Alvaro Gómez Vieites, Christian Delgado-von-Eitzen, Diego Estévez Garcia
For years, combining the immutability associated with blockchain technology with the European Union’s General Data Protection Regulation (GDPR) has been considered a practically unsolvable conflict due to the very nature of blockchain and the GDPR. This article presents the GAVIN project (GDPR-Compliant Blockchain-Based Architecture for Universal Learning, Education and Training Information Management), a pioneering initiative that overcomes this challenge through an innovative technical and legal approach to trusted digital academic certification. Developed by atlanTTic (University of Vigo) and funded by the European Union, GAVIN proposes a scalable architecture that combines off-chain storage, encrypted Hash-Based Message Authentication Code (HMAC) anonymization, access notarization, and blockchain-based access control. The legal validation of the working prototype under development demonstrates that blockchain decentralization is compatible with GDPR compliance. The model is presented as a replicable reference for institutions wishing to leverage distributed ledger technologies without compromising personal data protection. This paper details the legal design, technical architecture, and compliance mechanisms, offering a practical framework for implementing decentralized systems with privacy by design.
Blockchain technology has emerged as a promising solution for improving traceability across global supply chains, offering tamper-proof records and increased transparency.However, concerns related to data privacy, confidentiality, and interoperability continue to hinder widespread adoption.This paper proposes a comprehensive framework addressing these key challenges by combining privacy-preserving techniques-such as permissioned ledgers, zero-knowledge proofs, and verifiable credentials-with industry-driven data standards (GS1 EPCIS, W3C Verifiable Credentials).We first review the landscape of blockchain traceability solutions and outline critical requirements from regulatory and operational perspectives.Next, we detail our proposed privacy-preserving and interoperable architecture, incorporating off-chain storage, role-based permissions, and selective disclosure mechanisms to accommodate the diverse needs of modern supply chains.We illustrate these concepts through a high-level system design, accompanied by implementation considerations.Our evaluation highlights that successful adoption depends on carefully balancing transparency and confidentiality, supplemented by robust governance structures and standard APIs.The paper concludes by discussing future directions for blockchain traceability, emphasizing scalability, user-centric design, and cross-chain interoperability as critical enablers of a global, privacypreserving supply chain ecosystem.
Traditional centralized scholarship evaluation processes typically require students to submit detailed academic records and qualification information, which exposes them to risks of data leakage and misuse, making it difficult to simultaneously ensure privacy protection and transparent auditability. To address these challenges, this paper proposes a scholarship evaluation system based on Decentralized Identity (DID) and Zero-Knowledge Proofs (ZKP). The system aggregates multidimensional ZKPs off-chain, and smart contracts verify compliance with evaluation criteria without revealing raw scores or computational details. Experimental results demonstrate that the proposed solution not only automates the evaluation efficiently but also maximally preserves student privacy and data integrity, offering a practical and trustworthy technical paradigm for higher education scholarship programs.
The traditional voting process, whether paper-based or electronic, is often criticized for its lack of transparency, susceptibility to fraud, and dependence on centralized authorities. Blockchain technology, particularly in the Web3 ecosystem, provides a decentralized, secure, and tamper-proof solution for digital voting. This paper explores how blockchain can enhance election integrity by leveraging decentralized applications (DApps), smart contracts, and cryptographic security. The proposed system employs Ethereum-based smart contracts to automate vote casting and tallying while ensuring voter privacy through zero-knowledge proofs. Decentralized Identity (DID) is integrated for secure authentication, preventing double voting and identity fraud. The paper discusses system architecture, security considerations, scalability challenges, and real-world applications of blockchain voting, highlighting how Web3 can transform democratic elections.
