The rapid development of the Internet of Things (IoT) is affecting several sectors, in particular the Vehicular Ad-Hoc Network (VANET). The link between the IoT and VANET is giving rise to the Internet of Vehicles (10V). With the IoV,vehicles are able to communicate with each other and with other connected objects. To ensure the exchange of information flows between the different entities, autonomy, speed and the decentralized concept must be taken into account. Blockchain technology is a distributed register technology. It is the solution to overcome these challenges and to guarantee vehicular communication. This research work deals primarily with this new technology and its applications in IoV.We then present a multi-agent model of vehicle communication based on Blockchain technology and smart contracts.
As the commercial use of 5G technologies has grown more prevalent, smart vehicles have become an efficient platform for delivering a wide array of services directly to customers. The vehicular crowdsourcing service (VCS), for example, can provide immediate and timely feedback to the user regarding real-time transportation information. However, different sources can generate spurious information towards a specific service request in the pursuit of profit. Distinguishing trusted information from numerous sources is the key to a reliable VCS platform. This paper proposes a solution to this problem called "RC-chain", a reputation-based crowdsourcing framework built on a blockchain platform (Hyperledger Fabric). We first establish the blockchain-based platform to support the management of crowdsourcing trading and user-reputation evaluating activities. A reputation model, the Trust Propagation \& Feedback Similarity (TPFS), then calculates the reputation values of participants and reveals any malicious behavior accordingly. Finally, queueing theory is used to evaluate the blockchain-based platform and optimize the system performance. The proposed framework was deployed on the IBM Hyperledger Fabric platform to observe its real-world running time, effectiveness, and overall performance.
Smart and connected vehicles play a vital role in today's advanced and luxurious life. Vehicular Ad-hoc Network (VANET) allows communication between these vehicles regarding safety and control messages, road situations, and surrounding environments. VANET demands security requirements like authentication, availability, confidentiality, reliability, etc. These requirements have crucial attacks associated with it which hampers a system to work. Blockchain is an immutable, distributed, decentralized, smart contract-based technology that provides an efficient solution to VANET requirements and their corresponding attacks. This paper discusses various such requirements and attacks and their possible solutions with Blockchain. Apart from that, Blockchain also acts as a prominent solution to deal with the challenges being faced by electric and autonomous vehicles to come to reality. We have reviewed, analyzed, and discussed the proficient researcher's works and their contributions in this paper to unfold new directions in the present and future research. Further, we have analyzed and discussed the insurance, and forensic management is amalgamated with Blockchain by various researchers to create an automatic assessment protocol. Future possibilities for smart and connected vehicles with Blockchain could be a major objective of this paper.
Previous work on misbehavior detection and trust management can identify falsified and malicious Vehicle-to-Everything (V2X) messages and enable witness vehicles to report their observations to the trust authority for certificate management. However, there may not exist enough “benign” vehicles with V2X connectivity or vehicle owners who are willing to opt-in at an early stage of connected vehicle deployment. In this paper, we propose a security protocol for Vehicle-to-Infrastructure (V2I) communication, titled Proof-of- Travel (POT), to answer the research question: How can we transform the power of cryptography techniques embedded within the protocol into social and economic mechanisms to simultaneously incentivize V2X adoption and determine the trustworthiness of V2I data? The POT protocol determines the trust of a vehicle based on its distance traveled and the V2I information the vehicle has shared along the path of its movement. Additionally, the total vehicle mileage traveled by the vehicle must be testified by the digital signatures from infrastructure components in the vehicle's trajectory. Targeting rationale attackers motivated by profit-seeking behaviors, the POT protocol creates burdens for malicious vehicles who must acquire chains of proofs for compulsory spatial movement to gain reputation. However, the protocol does not incur extra cost for a normal vehicle who naturally moves from the origin to the destination. Instead, the verifiable vehicle mileage traveled by the normal vehicle can be used to determine its contributions and stake in the system as the altruistic behaviors of sharing observations about traffic events can benefit the transportation network. We show how to use the POT protocol to construct voting-based consensus algorithms to decide the authenticity and the correctness of vehicle-reported events and present initial simulation results.
