Blockchain Papers

L. K. Bang, P. H. T. Trung, N. Ð. P. Trong, K. T. N. Ngan

No abstract is available for this record.

Antônio Espósito, Salvatore D’Angelo, Davide Casuccio

In recent years, cloud marketplaces have emerged as dominant platforms for cloud service procurement. These marketplaces, led by major providers such as Azure, Amazon Web Services, and Google Cloud, feature services exclusively available on their own platforms, introducing limitations for end users. This paper explores the convergence of cloud computing, blockchain, and semantics, envisioning a marketplace where cloud providers can offer their cloud services and cloud consumers can efficiently discover, procure, and potentially resell these services. Semantic representations streamline service discovery and composition, enhancing interoperability. Blockchain technology and non-fungible tokens play pivotal roles in establishing a fully decentralized marketplace characterized by data verification and immutability. This enables autonomous contract validation and execution between cloud consumers and cloud providers, reducing reliance on intermediaries. This innovative fusion promises to reshape the landscape of cloud service procurement, making it more transparent and independent.

Adla Sanober, Shamama Anwar

The rapid digitization of the healthcare sector has led to the generation of massive volumes of Electronic Health Records (EHRs), necessitating a robust, secure, and scalable system capable of efficiently managing and accessing this ever-growing data. Ensuring privacy, security, and scalability in managing voluminous and sensitive healthcare data, particularly when stored across various geographical locations, poses critical challenges that require innovative solutions. To address these issues, MeDiStore, a decentralized framework built on the Ethereum blockchain, is proposed. By integrating the InterPlanetary File System (IPFS), MeDiStore ensures scalable and secure storage while mitigating centralization risks and providing improved accessibility for EHRs. The framework leverages Elliptic Curve Cryptography (ECC) to encrypt and secure patient records, ensuring data ownership remains with the patient. To further enhance scalability, security, and reliability, of the blockchain network, the MeDiStore Trust Protocol, introduced a modified Proof of Stake (PoS) consensus mechanism that evaluates validators based on their network stake and reputation score, derived from their historical performance. Additionally, a Data Translation Layer is incorporated to ensure interoperability by converting EHRs into Fast Healthcare Interoperability Resources (FHIR) or Health Level 7 (HL7) systems without compromising security. Performance evaluation across 200 consensus rounds highlights metrics such as smart contract execution time, average IPFS file upload time, and reputation score behavior of validators. A comprehensive security analysis simulates Sybil attack scenarios, demonstrating the system's resilience through reputation-based validator selection. By integrating these factors, MeDiStore offers a scalable, secure, privacy-preserving, and interoperable solution tailored for efficient EHR management in the healthcare domain.

Alessandro Bigiotti, Gianmarco Mazzante, Leonardo Mostarda, Alfredo Navarra · 5 authors

The interest in blockchain for Industry 4.0 applications and the integration of the Industrial Internet of Things (IIoT) has grown considerably. This is due to the unique characteristics of blockchain, including the immutability of the distributed ledger, transparency, traceability of transactions, and security based on cryptographic techniques that certify the integrity of the data. So, the integration of blockchain can enhance data integrity, transparency, and security while eliminating trusted third parties. However, these characteristics make blockchains difficult to scale and typically involve high costs for a large number of transactions. It makes it difficult to manage large amounts of data which are generally produced in IIoT environments. Some recent results have demonstrated how the use of private blockchains can improve the issues of scalability and transaction costs. This paper addresses the following research question: Can blockchain technology, in its current state, be suitable for implementing industrial monitoring applications that use IIoT devices? Our objective is to propose a blockchain-based application integrated with IIoT devices in order to control the air and water pollution produced by industrial activities. The application we propose complies with current European regulations. Finally, we perform an empirical evaluation of the solution's performance to understand its applicability in real-world scenarios.

