Blockchain Papers

Ali Samanipour, Omid Bushehrian

No abstract is available for this record.

Shuchi Priya, Sushil Kumar, Anjani Anjani, Ahmad M. Khasawneh · 5 authors

Smart vehicles integrated with the Internet of Things (IoT) provide rich data for traffic management, safety, and liability services; however, existing blockchain-enabled vehicular architectures still struggle with consensus scalability, heavy centralized validation, limited interaction-based corroboration, incomplete attack coverage, and rapid ledger growth. In particular, many schemes either optimize single-layer consensus or embed detailed reputation information into every transaction, while pushing most validation to central servers. This leads to bottlenecks under dense traffic and leaves replay, Sybil-assisted 51% attacks on roadside units (RSUs), and man-in-the-middle tampering only partially addressed. In this context, this paper proposes a novel hierarchical blockchain for vehicular IoT (HBV-IoT) model to address the above challenges. An independent transaction for periodic vehicle status reporting and an interaction-based transaction for corroborating data between vehicles in proximity are presented. Three smart contracts are designed to automate the validation and processing of transactions, and to identify compromised or malicious vehicles within the HBV-IoT network. Algorithms for distributed consensus to accept transactions into the blockchain and for vehicle reputation management to enforce edge-level filtering and down-weighting of malicious nodes are implemented. Simulation results demonstrate significant improvements compared to conventional vehicular blockchain approaches, with performance gains validated by 95% confidence intervals. The model supports practical applications, including real-time traffic monitoring, automated e-challan issuance, intelligent insurance claim processing, and blockchain-based vehicle registration.

Satoshi Kawauchi

This study proposes a mobility control architecture that replaces conventional physical distance-based autonomous driving with a network-based logical spatiotemporal occupancy reservation system. Instead of relying solely on onboard sensors, vehicles reserve future movement regions as packetized occupancy rights across a communication infrastructure. A multi-layer consensus mechanism—combining efficiency, safety, and legal validation algorithms—determines vehicle behavior, while smart contracts and distributed ledgers record risk evaluation and liability allocation in real time. This approach enables high-density traffic flow beyond traditional braking constraints, improves road utilization efficiency, and enhances legal accountability in autonomous mobility networks. The framework also integrates infrastructure routing and fail-safe fallback mechanisms and relies on the Quantum Thought Circuit OS ASI architecture for deterministic decision control.

Vairam T, Mukilan A

A growing requirement for intelligent transportation systems (ITS) and vehicle-to-infrastructure (V2I) communication provides the foundation for a safe, highly-scalable, and decentralized tolling and real-time data exchange solution. Blockchain solutions typically incorporate the overhead burden of using consensus algorithms such as PBFT, which do not provide the scalability required in dynamic vehicular environments. This thesis proposes a decentralized V2I communication and data exchange mechanism, based on using a Proof of Stake (PoS) Blockchain. Smart contracts facilitate toll collection, transaction confirmation, and record keeping for V2I vehicle communication via an unbiased blockchain ledger that is immutable. Therefore, the proposed framework creates transparency, tamper-resistance, and data security for the exchange of V2I communication. This work achieves an improvement in communication infrastructurerelated latency and scalability, allowing for applications in many different real-time V2I cases by substituting the communicationintensive nature of POS for the consensus-based approach of existing blockchain systems.

Ram Krishna Upadhyay, Sunil Kumar Sharma, Manoj Gupta

No abstract is available for this record.