The digitization of democratic processes promises greater accessibility but presents challenges in terms of security, privacy, and verifiability. Existing electronic voting systems often rely on centralized architectures, creating single points of failure and forcing too much trust in authorities, which contradicts democratic principles. This research addresses the challenge of creating a secure, private e-voting system with minimized trust dependencies designed for the most versatile personal device: the smartphone. We introduce SmartphoneDemocracy, a novel e-voting protocol that combines three key technologies: the emerging European Digital Identity (EUDI) Wallet for Sybil-resistant identity verification, Zero-Knowledge Proofs for privacy-preserving validation, and a peer-to-peer blockchain (TrustChain) for a resilient, serverless public bulletin board. Our protocol enables voters to register and cast ballots anonymously and verifiably directly from their smartphones. We provide a detailed protocol design, a security analysis against a defined threat model, and a performance evaluation demonstrating that the computational and network overhead is feasible for medium- to large-scale elections. By developing and prototyping this system, we demonstrate a viable path to empower citizens with a trustworthy, accessible, and user-controlled digital voting experience.
Jul 11, 2025·The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Abstract. Environmental surveillance, emergency response, and smart city planning all require the use of geospatial data, which includes satellite imagery, cartographic records, and real-time GPS coordinates. The high sensitivity and value of location-specific information make it unsafe to store and transmit it through conventional, centralized means, which can result in privacy breaches, unauthorized manipulations, and potential misuse. This paper aims to design and implement a secure, blockchain-based framework that blends AES (Advanced Encryption Standard) and RSA (Rivest–Shamir–Adleman) key management, which addresses these challenges. The aim is to guarantee strong data confidentiality by using symmetric encryption, and to use public-key cryptography for granular access control and secure key distribution. The proposed system uses Ethereum smart contracts to connect encrypted data references to a decentralized ledger, ensuring tamper resistance and auditability. In the proposed system, a Python-based FastAPI backend is responsible for data ingestion, cleaning, encryption, and blockchain interaction, while a React frontend can upload datasets, generate encryption keys, and retrieve access permissions. Modular microservices and well-defined APIs can seamlessly integrate various components, such as data processing scripts and on-chain contract logic, during development. The system's scalability is demonstrated by evaluating its performance against various dataset sizes, which involves metrics such as encryption overhead, blockchain transaction costs, and smart contract execution times. The practical usability of the system in actual scenarios is demonstrated through user acceptance testing, which is crucial for adoption in resource-limited environments. The results show the proposed crypto-enhanced blockchain framework can significantly enhance geospatial data security while still maintaining operational efficiency. Integration with zero-knowledge proofs may be explored in future work to enhance privacy, mitigate energy costs through alternative consensus algorithms, and enhance resilience in multi-network ecosystems through cross-chain interoperability.
Crowd-sensing is considered a robust model for data collection, yet with challenges related to data availability and privacy. Traditional techniques such as data encryption and anonymization may not fully mitigate these issues, since anonymized data can still be traced back to individual users, and the volume of data generated can reveal user identities. This paper introduces a system that employs smart contracts and blockchain technology to manage crowd-sensing campaigns. The smart contract oversees user subscriptions, data encryption, and decentralized storage, creating a secure data marketplace. Incentive mechanisms within the smart contract promote user participation. Simulation results validate the system’s feasibility, emphasizing the importance of user engagement for data credibility and the impact of geographical data scarcity on rewards.
The rapid evolution of smart cities has led to transformative advancements through the integration of IoT devices, sensors, and data-driven systems, yet has simultaneously exposed critical vulnerabilities in cybersecurity, data integrity, and trust management. This research proposes a Decentralized Trust Framework that leverages blockchain technology, AI-driven threat detection, and a Lightweight Adaptive Proof-of-Stake (LA-PoS) consensus mechanism to address these challenges. The framework integrates three key layers: a Blockchain Layer for decentralized trust and immutability, a Cybersecurity Layer employing cryptographic standards and AI-based anomaly detection, and a Data Integrity Protocol Layer for real-time synchronization and tamper-proof data validation. Performance evaluations indicate the framework achieves a threefold increase in transaction throughput, a 30% reduction in latency, and enhanced energy efficiency compared to traditional blockchain systems. Security metrics highlight a 98.2% threat detection rate and a substantial reduction in false positives, while resource optimization nearly doubles IoT device battery life. The framework demonstrates applicability in critical smart city use cases, including smart traffic management, energy systems, and public safety, providing secure, scalable, and efficient solutions for urban infrastructures. Despite these advancements, challenges such as interoperability among heterogeneous systems, computational overhead for IoT devices, and policy adoption persist. Future research will focus on optimizing interoperability protocols, incorporating quantum-resistant cryptographic techniques, and extending the framework to emerging domains such as autonomous systems and smart healthcare. The proposed framework provides a robust foundation for building sustainable, resilient, and trustworthy urban ecosystems, bridging gaps in current smart city technologies.