Nitima Malsa, Vimal Gupta, Rachna Jain, Sur Singh Rawat · 5 authors

The increasing global reliance on renewable energy, coupled with the strain on traditional electricity grids and limited access to power in rural areas, underscores the need for innovative solutions like Peer-to-Peer (P2P) energy trading platforms. This paper presents a hybrid Internet of Things (IoT) system designed for energy trading between prosumers (entities that both produce and consume energy), leveraging blockchain technology alongside AWS cloud infrastructure to ensure scalable and secure energy transactions. Our system integrates environmental sensors (solar, air) connected to microcontroller platforms like ESP32, facilitating real-time monitoring and management of energy production and consumption. Data from these devices is transmitted to AWS cloud architecture via IoT protocols such as MQTT and HTTP, ensuring secure, scalable storage, and reliable analysis. This robust architecture enhances real-time energy management, allowing prosumers to optimize energy usage. A key feature is the hybrid architecture combining decentralized Ethereum blockchain, which enables tamper-proof energy trading via smart contracts, and AWS cloud, which handles large-scale data processing. This dual system reduces reliance on centralized power grids, promotes energy independence, and supports decentralized energy markets. By using this platform, prosumers gain greater control over energy resources, promoting efficiency and sustainability while contributing to the future of decentralized energy economies.

Ajoe Sweetlin Jeena A, J M Gnanasekar

The Internet of Medical Things (IoMT) integrates interconnected medical devices and sensors to enable continuous patient monitoring and real-time healthcare delivery. Despite its transformative potential, IoMT systems face critical challenges related to data privacy, interoperability, latency, and security vulnerabilities inherent in centralized cloud architectures. Blockchain technology, with its decentralized ledger, cryptographic integrity, and smart contracts, has emerged as a promising solution to secure sensitive medical data while ensuring transparency and compliance with regulations such as HIPAA and GDPR. Concurrently, reinforcement learning (RL) techniques, especially advanced deep RL algorithms, facilitate intelligent, adaptive task offloading in fog-cloud computing environments to optimize latency, energy consumption, and resource allocation. This survey synthesizes twenty recent studies addressing blockchain-enabled privacy-preserving frameworks and RL-based task offloading mechanisms in IoMT. It critically evaluates architectural designs, cryptographic innovations including zero-knowledge proofs and quantum-resistant signatures, and RL methodologies for dynamic resource management. Key research challenges identified include the lack of standardized interoperability protocols across heterogeneous IoMT devices and blockchain platforms, the computational overhead of quantum-resistant cryptography on resource-constrained devices, and the opaque nature of RL models hindering clinical trust. Future research directions emphasize developing unified communication standards, lightweight post-quantum cryptographic schemes tailored for IoMT edge devices, and explainable RL frameworks to foster clinical adoption. Ultimately, this comprehensive analysis delineates a pathway toward robust, scalable, and secure IoMT ecosystems capable of delivering efficient, privacy-preserving healthcare services in complex digital infrastructures.

Manjula K. Pawar, Prakashgoud Patil, P. S. Hiremath

Blockchain technology is a nascent technology that possesses attributes such as immutability, security, transparency, openness, and decentralization. It is widely used in industry and business applications. Though it has the best features, it still suffers from some main characteristics, such as scalability and privacy. Scalability is measured through throughput (transactions per second), space, cost, and latency. Bitcoin and Ethereum, which are prominent blockchain platforms, carry out 7 and 20 transactions per second, respectively. This is much less than popular platforms such as VISA, PayPal, and Amazon, which perform thousands of transactions per second. Therefore, this article presents comprehensive study of scalability improving techniques for blockchain and case studies for improving scalability by using some of the techniques. The scalability of blockchain systems can be enhanced by on-chain, off-chain, and machine learning algorithms. The proposed methodology improves the scalability using off-chain technique for supply chain management and KNN classification for the healthcare domain.