U. B. Nagesh, Manjunath Kotari

The application of Distributed Ledger Technology in Intelligent Transportation Systems ensures a secure and decentralized mechanism for data sharing among vehicles and infrastructure. However, DAG based protocols such as the IOTA Tangle when applied to autonomous vehicular systems face significant challenges in ledger consistency, transaction confirmation, and convergence due to the highly dynamic and intermittently connected nature of vehicular networks. To address these limitations, this paper proposes a Connectivity Aware Intelligent Distributed Ledger Construction Model tailored for autonomous vehicular environments. The proposed framework integrates a connectivity aware tip selection mechanism with a reinforcement learning strategy based on sliding window bias thompson sampling to dynamically select optimal ledger construction actions under non-stationary network conditions. Vehicular connectivity is modeled using an alternating renewal process, and transaction arrivals by a nonstationary Poisson process. Extensive simulation results demonstrate that CA-IDLCM outperforms URTS, MCMC, and Biased-TS approaches by achieving confirmation rate of 95.8%, and maintaining the orphan fraction well below 2%, with tip counts stabilizing near 1.0. highlighting its robustness, adaptability, and suitability for next generation Intelligent Transportation Systems.

Qichang Li, Yingjie Xia, Xuejiao Liu, Xiyuan Chen · 8 authors

Vehicle platoon (VP), as a typical form of traffic cooperation, can significantly enhance traffic efficiency and safety in Vehicular Ad hoc Networks (VANETs). However, malicious vehicles in VP poses a severe threat to the security of entire VP, requiring to be efficiently traced by identity authentication. In this paper, we propose a lattice-based efficient and traceable privacy-preserving batch authentication scheme for vehicle platoon in VANETs, named LETA. First, we design a dynamic VP identity structure VPD-Tree which is constructed based on hash tree and pseudonyms of vehicles to preserve privacy. Then, an aggregate signature is constructed based on VPD-tree and modular lattice for secure and efficient batch authentication of VP. Finally, Zero-Knowledge Proofs (ZKP) is applied on the VPD-Tree structure to anonymously and efficiently trace the malicious vehicles of VP. Security analysis shows that LETA achieves stronger security guarantees, thereby offering a more secure solution than existing approaches. Moreover, performance evaluations show that LETA achieves lower computation and communication overheads through the VPD-tree structure and efficient batch authentication scheme.

Xingyu Chen, Weihua Zhang, Haijian Bai, Feng Zhu · 6 authors

No abstract is available for this record.

Tiago Silvestre, Paulo Bartolomeu

This paper addresses the application of blockchain in Digital Twin (DT) systems, which often rely on centralized architectures, by proposing and evaluating a decentralized management system for vehicle DTs. The system uses Ethereumbased ERC-1155 NFTs to represent vehicles. Smart contracts handle NFT minting, ownership transfers, and a three-phase lifecycle. Off-chain data is stored on IPFS, with privacy secured by an algorithm based on ECDH. A decentralized application was developed to enable interaction with the blockchain and IPFS. Evaluation of the system included static analysis, automated testing, and gas cost analysis. The system is capable of managing a vehicle NFT from its inception until its decommissioning, with all actions recorded on the blockchain and IPFS. While scalable at the smart contract level, Ethereum’s network throughput can pose limitations for full-scale automotive industry adoption, suggesting suitability for smaller-scale applications or the necessity for improvements in both Layer 1 and Layer 2 solutions. This work demonstrates a feasible end-to-end Web3 solution for vehicle Digital Twins, bringing transparency and data integrity to the vehicular ecosystem.

Xiaoyu Zhou

With the acceleration of urbanization and the promotion of the “dual carbon” goal, the road transport system is facing the triple challenges of efficiency bottlenecks, excessive carbon emissions, and data security risks. In view of the shortcomings of the existing research in dynamic response, multi-objective collaboration and privacy protection, this paper proposes a three-in-one intelligent management framework: (1) construct a real-time dynamic path optimization model based on Deep Reinforcement Learning (DRL), and realize the precise regulation of traffic flow through multi-source data fusion and adaptive reward mechanism; (2) Design a multi-objective optimization model integrating carbon trading mechanism to quantify the synergistic relationship between transportation efficiency, carbon emissions and economic costs; (3) Develop a distributed data management framework based on blockchain, and use zero-knowledge proof and smart contract technology to protect user privacy. The peak simulation experiment based on the fifth ring road section of Beijing shows that the proposed method reduces the average traffic time by 18.7%, the carbon emission by 23.5%, and the risk of data leakage by 76% compared with the traditional algorithm. This study provides theoretical and technical support for the construction of a safe, efficient and low-carbon intelligent transportation system.