Chenyue Zhang, Wenjia Li, Yuansheng Luo, Yupeng Hu
Currently, connected vehicles have gradually stepped into our daily lives, and they generally rely on vehicular networks to generate and exchange traffic-related messages to improve the overall travel safety and efficiency. However, due to the open nature of vehicular networks, these traffic-related messages could be erroneous, which may be caused by various reasons, ranging from an onboard device (OBD) sensor malfunctioning and reporting incorrect reading to the message being tampered by a malicious vehicle. To address these rapidly increasing security challenges, we have proposed an AI-enabled trust management system (AIT) in this article, which is an AI-enabled trust management system for vehicular networks using the blockchain technique. In the AIT system, each vehicle first senses, generates, and exchanges messages with other vehicles. These messages then get validated by the neighboring vehicles. As vehicles receive and validate messages from other nearby vehicles, they will establish and manage the trust of those nearby vehicles, which is enabled by utilizing the deep learning algorithm. Once a vehicle identifies untrustworthy vehicles, it reports them to the nearby roadside unit (RSU), and the RSU will validate the authenticity of the report as well as the identity of the vehicle by using the emerging blockchain technique. The security credentials of untrustworthy vehicles will then be revoked by the RSU. We have conducted an extensive experimental study to evaluate the AIT system. Simulation results clearly indicate that AIT performs better than existing approaches and can manage the trust of vehicles and detect malicious ones in an accurate and efficient manner.
Conventional centralized architectures are sufficiently educated to provide high scalability, availability, and low latency and bandwidth usages for the Internet of Things (IoT) network. The exponential increase in volume and number of IoT devices in Intelligent Transportation Systems (ITS) turns our physical world into the cyber world. Security and privacy in the ITS network have become the main concern. To address these issues and challenges, a secure distributed mist computing network architecture for ITS is proposed by leveraging the features of blockchain technology. In this model, we present IoT user/device registration and authentication algorithms and enable the computing resources at the extreme edge of the network by deploying a smart contract. The proposed model uses an aggregate signature scheme to generate a signature for multiple IoT devices. To evaluate the proposed model, we performed an experimental analysis based on various performance measures. The proposed model gains 81% of lower median latency at local nodes compared to the core model. The result shows that the model performed effectively and a suitable solution for various ITS applications.
R. Varsha, Meghna Manoj Nair, Siddharth M. Nair, Amit Kumar Tyagi
The Internet of Things (smart things) is used in many sectors and applications due to recent technological advances. One of such application is in the transportation system, which is of primary use for the users to move from one place to another place. The smart devices which were embedded in vehicles are useful for the passengers to solve his/her query, wherein future vehicles will be fully automated to the advanced stage, i.e. future cars with driverless feature. These autonomous cars will help people a lot to reduce their time and increases their productivity in their respective (associated) business. In today’s generation and in the near future, privacy preserving and trust will be a major concern among users and autonomous vehicles and hence, this paper will be able to provide clarity for the same. Many attempts in previous decade have provided many efficient mechanisms, but they all work only with vehicles along with a driver. However, these mechanisms are not valid and useful for future vehicles. In this paper, we will use deep learning techniques for building trust using recommender systems and Blockchain technology for privacy preserving. We also maintain a certain level of trust via maintaining the highest level of privacy among users living in a particular environment. In this research, we developed a framework that could offer maximum trust or reliable communication to users over the road network. With this, we also preserve privacy of users during traveling, i.e., without revealing identity of respective users from Trusted Third Parties or even Location Based Service in reaching a destination. Thus, Deep Learning based Blockchain Solution (DLBS) is illustrated for providing an efficient recommendation system.
Vehicular ad hoc networks (VANET) authorize the vehicles to communicate and exchange data among themselves and with the Road-Side Unit (RSU). However, with the increase of the vehicles number, the VANET become vulnerable to many attacks. One serious attack is the Sybil attack which threats the functionalities of VANET by generating a high number of fake identities. In this paper, we present a Multi-Levels Trust Mechanism solution (BMLT-SA) based on the blockchain to detect the Sybil attack. Our approach is divided into three main parts : (1) A Horizontal Trust Management mechanism (HTM) is introduced as vehicle to vehicle (V2V) scheme to detect a malicious vehicle. In this level, each vehicle runs a Local Machine Learning (LML) algorithm to classify their neighbors as normal and malicious ones. All the decisions made by the vehicles are broadcasted to the RSUs; (2) A Vertical Trust Management mechanism (VTM) is used to launch a verification algorithm by the RSU. This algorithm takes as input all the LML results and gives a Vehicular Trust list as output; (3) All the RSUs belonging to the same region are collaborating to form a Distributed Trust Management mechanism (DTM) based on the use of the blockchain to share the Vehicular Trust List and to identify the class of each vehicle crossing the network. Simulations and experiments demonstrate that the proposed model based on the collaboration of different VANET components is an effective method for Sybil attack detection.