Mohammed Naif Alatawi

The increasing reliance on cloud services demands advanced security mechanisms to protect sensitive data and ensure robust access control. This study addresses critical challenges in cloud security by proposing a novel framework that integrates blockchain-based smart contracts to enhance authorization and authentication processes. Smart contracts, as self-executing agreements embedded with predefined rules, enable decentralized, transparent, and tamper-proof mechanisms for managing access control in cloud environments. The proposed system mitigates prevalent threats such as unauthorized access, data breaches, and identity theft through an immutable and auditable security framework. A prototype system, developed using Ethereum blockchain and Solidity programming, demonstrates the feasibility and effectiveness of the approach. Rigorous evaluations reveal significant improvements in key metrics: security, with a 0% success rate for unauthorized access attempts; scalability, maintaining low response times for up to 100 concurrent users; and usability, with an average user satisfaction rating of 4.4 out of 5. These findings establish the efficacy of smart contract-based solutions in addressing critical vulnerabilities in cloud services while maintaining operational efficiency. The study underscores the transformative potential of blockchain and smart contracts in revolutionizing cloud security practices. Future research will focus on optimizing the system’s scalability for higher user loads and integrating advanced features such as adaptive authentication and anomaly detection for enhanced resilience across diverse cloud platforms.

Evangelos Stavropoulos, Ioanna Karampela, Arjun Singh, Maria K. N. Fountoulakis · 8 authors

—The European research project GHOST challenges the traditional cyber security solutions for the Internet of Things (IoT) sector by exploiting novel technologies, such as blockchain, to provide resilience and integrity of decision making on the communication exchange in a smart home context. When it comes to novel cyber security solutions for extremely heterogeneous environments like IoT and smart homes, the key focus is typically given to the understanding of network activities and elimination of suspicious traffic. The GHOST project adds an extra dimension to this approach by integrating blockchain technology at its core decision mechanism. On a daily basis, each GHOST installation is encountering malicious behaviour and suspicious IoT communications, where easy information sharing with other installations, as well as decentralised decision making, are mandatory features for the efficient protection of the end-user. GHOST's Smart Contracts (SC) are designed to tackle in an easy, yet productive way, the reporting on suspicious IP addresses which the IoT devices in a smart home are trying to communicate with. Two variations of blacklisting smart contracts are presented in this paper, covering a diverse spectrum of possible attack vectors while closely following the Privacy by Design (PbD) principles. A reputation scoring scheme for malicious IPs reporting is integrated in the SC, uncovering the implementation details on the penalisation of existing entries in case of malicious behaviour of reporting devices

Sadly Syamsuddin, Salama Manjang, Muhammad Bachtiar Nappu, Ady Wahyudi Paundu

This study proposes the integration of a hybrid Proof of Work/Proof of Stake (PoW/PoS) consensus mechanism with a Long Short-Term Memory (LSTM) model for anomaly detection in blockchain-based microgrids. The hybrid PoW/PoS model is designed to address common issues in blockchain systems, such as 51% attacks, double-spending, and high energy consumption, by optimizing energy usage and enhancing security. Simulation results show that the system can process transactions with an average throughput of 37.25 transactions per second (TPS), an average latency of 26.84 milliseconds per transaction (ms/tx), and extremely efficient energy consumption per transaction (0.01 kWh/tx). The LSTM model applied for anomaly detection achieves an 89.10% detection rate, a 0.00% false positive rate, and a 0.12 s recovery time, indicating the system's reliability in facing attacks. The hybrid PoW/PoS system demonstrates advantages in both energy efficiency and resilience to attacks compared to individual PoW and PoS systems. This research contributes to the development of safer, more efficient, and scalable blockchain-based microgrids by integrating Artificial Intelligence (AI) to strengthen the system against anomalies and threats.