Background: Cryptocurrency is a digital decentralized currency that enables peer-to-peer transactions without the involvement of intermediaries, using blockchain technology to ensure security and transparency. These emotions can help understand when and what behavioral intentions toward cryptocurrency adoption are necessary. These insights contribute to the growing literature on fintech adoption in emerging economies and provide valuable guidance for policymakers and investors formulating cryptocurrency regulations in Nepal. Objectives: It aims to investigate the influence of perceived usefulness, perceived ease of use, trust, and perceived risk constructs attached to an individual's intention to be involved in cryptocurrency transactions. It finally aims to study the relationships among these variables and their effect on cryptocurrency adoption in the Nepal context. Methods: The study uses a quantitative descriptive design and snowball sampling alone to extract information from cryptocurrency users in Nepal. A structured online questionnaire was used to gather 272 responses and analyzed using correlation and regression to investigate the significance of the proposed hypotheses. Results: Findings show that perceived usefulness, ease, or trust significantly and positively influence behavioral intention toward cryptocurrency adoption, while perceived risk harms adoption because users worry about market volatility, regulatory uncertainty, and security threats. Despite the government's legal restrictions, many Nepalese citizens are still involved in cryptocurrency transactions, seeing it as a source of financial benefit and investment opportunity. Conclusion: The study attests that perceived usefulness, perceived ease of use, and trust motivate behavior toward adopting cryptocurrency, while perceived risk provides a barrier. This enlightens policymakers on balanced regulatory measures that address risks while encouraging innovation in digital finance. These findings would provide valuable implications for policymakers, financial institutions, and technology developers in outlining the future of cryptocurrency regulation and adoption strategies. JEL Classification: D14, E42, G41
Blockchain technology presents transformative opportunities for secure personal data sharing, particularly in healthcare, finance, and identity management. However, its widespread adoption is constrained by challenges such as limited scalability, privacy concerns, and conflicts with regulatory frameworks like the General Data Protection Regulation (GDPR). This study introduces a novel hybrid framework that integrates the InterPlanetary File System (IPFS) for off-chain storage with Zero-Knowledge Proofs (ZKPs) to enhance privacy, ensure regulatory compliance, and reduce on-chain storage demands. Employing a Design Science Research (DSR) methodology, the framework was developed and validated using Ethereum and Hyperledger Fabric, guided by insights from a systematic review of 180 studies from 2018 to 2023. Empirical evaluations revealed a 75% reduction in blockchain storage, 98% GDPR compliance, and zk-SNARK proof verification times below one second. The framework also enables GDPR-compliant erasure by removing encrypted off-chain data while preserving on-chain auditability. Despite challenges such as IPFS latency and trusted setup complexities, the solution offers a scalable and privacy-preserving architecture applicable to real-world domains, especially in privacy-critical environments like healthcare and finance by resolving blockchain’s GDPR compliance paradox.