Mohsen Ahmadvand, Pedro Souto

Zero-knowledge rollups rely on provers to generate multi-step state transition proofs under strict finality and availability constraints. These steps require expensive hardware (e.g., GPUs), and finality is reached only once all stages complete and results are posted on-chain. As rollups scale, staying economically viable becomes increasingly difficult due to rising throughput, fast finality demands, volatile gas prices, and dynamic resource needs. We base our study on Halo2-based proving systems and identify transactions per second (TPS), average gas usage, and finality time as key cost drivers. To address this, we propose a parametric cost model that captures rollup-specific constraints and ensures provers can keep up with incoming transaction load. We formulate this model as a constraint system and solve it using the Z3 SMT solver to find cost-optimal configurations. To validate our approach, we implement a simulator that detects lag and estimates operational costs. Our method shows a potential cost reduction of up to 70\%.

Imad Bourian, chaimae elfilali, Khalid Chougdali

No abstract is available for this record.

Kamini Sharma, Bhavna Bajpai, Hansa Vaghela, Praveen Kumar Patidar · 6 authors

In smart cities, blockchain technology has the ability to completely transform how intelligent transportation systems (ITSs) function. Blockchain can offer a safe and decentralized platform for exchanging and storing data. Improve ITS systems' interoperability, security, and privacy. Blockchain technology may be applied to a number of ITS applications, such as decentralized markets for transportation services, smart contracts for driverless cars, and secure data transmission between automobiles, infrastructure, and service providers. Scalability and high processing power needs are two of the unique difficulties associated with integrating blockchain technology into ITS. Notwithstanding the difficulties, blockchain technology presents ITS in smart cities with a number of benefits, opening up new commercial avenues and encouraging innovation in transportation services. ITS's potential study topics and prospects for city development.

Fatima Al‐Quayed, Noshina Tariq, Mamoona Humayun, Farrukh Aslam Khan · 6 authors

ABSTRACT The Internet of Vehicles (IoV) is a critical component of the smart city. Various nodes exchange sensitive data for urban mobility, such as identification, position, messages, speed, and traffic statistics. Along with developing smart cities come threats to privacy and security through networks. Security is of the highest priority, considering various security‐privacy risks from the wellness, safety, and confidentiality of men and women inside the vehicle. This survey presents a detailed analysis of state‐of‐the‐art and evolving security challenges to IoV systems. It handles security challenges, such as data integrity and privacy. It also includes a critical review of the literature to identify gaps in current security mechanisms. It uses complete mathematical modeling and case studies to show the practical effectiveness of the proposed solutions. It aims to guide future development and implementation of more secure, efficient, and resilient IoV systems, particularly in smart city environments. It also introduces a novel Intrusion Detection System (IDS) with Artificial Intelligence (AI), smart contracts, and blockchain technology. These smart contracts ensure instant security with the utmost level of vulnerability through blockchain technology. In addition, we proposed a hybrid multi‐layered framework using Fog to conserve the resources at the vehicle level. We used mathematical proof to assess this framework. Merging blockchain, smart contracts, and AI into IoVs could increase human security by removing significant vulnerabilities.