Usha Sri Peddibhotla, C C Sobin, Randhir Kumar

Water usage serves as a key factor in boosting groundwater levels, alleviating water scarcity, and enhancing sustainable farming practices. Yet, ineffective oversight and accountability among stakeholders often undermine water resource management (WRM). To address this issue, we introduce a framework called S2WRM, which integrates a dual strategy: a game theory-based method and a blockchain-based system. In the game theory component, we apply a Stackelberg game, positioning the Water Resource Management Authority (WRMA) as the leader and industrialists and farmers as followers. Through this sequential game, dynamic pricing is determined as the leader establishes pricing strategies across various scenarios, analyzing usage trends to boost WRMA revenue. In addition, a blockchain incentive system is implemented, using ERC-20 contracts to mint and distribute tokens as rewards. This blockchain framework is built on the Ethereum platform, with Stackelberg simulations coded in Python. Analysis of different scenarios reveals key insights: first, blockchain-based incentives improve consumption oversight, fostering transparency in stakeholder supply chains second, WRMA revenue rises as blockchain reduces overhead costs tied to dynamic pricing and third, sustainability is advanced through token limits and penalties.

Yue Wang, Lincong Zhang, Bo Qian

Fog Radio Access Networks (F-RAN) offload computational processes to the network edge and transmit the processed results to the cloud, significantly reducing the load on cloud servers and improving service efficiency. While this architecture offers convenience, it inevitably raises severe privacy concerns. To address these issues, this paper proposes a blockchain-integrated F-RAN architecture. It employs smart contracts to ensure the security of user requests and introduces Zero-Knowledge Proof (ZKP) technology to minimize the frequent transmission of user private information across the network, thereby providing more effective privacy protection for users.

S Kumarswamy, A.S. Poornima

Blockchain technology has become an essential tool for enhancing reliability and security across several industries, including the healthcare sector. In this work, we propose and implement an Ethereum-based blockchain framework to decentralize electronic health records (EHRs) at Tumakuru Siddaganga Hospital. The system establishes an append-only chain of transaction blocks that guarantees the confidentiality, auditability, and integrity of patient health records. By design, only authorized healthcare professionals can access patient data, and even then, only with the patient’s explicit consent—ensuring a privacy-preserving access model. Our approach demonstrated a 40% reduction in data access delays and eliminated unauthorized access attempts through smart contract-based access control. The decentralized nature of the framework reduces reliance on centralized databases, significantly lowering the risk of data tampering and breaches. Additionally, the implemented consensus protocol ensures that only verified transactions are recorded, maintaining consistency across distributed nodes. Compared to traditional systems, our blockchain-based solution improved the traceability of health data access events by 100%, ensuring transparency and accountability. These findings validate that blockchain technology can substantially enhance data sharing, integrity, and patient control in modern healthcare systems.

Haoxiang Luo, Gang Sun, Jiacheng Wang, Hongfang Yu · 7 authors

Blockchain has emerged as a foundational element in establishing trust relationships within networks, demonstrating its reliability and efficacy across diverse applications. It can coordinate all nodes within the network independently of third-party entities for unified decision-making and consistency, and is traceable and immutable, making blockchain particularly attractive for communication networks. Wireless networks are an important part of network and communication systems, their flexibility significantly enhances the coverage of communication systems, making their integration with blockchain undeniably promising. This synergy between wireless communication and blockchain has culminated in the development of Wireless Blockchain Network (WBN). It offers a more trustworthy communication paradigm for the forthcoming sixth-generation (6G) wireless networks. This paper serves as a comprehensive tutorial on the integration of WBN and 6G, to establish trustworthy wireless networks. We begin by defining the WBN and exploring its advantages, underscoring its broad applicability in various 6G scenarios. Furthermore, we present the key technologies underpinning WBN and its critical performance metrics. Subsequently, we provide a series of case studies that illustrate the integration of WBN with 6G use cases, which underscore the utility and effectiveness of WBN in practical communication settings, indicating potential benefits for future networks. Finally, we summarize the current practical blockchain cases deployed by network operators and discuss the future direction of WBN. This tutorial is expected to provide an in-depth exploration of the fundamental principles, technological architectures, and practical applications on the integration of blockchain with 6G.

