scheme possesses outstanding attributes required for a secure vehicular communication system. The experimental simulation is conducted using simulation of urban mobility (SUMO) and the broadly-accepted network simulator NS-3. The results indicate that the proposed scheme has a high efficiency in terms of transmission delay and message delivery rate. The comparative analysis with the state-of-the-art schemes reveals that the proposed scheme has an improvement of 50%–90.5% in computation cost and 38.46%–69.6% in communication overhead. The simulation result of the neuro-fuzzy gives an accuracy of 91.5% and further analysis shows that it significantly reduces the computation burden on the RSU proportionately with increase in the number of malicious messages.

Machine Learning Technologies for Secure Vehicular Communication in Internet of Vehicles: Recent Advances and Applications

Recently, interest in Internet of Vehicles’ (IoV) technologies has significantly emerged due to the substantial development in the smart automobile industries. Internet of Vehicles’ technology enables vehicles to communicate with public networks and interact with the surrounding environment. It also allows vehicles to exchange and collect information about other vehicles and roads. IoV is introduced to enhance road users’ experience by reducing road congestion, improving traffic management, and ensuring the road safety. The promised applications of smart vehicles and IoV systems face many challenges, such as big data collection in IoV and distribution to attractive vehicles and humans. Another challenge is achieving fast and efficient communication between many different vehicles and smart devices called Vehicle-to-Everything (V2X). One of the vital questions that the researchers need to address is how to effectively handle the privacy of large groups of data and vehicles in IoV systems. Artificial Intelligence technology offers many smart solutions that may help IoV networks address all these questions and issues. Machine learning (ML) is one of the highest efficient AI tools that have been extensively used to resolve all mentioned problematic issues. For example, ML can be used to avoid road accidents by analyzing the driving behavior and environment by sensing data of the surrounding environment. Machine learning mechanisms are characterized by the time change and are critical to channel modeling in-vehicle network scenarios. This paper aims to provide theoretical foundations for machine learning and the leading models and algorithms to resolve IoV applications’ challenges. This paper has conducted a critical review with analytical modeling for offloading mobile edge-computing decisions based on machine learning and Deep Reinforcement Learning (DRL) approaches for the Internet of Vehicles (IoV). The paper has assumed a Secure IoV edge-computing offloading model with various data processing and traffic flow. The proposed analytical model considers the Markov decision process (MDP) and ML in offloading the decision process of different task flows of the IoV network control cycle. In the paper, we focused on buffer and energy aware in ML-enabled Quality of Experience (QoE) optimization, where many recent related research and methods were analyzed, compared, and discussed. The IoV edge computing and fog-based identity authentication and security mechanism were presented as well. Finally, future directions and potential solutions for secure ML IoV and V2X were highlighted.

Adaptive and Optimum Secret Key Establishment for Secure Vehicular Communications

In intelligent transportation systems (ITS), communications between vehicles, i.e. vehicle-to-vehicle (V2V) communications are of greatest importance to facilitate autonomous driving. The current state-of-the-art for secure data exchange in V2V communications relies on public-key cryptography (PKC) consuming significant computational and energy resources for the encryption/decryption process and large bandwidth for the key distribution. To overcome these limitations, physical-layer security (PLS) has emerged as a lightweight solution by exploiting the physical characteristics of the V2V communication channel to generate symmetric cryptographic keys. Currently, key-generation algorithms are designed via empirical parameter settings, without resulting in optimum key-generation performance. In this paper, we devise a key-generation algorithm for PLS in V2V communications by introducing a novel channel response quantisation method that results in optimum performance via analytical parameter settings. Contrary to the current state-of-the-art, the channel responses incorporate all V2V channel attributes that contribute to temporal variability, such as three dimensional (3D) scattering and scatterers’ mobility. An extra functionality, namely, Perturbe-Observe (PO), is further incorporated that enables the algorithm to adapt to the inherent non-reciprocity of the V2V channel responses at the legitimate entities. Optimum performance is evidenced via maximisation of the key bit generation rate (BGR) and key entropy (H) and minimisation of the key bit mismatch rate (BMR). A new metric is further introduced, the so-called secret-bit generation rate (SBGR), as the ratio of the number of bits which are successfully used to compose keys to the total amount of channel samples. SBGR unifies BGR and BMR and is thus maximised by the proposed algorithmic process.