Syed Abrar Ahmed, Ricardo Correia, Anderson Oliveira do Carmo, Henrique Martins
Increasingly, across geographies, citizens are requiring access to and control of their health data. This paper examines the "Logging Component" proposed by the European Health Data Space (EHDS) regulation and its crucial role in facilitating secure and transparent access to electronic health records (EHR) and health data. We analysed the proposal for the five elements of the Logging Component (LC): identification of data accessors, identification of data subjects, categorisation of accessed data, temporal logging, and data origin tracking. Explored how these elements contribute towards enhanced accountability and compliance in health data management. We experimented with distributed ledger technology (DLT) to support the "data origin tracking element", reaching the demonstration level which can be presented. We used hybrid DLT to develop a system for immutable storage of access logs, and for using smart contracts to maintain a self-governing decentralised access control list (ACL) directly integrated with EHR and PHR systems. We found that the LC is more than a regulatory requirement. It can serve as a framework for the integration of advanced technologies, e.g. DLT and others, increasingly mature and potentially foundational to building new networks of trust among stakeholders, while ensuring data privacy in cross-border and intra-border healthcare scenarios. The study also identified shortcomings of the LC, such as the absence of "purpose logging", which was conceptualised and proposed. This study contributes to the understanding of how logging mechanisms can enhance transparency and accountability in electronic health record systems within the European healthcare landscape, but with potential usefulness for the "Global EHR". In conclusion, our findings suggest that the successful implementation of the five elements of the Logging Component are mandatory and can benefit from mature advance technologies, but the sixth element proposed by us would be critical for achieving the EHDS's broader objectives of harmonised health data sharing in Europe and beyond while maintaining robust security standards.
The article presents a comprehensive analysis of the transition from traditional centralized digital identity models to an innovative decentralized paradigm based on block-chain technologies and zero-knowledge proofs (ZKP). It highlights the fundamental problems of existing systems that rely on centralized registries, passwords, and social logins. Such approaches create significant vulnerabilities, including risks of data breaches, mass surveillance, and manipulation, as centralized intermediaries act as sole controllers of personal information, depriving users of control over their data. In response to these challenges, the article discusses the concept of Decentralized Identity (DID). This model enables individuals to own, store, and control their digital credentials independently, without involving intermediaries. The key technological components of this ecosystem include Verifiable Credentials (VC), Digital ID Wallets, and Decentralized Identifiers (DID), which are typically stored on a block-chain to ensure immutability and security. A triadic trust model involving the Issuer, Holder, and Verifier is described, allowing data verification without direct contact with the issuing organization. Special attention is given to the concept of Self-Sovereign Identity (SSI) as a specific philosophy within DID that emphasizes user autonomy, data minimization, and privacy by design. Unlike the broader DID concept, in the SSI model, the user makes the final decision regarding the disclosure of their data. A central technology ensuring privacy in decentralized systems is zero-knowledge proofs (ZKP). ZKP allow the validation of the truthfulness of a statement without revealing the underlying information. The article provides a detailed analysis of the benefits of using ZKP in the context of DID, including selective attribute disclosure (e.g., proving legal age without revealing the date of birth), minimizing the amount of shared data, preventing correlation and user activity tracking, as well as creating reputation systems that preserve anonymity. Practical application scenarios such as private electronic voting and confidential medical data protection are examined. The paper also addresses standardization, which is key to ensuring compatibility and widespread adoption of DID solutions. Leading initiatives such as W3C Verifiable Credentials, the Decentralized Identity Foundation (DIF), and projects like Hyperledger Indy and Aries are mentioned. Examples of advanced implementations already in use are provided: Polygon’s zkKYC for private verification in DeFi, the Sismo protocol for creating anonymous reputation badges in Web3, and Evernym’s SSI platform based on Hyperledger Indy. In conclusion, it is emphasized that the combination of DID and ZKP forms a new paradigm for digital identity management focused on security and user autonomy. Despite challenges related to usability complexity, key loss risk, and legal uncertainty, the technology is actively evolving and moving from conceptual to practical application, which may eventually become the foundation for a global sovereign digital identity.
This study investigates the integration of the Portuguese Citizen’s Card authentication with Hyperledger Fabric blockchain technology, addressing the challenge of bridging traditional government-issued digital identities with blockchain-based systems, particularly focusing on reducing barriers to Web3 adoption for users unfamiliar with decentralized technologies. The proposed solution leverages the Autenticação.gov Software Development Kit (SDK), developed by the Portuguese Agency for Administrative Modernization (AMA) to create a secure bridge between the Citizen’s Card authentication system and Hyperledger Fabric's permissioned blockchain framework. The study examines how this approach can facilitate the development of transparent, tamper-proof authentication systems suitable for critical applications such as e-voting and digital government services, and also feasible for on-premises systems. The findings suggest that integrating existing digital identity systems with blockchain technology can promote wider acceptance of decentralized solutions while maintaining security, privacy, and accessibility standards required for public sector applications.