P. Bhuvaneshwari, Harold Robinson, M. Lakshmi

The pharmaceutical supply chain has a critical component, the Drug Traceability System, which tracks drugs from manufacturers for further processing and distribution. The integration of blockchain technology yields a secure solution for monitoring drugs throughout the supply chain management process. The paper proposes a novel Blockchain-enabled Secured Vertical Aggregation Algorithm (BSVA) by leveraging the Hyperledger model. The proposed model minimizes the requirement for a centralized authority to ensure privacy while also enhancing scalability to reduce response time in the process of managing transactions on the Blockchain. The Certificate Authority is used to maintain a secure data-sharing process. The robust aggregation is used for the local models to process the chain code, ensuring the successful execution of the secured transaction. The smart contract is deployed into a blockchain model as the block is stored and linked to the distributed Ledger. The decentralized framework is used by chain code, which guarantees that transactions are highly transparency. The performance parameters demonstrate the efficiency of the proposed model by enhancing the overall performance of the drug traceability system, as the proposed algorithm ensures the integrity of pharmaceutical products throughout the supply chain.

M. Rupasri

This review article examines the state of blockchain-enabled identity management in Internet of Things (IoT) networks, focusing on decentralized and secure mechanisms for device identification, authentication, and access control. Traditional centralized identity systems face limitations such as single points of failure, scalability bottlenecks, and vulnerability to breaches. We systematically survey recent literature on blockchain-based frameworks applied to IoT, categorizing approaches by blockchain platform, identity credential models, consensus mechanisms, and smart contract implementations. The analysis highlights key performance metrics such as system latency, throughput, resource overhead, and energy consumption, and compares existing prototypes deployed across diverse IoT scenarios. We assess the security and privacy implications, including resistance to spoofing, Sybil attacks, unauthorized access, data tampering, and insider threats. Additionally, the review identifies open research challenges such as managing identity lifecycle in constrained devices, achieving interoperability across heterogeneous networks, balancing decentralization with scalability, and integrating with emerging technologies like edge computing and zero-knowledge proofs. Finally, we offer recommendations for future research directions and practical deployment strategies to advance blockchain-based identity solutions in IoT ecosystems. Our comprehensive synthesis aims to guide researchers and practitioners in developing robust, scalable, and trustworthy identity frameworks using blockchain for the evolving IoT landscape.

Mohsen Rahmanikivi, Cristina Pérez‐Solà, Víctor Garcia-Font

This paper introduces “SmartBLock”, a novel protocol that integrates smart lock management with the Bitcoin blockchain. By employing blockchain technology, the SmartBLock protocol eliminates the need for centralized databases (reducing the risk of data breaches) and ensures accountability for all access events. Authentication is accomplished through Bitcoin's cryptographic signature scheme. Additionally, SmartBLock is an open and manufacturer-agnostic protocol, relying on the open and permissionless Bitcoin blockchain rather than proprietary tools or protocols. Given the limited computational capabilities of Internet of Things (IoT) devices, achieving this integration presents a significant challenge. This paper provides a comprehensive review of the state of the art in smart lock protocols, details the design of the SmartBLock protocol, presents a proof-of-concept prototype to validate its feasibility, and offers a meticulous analysis of its security, privacy, and traceability features. • Literature review on blockchain-integrated smart locks. • Propose a smart lock protocol on Bitcoin for immutable and transparent management. • Provide a demonstration that the protocol is secure, private, and transparent. • Build a PoC for the proposal on an IoT device and gather evidence of its feasibility.