Kisung Park, Ashok Kumar Das, Youngho Park

The integration of intelligent transportation systems (ITS) within the smart grid has significantly enhanced the reliability, efficiency, and security of vehicle-to-grid (V2G) services over the past decade, leading to increased research interest in this technology. Charging stations (CSs) utilize electric vehicles (EVs) to manage demand response and provide sustainable energy solutions. However, the transmission of information between EVs and CSs via public channels causes critical security vulnerabilities. Although much effort has been made to overcome the challenge of protecting security and privacy in V2G environments, these efforts have either been proposed based on a centralized architecture or do not ensure essential security requirements, such as self-sovereignty, reliable, and blockchain scalability. Furthermore, in decentralized network, it is difficult to provide reliable energy distribution because a malicious participant can easily try to inflate trading volumes and manipulate energy prices. In this paper, we propose a new blockchain-enabled, reliable, privacy-preserving scheme using decentralized identifiers (DIDs) for preventing energy wash trading in V2G networks called BAPS-DITS. BAPS-DITS guarantees to tackle the above challenges without a trusted third-party intervention. Additionally, we use informal and formal (mathematical) analysis to prove the security of BAPS-DITS and conduct a comparative analysis comparing the security properties, computational cost, and communication cost of BAPS-DITS to previous studies. Furthermore, we implement BAPS-DITS on a practical Ethereum network, demonstrating its efficiency and feasibility, showing that BAPS-DITS provides self-sovereignty, accountability, and blockchain scalability; thus, it is suitable for actual V2G environments.

Bin Wang, Zhao Tian, Fengxiao Tang, Heng Pan · 6 authors

Vehicle trajectory prediction plays a crucial role in IoT-based intelligent transportation systems, which can effectively address key issues, such as driving safety and multivehicle collaboration. However, the sensitivity of trajectory data and the reluctance of data holders to share it constrain the prediction model’s ability to capture vehicle behavior patterns in different scenarios. To address the above problems, we propose a blockchain-enabled asynchronous federated proximal policy optimization framework (BE-AFPPO) for the trajectory prediction of self-driving vehicles. First, we propose a curiosity proximal policy optimization (C-PPO) algorithm. The method utilizes a driven exploration strategy to actively motivate the intelligent agent to explore the unknown state space. The avoidance policy model reaches a local optimum when processing trajectory data. In addition, we design historical gated recurrent unit (GRU) and future GRU as input layers. The target’s historical motion features and future trajectory features are extracted, respectively. Then, various data is received through asynchronous federated learning. This model can fully learn the vehicle’s behavior patterns in different scenarios, which improves prediction accuracy. Based on this, we develop a blockchain-based dynamic group practical Byzantine fault tolerance (DG-PBFT) consensus algorithm. This enhances the credibility and integrity of the data while enriching the sources of trajectory data. Finally, we perform the experiments on the publicly available dataset nuScenes. The results demonstrate that the proposed method improves the robustness and accuracy of trajectory prediction.

Weijian Jiang, Cheng Cheng, Zhong Chen, Qiuling Yue

Optimistic Rollup is a blockchain scalability solution. However, it assumes that transactions are correct unless challenged by a challenger, which leads to the concept of a challenge period. If there is no challenge during this time, the user needs to wait until the end of the challenge period, which is very inconvenient for the user. This is because challengers and task publishers are self-interested and aim to maximize their own benefits, leading to internal incentive issues within Optimistic Rollup. Although zero-knowledge proofs can effectively address this issue, ZK rollups face challenges such as high computational complexity and the need for transaction-specific proofs. Optimistic rollups have low computational requirements and simple design, making the design of an effective incentive mechanism a good choice. This paper proposes a reward-based incentive model to encourage rational workers to actively verify transactions based on game theory. The rewards in this incentive model are related to a time factor, where earlier verification yields greater rewards, motivating verifiers to verify transactions more quickly. We simulate under various proportions of false declarations and the results show that our method could incentivize the workers effectively to exert their best efforts.

Zi Yang, Anthony O’Dwyer

No abstract is available for this record.

Danila Valko, Daniel Kudenko⋆

No abstract is available for this record.

GOPICHAND BANDARUPALLI

No abstract is available for this record.