Nikos Papatheodorou, George Hatzivasilis, Nikos Papadakis
Self-sovereign identity (SSI) is an emerging model for digital identity management that empowers individuals to control their credentials without reliance on centralized authorities. This work presents YouGovern, a blockchain-based SSI system deployed on Binance Smart Chain (BSC) and compliant with W3C Decentralized Identifier (DID) standards. The architecture includes smart contracts for access control, decentralized storage using the Inter Planetary File System (IPFS), and long-term persistence via Web3.Storage. YouGovern enables users to register, share, and revoke identities while preserving privacy and auditability. The system supports role-based permissions, verifiable claims, and cryptographic key rotation. Performance was evaluated using Ganache and Hardhat under controlled stress tests, measuring transaction latency, throughput, and gas efficiency. Results indicate an average DID registration latency of 0.94 s and a peak throughput of 12.5 transactions per second. Compared to existing SSI systems like Sovrin and uPort, YouGovern offers improved revocation handling, lower operational costs, and seamless integration with decentralized storage. The system is designed for portability and real-world deployment in academic, municipal, or governmental settings.
Ahmed Sayed M. Metwally, Yazeed Alhumaidan, Saad Alzahrani, Mohamed H. Abdelati
Implementing artificial intelligence (AI) and blockchain technology in management systems transforms traditional libraries into advanced information centers that are data-driven and effectively managed. While these technologies enhance efficiency and operational capabilities, they also present two critical challenges: data privacy and ethical concerns. This study examines the role of AI and blockchain in library management, focusing on issues related to data privacy and ethical challenges that arise from their use. It also offers best practices to ensure safe implementation. The research adopts a comprehensive mixed-methods approach, involving qualitative interviews and quantitative surveys to identify these challenges within the system architecture, assess the effectiveness of current designs, and propose a complete framework using privacy-preserving technologies. This framework incorporates innovative cryptographic techniques, including homomorphic encryption, differential privacy, and zero-knowledge proofs, providing a novel model for the ethical use of AI in libraries. The findings indicate that robust data protection, transparency, and accountability are essential to building trust in AI-powered library services.
In an increasingly digital world, establishing secure and reliable methods for verifying identity has become a critical priority across sectors such as finance, healthcare, education, and e-governance. Traditional authentication mechanisms—relying on passwords, personal identification numbers, and physical documents—are increasingly susceptible to fraud, data breaches, and user inconvenience. This paper presents a multi-modal biometric framework for digital identity management, integrating facial recognition and fingerprint verification to enhance accuracy, reduce fraud, and ensure user-centric security. The proposed system includes modules for data acquisition, preprocessing, feature extraction using Convolutional Neural Networks (CNNs) and minutiae detection, score-level fusion, and final authentication decisions. Security and privacy are ensured through AES-256 encryption, differential privacy techniques, and decentralized blockchain-based data storage. This research contributes a scalable, privacy-aware, and highly accurate digital identity model capable of addressing challenges such as interoperability, user trust, and regulatory compliance. Future enhancements include the integration of additional biometric modalities and deployment in mobile and IoT environments.