Optimal secure transmit design for wireless information and power transfer in V2X vehicular communication systems

Simultaneous wireless information and power transfer (SWIPT) in vehicle to everything networks is a perspective technology which helps prolong the lifetime of sensors installed on roadside devices and vehicles. In this study, we consider a secure vehicular communication system with SWIPT under a non-linear EH model where the energy vehicular receivers are able to collect energy from the radio frequency signals as they are idle. We formulate the secure transmit signal design as an optimization problem which aims to maximize the minimum fairness energy power at the energy vehicular users. In addition, the considered optimization problem also considers different quality of service requirements: a maximum tolerable capacity at energy vehicular receivers and a minimum needed signal-to-interference-ratio at information vehicular receivers. To obtain a manageable solution, we reexpress the referred problem by variable substitutions and replacing a non-convex constraint with a convex form. Then, we adopt the semidefinite relaxation (SDR) technique to obtain the optimal solution of the original problem. To decrease calculational complexity, we also propose a suboptimal secure beamforming scheme for facilitating wireless energy transfer and providing physical layer security. Simulation results indicate that the developed secure transmit signal algorithm can obtain better performance gains than other algorithms.

Physical-Layer Security and Privacy for Vehicle-to-Everything

Vehicular communications in intelligent transportation systems promise to improve traffic efficiency, road utilization, and safety. Achieving secure vehicular communications is vital for the deployment of vehicle-to-everything (V2X) applications. This article provides a comprehensive overview of physical-layer security (PLS) strategies employed for V2X. By exploiting the randomness and the physical characteristics of wireless channels, PLS offers reliable solutions against eavesdropper attacks as complementary approaches to cryptographic techniques. We give a brief introduction to the architecture and characteristics of V2X networks. Then the fundamental principles of PLS technology are proposed, followed by security threats in V2X. Additionally, we discuss some open issues and challenges for future research. Finally, we investigate a case study where different challenges and technologies coexist in one V2X scenario.

Lightweight privacy-preserving power injection and communication over vehicular networks and 5G smart grid slice with provable security

In vehicle-to-grid (V2G) network, electric vehicles (EVs) can store greenpower from renewable energy sources and inject excess power to the grid during the peak hours for monetary benefits. Since transactions are involved in this process, it is pertinent to secure any transmitted packet and protect users’ privacy to ensure fairness in the energy market and combat any privacy issues that can expose the users’ energy profile and hinder the deployment of autonomous vehicle networks (AVNs). In this research article, a lightweight privacy-aware power injection and communication (LPPC) scheme suitable for deployment over vehicular networks and 5G smart grid slice is proposed. In LPPC, each EV prepares its bids and computes two secret keys shared with the utility company and gateway to blind the bids for different time slots. A novel aggregation technique based on elliptic curve cryptography (ECC) is utilized to aggregate the blinded bids. A hash function-based technique which allows the utility company to verify the authenticity and integrity of the aggregated bid while concealing the individual bids is developed. We demonstrate the security of LPPC in the random oracle model based on the intractability of the computational Diffie–Hellman and Discrete Logarithm problems. Our analysis shows that LPPC can protect the individual bids and achieve secure vehicular communication. The performance evaluation shows that LPPC is much more efficient than the state-of-the-art schemes.

A sensor enabled secure vehicular communication for emergency message dissemination using cloud services

A Vehicular Ad-hoc Network (VANET) entails smart vehicles on the road to provide communication services among nearby vehicles. It is ideated with the intention to develop applications that are versatile and efficient. Due to its dynamic nature, achieving a secure and reliable communication via VANET is a crucial challenge. Hence, varied security mechanisms are developed conventionally. But there were limitations such as increased delay, bandwidth usage, limited security, and reduced communication efficiency. In order to overcome these limitations, this paper introduces a protocol namely, Sensor Enabled Secure Vehicular Communication (SSVC) to enable a secure and reliable communication in VANET. The objectives of this paper are to reduce the latency, and to improve the communication efficiency of the network. At first, a network is formed with n number of vehicles and neighbor discovery is performed via Wireless Access in Vehicular Environment (WAVE) protocol. Further, the sensors attached with the vehicle machinery are used to obtain information such as, air pressure, temperature, and speed of the vehicle. These information are stored in a gateway and the vehicles of the network are registered in a gateway by generating a unique ID and password to each vehicle. A cloud connection is enabled to broadcast the emerging messages to all the vehicles. Also, blowfish technique is implemented to store the location information of the vehicle in the cloud in a secure manner. This improves the security level of the vehicular communication. Different performance measures are used to evaluate the results of the proposed system via simulations. Then the results are compared with the existing mechanism to prove the efficiency of the proposed SSVC mechanism.

Robust Beamforming Design for Secure V2X Downlink System with Wireless Information and Power Transfer under a Nonlinear Energy Harvesting Model.

Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes.