The revolutionary of Internet of Things (IoT) is currently enabling the transformation of various existing research areas into new themes involving smart mobility, smart home, smart health and smart transport. Focusing on the smart transport, it actually leads towards the development of smart cities. For this purpose, Internet of Vehicles (IoV) is evolving, replacing the previous mobile-based vehicular adhoc network (VANET). This review paper presents a collective discovery on the IoV network model and the rational of introducing and implementing blockchain-based IoV (BIoV). BIoV is the solution to the basic IoV whereby it promises a secured and trusted network and connection to the users. Data stored in blockchain is transparent and users in the network need a key to download the relevant information. Thus, it is proved that blockchain is not easily can be breached by any attacks.
Nathan Martindale, Scott Stewart, Mark Adams, Greg Westphal
In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.
Superior to traditional vehicles, intelligent vehicles (IV) can share data in Vehicular Ad-Hoc Networks (VANETs) to provide a more comfortable and safer driving experience, based on the assumption that the data sharing is accountable and reliable. However, trusted data sharing in VANETs is always a paramount concern. We define that the trusted data sharing includes the three properties, namely data sharing accountability, privacy preservation, and transmission confidentiality. To address the problem, we propose a comprehensive solution including the trusted ledger model (TLM) and implement the Fengyi system to verify it. The TLM is a model that ensures the consistency of multiple data resources in a low trust distributed computing environment. Then, distributed Fengyi ledgers based on the TLM are proposed to keep data sharing accountable and private in VANETs. The Fengyi system is designed and implemented to provide authentication and encrypted communication services with the ledgers. Finally, we deploy the Fengyi system on three different platforms, checking the effectiveness and efficiency of the Fengyi system. The results show that the system can ensure trusted data sharing in VANETs, and the time cost for the verification of data sharing on-road is average 253.33μs, 38% lower than that in recent research.
Ride-hailing is a favored vehicular service model where drivers can deliver convenient rides to waiting riders via responding to a road-side unit or a ride-hailing service provider. However, previous works did not consider the order-linking function where a rider Cathy waving for a ride will be matched to a driver Bob in service with rider Alice whose destination is close to the start point of Cathy. Furthermore, a malicious matching executor could collude with an appointed driver to interfere with the matching process, which causes service unfairness and has not been addressed before. To mitigate these limitations, we first propose a privacy-preserving ride-hailing scheme OLink with the verifiable order-linking property. Specifically, we adopt road network partitioning and range query to achieve basic user matching. The user matching process supports range conditions and protects users' privacy. Next, a Proof-of-Linking protocol is designed based on the zero-knowledge succinct non-interactive argument of knowledge, zero-knowledge proof, and Bloom filters to enable the driver in service to generate three consecutive proofs for linking a current order to the next rider's order in advance; the proofs will be released such that anyone can verify the proofs and matching fairness is guaranteed. Finally, we formally prove the privacy and security of OLink, and then evaluate its performance with PySNARK to demonstrate feasibility and efficiency.
Muhammad Arif, Walter Balzano, Alessandro Fontanella, Silvia Stranieri · 6 authors
The global internet of vehicles market is growing rapidly, it is estimated to increase significantly its value by the next few years. Vehicular Ad hoc Networks (VANETs) has a central role in the development of Intelligent Transportation System, since vehicles can communicate with each other. This paper proposes a model integrating both 5G and Blockchain for vehicular ad-hoc network management. This choice is motivated by the need of guaranteeing secure and reliable information exchange between vehicles. 5G provides low latency communication improving both V2V (Vehicle to Vehicle) and V2I (Vehicle to Infrastructure) connections increasing considerably their trustworthiness. On the other side, BlockChain offers a distributed ledger, enhancing security and data reliability. These technologies together with VANETs mechanism can provide multiple new opportunities and uses, such as automating braking system. In this work, not only we provide a complete overview of these technologies, but also we suggest a new research topic, based on the integration of such technologies with VANETs environment, to obtain a very robust network, and hence a safer traffic management.
Safa Otoum, Ismaeel Al Ridhawi, Hussein T. Mouftah
The advances in today's IoT devices and machine learning methods have given rise to the concept of Federated Learning. Through such a technique, a plethora of network devices collaboratively train and update a mutual machine learning model while protecting their individual data-sets. Federated learning proves its effectiveness in tackling communication efficiency and privacy-safeguarding issues. Moreover, blockchain was introduced to solve many network issues in regard to data privacy and network single point of failure. In this article, we introduce a solution that integrates both federated learning and blockchain to ensure both data privacy and network security. We present a framework to decentralize the mutual machine learning models on end-devices. A blockchain-based consensus solution as a second line of privacy is used to ensure trustworthy shared training on the fog. The proposed model enables on-end device machine learning without any centralized training of the data nor coordination by utilizing a consensus method in the blockchain. We evaluate and verify our proposed model through simulation to showcase the effectiveness of the adapted scheme in terms of accuracy, energy consumption, and lifetime rate, along with throughput and latency metrics. The proposed model performs with an accuracy rate of ≈ 0.97.