Lianbo Ma, Ying Qian, Guo Yu, Zhetao Li · 8 authors

With advances in the edge computing (EC) and federated learning (FL) technologies in jointcloud, the edge FL service market has emerged recently and it requires trading edge resources between model requesters and data owners to complete FL tasks, which needs to incentivize sufficient data owners to participate in model training tasks. However, the limitations of resource trading and incentive design for edge FL service market have not been well addressed. In this paper, we propose a two-level blockchain-aided resource trading mechanism for encouraging appropriate edge servers to compete for dynamic FL tasks from the market while incentivizing data owners to participate in the FL tasks. At the upper level, we apply the deep learning-based reverse auction to model the dynamics of the task server selection process, with the aim of maximizing the total social welfare of the edge FL service market, where the edge server, as a seller, considers not only the data contribution of edge devices but also the cost of using blockchain when bidding. At the lower level, the edge servers offer rewards in exchange for the data owners’ participation, while the parameter aggregation is completed through the blockchain in a decentralized manner, which improves the FL’s robustness. Then, we utilize the Stackelberg game to model the dynamic process that the data owners compete for the servers’ revenue. We conduct extensive simulation experiments and the experimental results show that the proposed mechanism is able to get maximized social welfare and provide effective insights and strategies for the resource trading in the edge FL market to complete the federated training.

Mahmood Alsaadi, Hamad Aldawsari, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka · 9 authors

Efficient cryptographic verification methods are critical for secure communication in intelligent transportation systems (ITS), especially with the proliferation of Internet of Vehicles (IoV) devices powered by consumer technology. However, traditional zero-knowledge proofs often face efficiency limitations. This paper proposes a novel verifiable decryption scheme for IoV applications within ITS, leveraging the Module Learning with Errors (MLWE) and Module Small Integer Solution (MSIS) problems to address these challenges using widely available consumer technology platforms. The scheme integrates a compression function tailored for IoV devices and consumer technology in intelligent transportation systems, coupled with error estimation techniques, effectively mitigating disparities in equality relationships between the private data of the prover and verifier during the encryption and decryption process. This enables the prover to selectively share partial information, reducing discrepancies and transforming the verifiable decryption problem into a proof that a vector in the ring satisfies a linear relationship. A rigorous theoretical analysis demonstrates the schemes correctness, security, communication overhead, and computational complexity, reducing its soundness and zero-knowledge properties to the hardness assumption of the MSIS problem. The paper also recommends two parameter sets for different security levels that are feasible for deployment on consumer technology devices. To evaluate the schemes practicality, a C-language implementation was developed and tested on typical consumer technology hardware. Experimental results show significant advantages in proof size and computation time for a single ciphertext compared to existing schemes, making the proposed method highly efficient for ITS scenarios. This verifiable decryption scheme offers a post-quantum cryptographic solution that ensures secure, efficient, and scalable data exchange, aligning with the stringent demands of intelligent transportation systems and leveraging the accessibility of consumer technology.

Jianzheng Shi, Yue Wang, Terence T. Ow

As Web3 technology rapidly evolves, data management efficiency has become a critical challenge because of the decentralized nature of blockchain technology, which requires extensive computational and storage resources. Existing research highlights that decentralized consensus mechanisms in blockchain, such as proof-of-work (PoW) and proof-of-stake (PoS), lead to significant data redundancy, storage limitations, and latency issues, making data management efficiency complex. Moreover, the need for security and immutability in blockchain data storage exacerbates these challenges as the system scales and unique challenges unfold in maintaining efficient data management. Using Monte Carlo simulation, we analyzed the model’s behavior under various scenario by manipulating key variables such as network latency, node distribution, data block size, consensus mechanism efficiency, and storage redundancy levels. Our findings indicate that consensus mechanism efficiency has the most significant impact on overall data management performance, followed by network latency and node distribution. Interestingly, although data block size shows a moderate impact, storage redundancy levels have a relatively minor effect on efficiency. These simulation studies provide insights into optimizing consensus protocols and improving network infrastructure in enhancing the efficiency of Web3 data management.