Optical PUF for Non-Forwardable Vehicle Authentication

Modern vehicles are configured to exchange warning messages through IEEE 1609 Dedicated Short Range Communication over IEEE 802.11p Wireless Access in Vehicular Environment. Essentially, these warning messages must associate an authentication factor such that the verifier authenticates the message origin via visual binding. Interestingly, the existing vehicle communication incorporates the message forward-ability as a requested feature for numerous applications. On the contrary, a secure vehicular communication relies on a message authentication with respect to the sender identity. Currently, the vehicle security infrastructure is vulnerable to message forwarding in a way that allows an incorrect visual binding with the malicious vehicle, i.e., messages seem to originate from a malicious vehicle due to non-detectable message relaying instead of the actual message sender. We introduce the non-forwardable authentication to avoid an adversary coalition attack scenario. These messages should be identifiable with respect to the immediate sender at every hop. According to a coalition attack scenario, the group of adversaries in coalition adopt the fabricated attributes of a target vehicle and resembles it to be alike. The adversaries in coalition then reroute the eavesdropped messages in order to impersonate the target vehicle. We propose to utilize immediate optical response verification in association with the authenticated key exchange over radio channel. These optical response are generated through hardware means, i.e., a certified Physically Unclonable Function device embedded on the front and rear of the vehicle. To the best of our knowledge, this is the first work proposing a solution based on physically unclonable function for a secure non-forwardable vehicle to vehicle authentication. In addition a formal correctness sketch is derived using Strand Space methodology.

차량간 보안 통신에서 융합 해시함수를 이용하여 공격에 안전한 통신방법 검증

자동차에 정보기술 도입비율이 높아짐에 따라서 최근 스마트 카, 커넥티드 카로 일컬어지기 시작했다. 스마트자동차 시스템이 적용되어 외부 네트워크에서 차량과 접속하게 되면서 통신보안 위협 또한 증가하고 있다. 차량에 다양한 보안 위협에 대한 모의시험 결과로 관련된 취약성이 사회적 이슈와 기사화 되고 있으며, 자동차 융합 보안통신에 대한 연구가 활발히 진행되고 있다. 자동차 해킹이 일반적인 해킹보다 위험한 것은 운전자의 생명위협 및 사회적인 혼란을 야기할 수 있기 때문이다. 본 논문에서는 차량 대 차량, 차 내부 통신 등에 안전한 통신을 위해 해시함수, 난수, 공개키, 타임스탬프 및 Password 등을 이용하여 융합 프로토콜을 설계하였다. 정형검증 도구인 Casper/FDR을 이용하여 검증하였으며 제안한 프로토콜이 보안적으로 양호하게 동작되며 외부 공격자의 공격에 안전함을 확인하였다. The increase in applying IT to vehicles has given birth to smart cars or connected cars. As smarts cars become connected with external network systems, threats to communication security are on the rise. With simulation test results supporting such threats to Convergence security in vehicular communication, concerns are raised over relevant vulnerabilities, while an increasing number of studies on secure vehicular communication are published. Hacking attacks against vehicles are more dangerous than other types of hacking attempts because such attacks may threaten drivers' lives and cause social instability. This paper designed a Convergence security protocol for inter-vehicle and intra-vehicle communication using a hash function, nonce, public keys, time stamps and passwords. The proposed protocol was tested with a formal verification tool, Casper/FDR, and found secure and safe against external attacks.

Privacy-preserving authentication framework using bloom filter for secure vehicular communications

Vehicular ad hoc networks (VANETs) are the future of the intelligent transportation systems (ITS), which aim to improve traffic safety. The received message in VANETs can contain the malicious content that may affect the entire network; hence, these networks are more prone to such attacks. Thus, security is a major consideration before the deployment of such network. In this paper, a secure privacy-preserving authentication framework is proposed, which employs the use of pseudonyms for anonymous communication. A new digital signature scheme and aggregate verification scheme are designed for vehicular communications, and the ID-based signature scheme is used for vehicle-to-RSU communication. The multiple authorities are involved in revealing the identity of the vehicle in case of revocation. The signature verification scheme is improved by the use of bloom filters, and the results achieved by the proposed scheme have been implemented on a simulated environment.

Function-based connection protocol development and verification for secure communication in vehicle environment

The latest advancement of information communication technology has facilitated the development of multifunctional high-performance vehicular communication system and the great strides in user convenience. Still, due to the nature of inter-vehicle communication and that of the communication system between internal and external devices, problems of intruders' attacks arise in transmission sections. Any successful attack on vehicular operating, steering, controlling and imaging systems by intruders would end up in grave safety and privacy issues. In this regard, the need for safe and secure vehicular communication is considered important. In the same vein, the importance of research on hardware security and secure communication protocols is emphasized. This Paper designed a secure vehicular communication protocol using hash locks, random numbers and time-stamps. The proposed protocol was experimentally tested with the formal verification tool Casper/FDR and proved to be secure against diverse attacks from intruders. In brief, the proposed protocol turned out to be safe against deadlock and livelock and to finish without trouble.