Jyotir Moy Chatterjee, Palvadi Srinivas Kumar, Abhishek Kumar, B. Balamurugan
The “Big Four” advancements to come are starting to compel themselves to the fore as associations fiddle with any semblance of artificial intelligence (AI), blockchain (BC), internet of things (IoT), and big data (BD). Be that as it may, as these four springs from their embryonic stages, issues, and concerns are being paid attention to about their development. BC has impeded in its reception and development; however, its application is wide and diverse. In this way, it can profit, and help advantage, any semblance of AI and IoT. Be that as it may, BC can likewise have a critical task to carry out in aiding along with IoT. The development of IoT is as yet moving along, yet it also has hindered on the grounds that many have understood that acing this system of smart ‘things’ is far harder than they could have envisioned. Issues of security and courses of events of execution have caused the publicity around IoT to cool off. In a comparable vein, this has additionally occurred in BC. It is on the grounds that IoT and BC end up in comparative spots with regards to the selection that their mix might have the capacity to enable each other to out and comprehend a portion of the noteworthy worries that have hounded them exclusively. BC is no more in its early stages, yet it is the latest till now. Comparative proclamations can be done regarding the IoT. The buzz around BC utilization in IoT, be that as it may, is undeniably later. The association of the two skirts on the untested—and right now, the unapplied. In the IoT situation, the square chain and, when all is said in done, peer-to-peer methodologies could assume an essential job in the advancement of decentralized and data-serious applications running on billions of gadgets, saving the security of the clients. In this chapter, we will try to provide a detailed overview about this linkage between BC, Bitcoin, and IoT. We will focus on how IoT problems can be solved using the help of BC technology and vice versa.
Blockchain is developing rapidly in various domains for its security. Nowadays, one of the most crucial fundamental concerns is internet security. Blockchain is a novel solution to enhance the security of network applications. However, there are no precise frameworks to secure the Internet of Vehicle (IoV) using Blockchain technology. In this paper, a blockchain-based smart internet of vehicle (BSIoV) framework has been proposed due to the cooperative, collaborative, transparent, and secure characteristics of Blockchain. The main contribution of the proposed work is to connect vehicle-related authorities together to fix a secure and transparent vehicle-to-everything (V2X) communication through the peer-to-peer network connection and provide secure services to the intelligent transport systems. A key management strategy has been included to identify a vehicle in this proposed system. The proposed framework can also provide a significant solution for the data security and safety of the connected vehicles in blockchain network.
Haitham Abu Damis, Dina Shehada, Claude Fachkha, Amjad Gawanmeh · 5 authors
The use of Automatic Dependent Surveillance - Broadcast (ADS-B) for aircraft tracking and flight management operations is widely used today. However, ADS-B is prone to several cyber-security threats due to the lack of data authentication and encryption. Recently, Blockchain has emerged as new paradigm that can provide promising solutions in decentralized systems. Furthermore, software containers and Microservices facilitate the scaling of Blockchain implementations within cloud computing environment. When fused together, these technologies could help improve Air Traffic Control (ATC) processing of ADS-B data. In this paper, a Blockchain implementation within a Microservices framework for ADS-B data verification is proposed. The aim of this work is to enable data feeds coming from third-party receivers to be processed and correlated with that of the ATC ground station receivers. The proposed framework could mitigate ADS- B security issues of message spoofing and anomalous traffic data. and hence minimize the cost of ATC infrastructure by throughout third-party support.
With the tremendous pervasion of location-based services (LBSs) in vehicular networks, the location privacy of vehicles has become an utmost concern. K-anonymity is one of the most popular privacy protection solutions, in which the real location of the request vehicle (RV) can be covered by a cloaking area including the location of k -1 cooperative vehicles (CVs). However, K-anonymity assumes all CVs are always honest and thus offering opportunities for dishonest CVs to provide false location information. To combat such threats, we propose a trusted cloaking area construction (TCAC) scheme based on the trust mechanism to protect the location privacy of vehicles. In this article, the trust value is not only used to identify dishonest CVs, but also utilized to decide the LBS request of RV. A low trust value will make the LBS request be rejected due to dishonest and selfish cooperative behaviors when the RV has played the role of CV. To deal with the massive trust requirements caused by frequent vehicle movement, edge computing is employed to assist trust value evaluation. Moreover, traditional central and distributed trust data management may be unsuitable for vehicular networks. We also propose a blockchain-based trust data management method by combining vehicular regions partition, so as to rapidly evaluate trust value during the cloaking area construction. The security analysis and simulation results indicate that our proposed scheme is resilient to suppress dishonest CVs, inspire selfish CVs, and protect the location privacy of vehicles effectively, whereas the required computation time and communication cost are both limited.