Ahmad Ghazal, Zhou Ge, Anita Shao, Guoxin Kang · 12 authors

No abstract is available for this record.

Hongmin Gao, Yuhe Zhang, Libo Wang, Zhiquan Liu · 5 authors

With the widespread adoption of digital twin (DT) technology in cross-domain data sharing scenarios, ensuring secure and efficient search over encrypted data has become a significant challenge. This article proposes a blockchain-based searchable encryption scheme tailored for DTs, supporting privacy-preserving keyword search, verifiable data access, and decentralized trust establishment. The scheme collects real-time data streams from digital sensors and devices to construct unified DT records for intelligent analytics and decision-making. The scheme integrates lightweight searchable encryption with blockchain-based trapdoor delegation and ciphertext-level indexing, enabling secure and low-complexity keyword matching. By introducing a delegated trapdoor mechanism, users can authorize repeated keyword queries via a single token, thereby minimizing communication and computational costs. Additionally, a blockchain-driven key generation protocol based on distributed voting eliminates reliance on centralized authorities and ensures transparent, auditable key management. Moreover, encrypted records are stored in IPFS, resolving the storage limitations of blockchain and preserving verifiable data availability. The trapdoor delegation records and result verification parameters are committed on-chain, enabling query correctness checking and traceable access control. Under the ciphertext indistinguishability (CI) and trapdoor indistinguishability (TI) security models, the proposed scheme is formally proven to achieve CI and trapdoor privacy, providing resistance to adaptive insider keyword guessing attacks. Compared with existing schemes, it offers stronger privacy guarantees with lower overhead, supporting scalable and secure DT data sharing.

Ahmad Mutahhar, Tariq Jamil Saifullah Khanzada, Muhammad Farrukh Shahid

Large-scale events, such as festivals and public gatherings, pose serious problems in terms of traffic congestion, slow transaction processing, and security risks to transportation planning. This study proposes a blockchain-based solution for enhancing the efficiency and security of intelligent transport systems (ITS) by utilizing state channels and rollups. Throughput is optimized, enabling transaction speeds of 800 to 3500 transactions per second (TPS) and delays of 5 to 1.5 s. Prevent data tampering, strengthen security, and enhance data integrity from 89% to 99.999%, as well as encryption efficacy from 90% to 98%. Furthermore, our system reduces congestion, optimizes vehicle movement, and shares real-time, secure data with stakeholders. Practical applications include fast and safe road toll payments, faster public transit ticketing, improved emergency response coordination, and enhanced urban mobility. The decentralized blockchain helps maintain trust among users, transportation authorities, and event organizers. Our approach extends beyond large-scale events and proposes a path toward ubiquitous, Artificial Intelligence (AI)-driven decision-making in a broader urban transit network, informing future operations in dynamic traffic optimization. This study demonstrates the potential of blockchain to create more intelligent, more secure, and scalable transportation systems, which will help reduce urban mobility inefficiencies and contribute to the development of resilient smart cities.

Carlos Beis-Penedo, Francisco Troncoso‐Pastoriza, Rebeca P. Dı́az Redondo, Ana Fernández Vilas · 6 authors

The rapid growth of Internet of Things (IoT) devices and applications has led to an increased demand for advanced analytics and machine learning techniques capable of handling the challenges associated with data privacy, security, and scalability. Federated learning (FL) and blockchain technologies have emerged as promising approaches to address these challenges by enabling decentralized, secure, and privacy-preserving model training on distributed data sources. In this paper, we present a novel IoT solution that combines the incremental learning vector quantization algorithm (XuILVQ) with Ethereum blockchain technology to facilitate secure and efficient data sharing, model training, and prototype storage in a distributed environment. Our proposed architecture addresses the shortcomings of existing blockchain-based FL solutions by reducing computational and communication overheads while maintaining data privacy and security. We assess the performance of our system through a series of experiments, showing its potential to enhance the accuracy and efficiency of machine learning tasks in IoT settings.