Atharva Kalbhor, Rashmi S. Nair, Shraddha Phansalkar, Rahul Ganpatrao Sonkamble · 8 authors

The imbalance between parking availability and demand has led to a rise in traffic challenges in many cities. The adoption of technologies like the Internet of Things and deep learning algorithms has been extensively explored to build automated smart parking systems in urban environments. Non-human-mediated, scalable smart parking systems that are built on decentralized blockchain systems will further enhance transparency and trust in this domain. The presented work, PARKTag, is an integration of a blockchain-based system and computer vision models to detect on-field free parking slots, efficiently navigate vehicles to those slots, and automate the computation of parking fees. This innovative approach aims to enhance the efficiency, scalability, and convenience of parking management by leveraging and integrating advanced technologies for real-time slot detection, navigation, and secure, transparent fee calculation with blockchain smart contracts. PARKTag was evaluated through implementation and emulation in selected areas of the MIT Art Design Technology University campus, with a customized built-in dataset of over 2000 images collected on-field in different conditions. The fine-tuned parking slot detection model leverages pre-trained algorithms and achieves significant performance metrics with a validation accuracy of 92.9% in free slot detection. With the Solidity smart contract deployed on the Ethereum test network, PARKTag achieved a significant throughput of 10 user requests per second in peak traffic hours. PARKTag is implemented as a mobile application and deployed in the mobile application store. Its beta version has undergone user validation for feedback and acceptance, marking a significant step toward the development of the final product.

Christos N Kontos, Theodor Panagiotakopoulos, Achilles Kameas

Transportation plays an important role in urban development. Population growth and environmental burden have turned the efforts of cities globally towards smarter and greener mobility. Cooperative and Connected Automated Mobility (CCAM) serves as a concept with the power and potential to help achieve these goals building upon technological fields like Internet of Things, computer vision and distributed computing. However, its implementation is hindered by various challenges covering technical parameters such as performance and reliability in tandem with other issues, such as safety, accountability and trust. To overcome these issues, new distributed and decentralized approaches like blockchain and smart contracts are needed. This paper aims at identifying a comprehensive inventory of CCAM challenges and use it as a framework to describe methodologies using blockchain and smart contracts to address them. It provides a comparative analysis of the findings to draw useful conclusions and discuss future directions in CCAM and relevant blockchain applications. The paper contributes to intelligent transportation systems’ research by offering an integrated view of the difficulties in substantiating CCAM and providing insights on the most prominent blockchain and smart contract technologies that tackle them.

Chuanshan Huang, Tao Yan, Claudio J. Tessone

The increasing number of distinct blockchains has led to a growing need for data exchange and asset transfer across various isolated blockchains. To address this, cross-chain bridges have emerged as a critical mechanism for enabling interoperability and facilitating data and asset exchange across diverse blockchains. Among these bridges, the Layer-0 bridge stands out as a scalability solution that enhances blockchain performance at the foundational layer of data transition, without altering the blockchain's structure. Stargate is a notable Layer-0 Lock-and-Unlock cross-chain bridge that supports transactions across various EVM-based blockchains, with the highest Total Value Locked (TVL) among cross-chain bridges of the same kind. While previous cross-chain research has primarily focused on Layer-2 bridges, this study specifically examines Stargate and analyzes its dynamics as well as potential vulnerabilities. We collect transaction data of Stargate on six blockchains including Ethereum, Polygon, Binance Smart Chain, Avalanche, Arbitrum and Optimism. Our findings reveal the transaction patterns and evidence of exploitations of Stargate by investigating its transaction dynamics over time.

Lianna Zhao, Pietro Ferraro, Robert Shorten

In this paper we present the design for a smart-mask to mitigate the impact of an airborne virus such as COVID-19. The design utilises recent results from feedback control theory over a distributed ledger that have been developed to enforce compliance in a pseudo-anonymous manner. The design is based on the use of the IOTA distributed ledger. A hardware-in-the-loop simulation based on indoor positioning, paired with Monte-Carlo simulations, is developed to demonstrate the efficacy of the designed prototype.