Vehicular ad hoc network(VANET) is a special mobile ad hoc network (MANET) which plays an important role in the intelligent traffic system(ITS). Based on the high mobility of VANETs, the security problems have not been reasonably solved when we enjoy the convenience brought by the Location Based Service(LBS). We present a blockchain-based trust management model for location privacy preserving. The scheme allows vehicles to use certificate to request LBS without revealing their privacy information. We construct anonymous cloaking region to ensure the privacy security of vehicles. We propose a trust management algorithm to constrain and standardize the behavior of vehicles, and use blockchain to implement the data security of vehicles. In the experiments, we conduct the tests with various data sets. Security analysis and experiments show that the system is resilient to sorts of trust model attacks, which can better preserve the privacy security of vehicles. Simulation results reveal that the proposed system is effective and feasible in collect.
Pavlo Gaiduk, Kumar Rajeev Ranjan, Thomas Basmer, Florian Tschorsch
Cooperative intelligent transport systems promise considerable improvements on road safety and the utilization of transport infrastructures. Current approaches, however, build upon policies to protect privacy, which raise serious concerns. In this paper, we propose a privacy-preserving public key infrastructure (PKI) for vehicle-to-everything communication. We use zero-knowledge proofs to authenticate, while still being able to hide identities. In order to exclude malicious actors, we integrate an anonymous reputation-based blacklisting scheme. Our benchmarks on an on-board connectivity unit with resource-constrained hardware confirms the feasibility of the approach. Specifically, we expect approximately 67 kB payload and 35 minutes computation time per day to authenticate.
Zhaowei Ma, F. Richard Yu, Xiantao Jiang, Azzedine Boukerche
The extensive use of vehicles, especially with the emergency of autonomous driving, urges the improvement of traffic safety. Prevalent approaches, such as Global Positioning System (GPS), Internet of Things (IoT) system and Artificial Intelligence (AI), have demonstrated their strength in preventing road accidents, with the support of trustworthy data. However, in vehicular ad hoc networks (VANETs), data transmission and storage are unreliable due to various constraints such as limited physical resource and unsteady topology. Distributed schemes are widely applied in VANETs to enforce multifold protection on vehicular data. In particular, Blockchain has become a promising approach, as it implements the real-sense distributed solution with consensus algorithm and distributed ledger. To this end, we propose a novel system in this paper, which employs Blockchain technology to consolidate the traffic information sharing in VANETs and holds profound significance for intelligent applications. Our system focuses on sharing real-time visual traffic information at the frame level via Blockchain in VANETs. Integrity verification of frames based on their sequences and timestamps is imposed prior to the consensus in Blockchain, coupled with digital watermarking to protect the multimedia traffic data. Improved efficiency and reliability of sharing are achieved by the system dynamically adjusting transaction volume in terms of the frame type and number. With the fault tolerance and immutability of Blockchain, our proposal can solidly protect the traffic information sharing against vandalization in VANETs, and confidently escort the traffic with trustworthy safety guidance.
In this study, we initiate a cyberinfrastructure solution by synergizing both the blockchain and Internet of Things (IoT) technologies for transportation insurance. The insurance premium related services are encapsulated in “on-chain” chaincodes to perform over the facts on vehicle's trip and driver's behavior, which are deduced through “off-chain” analytic services using the sensing data collected from vehicles' on-board sensors. A hybrid scheme coordinating both the permissioned (Hyperledger) and public (Ethereum) blockchains is proposed to exploit their respective capabilities in terms of high transaction throughput and built-in cryptocurrency. A working prototype platform is implemented with a basic premium calculation model. The prototype system is deployed across Amazon Web Services (AWSs) cloud in a real-world Internet environment. A comprehensive performance study from the aspects of throughput, latency, and resource usage under different configurations is presented to show the solution's feasibility. The design practice and research findings are concluded in consort with the experience gained for further enhancing the proposed solution and extending the functional features such as a more realistic insurance policy to be applied in generic vehicle insurance applications.