The rapid adoption of Federated Learning (FL) in privacy-sensitive domains such as healthcare, IoT, and smart cities underscores its potential to enable collaborative machine learning without compromising data ownership. However, conventional FL frameworks face several critical challenges: high computational overhead on edge devices, significant communication latency due to frequent model updates, vulnerability to model and data poisoning attacks, and limited privacy-preserving mechanisms that expose systems to inference risks. These issues hinder the scalability, efficiency, and trustworthiness of FL in real-world, large-scale deployments-particularly in domains like Electronic Health Records (EHR) management, where data sensitivity is paramount. To address these challenges, this paper introduces the Enhanced Privacy-Preserving Blockchain-Enabled Federated Learning (EPP-BCFL) framework, which integrates blockchain with hybrid privacy mechanisms and intelligent aggregation strategies. The architecture comprises three layers: (1) an Edge Nodes Layer for on-device learning; (2) a Federated Aggregation Layer using Secure Multi-Party Computation (SMPC) and Differential Privacy (DP); and (3) a Blockchain Layer with a lightweight PoS + BFT consensus mechanism. Experimental evaluation on CIFAR-10 demonstrates 95.2% accuracy, a 43% reduction in communication latency, a 37% decrease in computational cost, and robust defense against data/model poisoning and adversarial attacks. Attack resilience improved accuracy from 72.5 to 93.2%, while privacy budget tuning achieved 90.3% accuracy at ε = 1.0. Compared to state-of-the-art models, EPP-BCFL exhibits superior performance in terms of security, scalability, and support for edge device heterogeneity, validating its applicability in secure EHR management.
Abstract— This research introduces a Blockchain-based Decentralized Application designed to address these issues. Leveraging Ethereum smart contracts and decentralized storage via IPFS, the application ensures secure peer-to-peer communication, immutable data storage, and enhanced transparency. By eliminating the need for centralized intermediaries, the Blockchain-based Decentralized Application empowers users, prioritizes data privacy, and fosters trust. This research introduces a Blockchain-based Decentralized Application designed to address these issues. Leveraging Ethereum smart contracts and decentralized storage via IPFS, the application ensures secure peer-to-peer communication, immutable data storage, and enhanced transparency. By eliminating the need for centralized intermediaries, the Blockchain-based Decentralized Application empowers users, prioritizes data privacy, and fosters trust. Index Terms—Distributed Ledger Technology(DLT), Smart Contracts, InterPlanetary File System(IPFS), Cryptographic Security.
S. M. Dilip Kumar, Namrta Tanwar, Namrta Tanwar, Aakarsh Chandna · 5 authors
The blockchain technology has disrupted the earlyage digital banking through concepts like bitcoin and ether [1,3].In this study, some major elements of the blockchain technology are examined-decentralized networks, smart contracts, cryptographic techniques, and consensus mechanisms of Proof of Work and Proof of Stake usage-and understanding how they contribute to safe, peer-to-peer transactions without intermediaries [2,5].Bitcoin can do no more than about seven transactions a second (TPS) is a very paltry competition of an impressive 30 to 40 TPS of Ethereum.This depicts the ongoing scalability challenges that need to be tackled by initiatives linked with Ethereum 2.0 and the Lightning Network [4,9].While most industries, apart from banking, have effectively made their blockchain applications and transparency useful-Supply Chain Management, Healthcare, and DeFi-currently poses challenges of transaction speed limitations, the vagueness of regulations, and energy consumption by mining [8].Emerging trends include Non-Fungible Tokens (NFTs), Central Bank Digital Currencies (CBDCs), and privacy enhanced through zero-knowledge proofs.There is hope for excellent feedback on the future of the blockchain from these and other initiatives yet to come into reality.
Smart contracts have been a topic of interest in blockchain research and are a key enabling technology for Connected Autonomous Vehicles (CAVs) in the era of Web 3.0. These contracts enable trustless interactions without the need for intermediaries, as they operate based on predefined rules encoded on the blockchain. However, smart contacts face significant challenges in cross-contract communication and information sharing, making it difficult to establish seamless connectivity and collaboration among CAVs with Web 3.0. In this paper, we propose DeFeed , a novel secure protocol that incorporates various gas-saving functions for CAVs, originated from in-depth research into the interaction among smart contracts for decentralized cross-contract data feed in Web 3.0. DeFeed allows smart contracts to obtain information from other contracts efficiently in a single click, without complicated operations. We judiciously design and complete various functions with DeFeed , including a pool function and a cache function for gas optimization, a subscribe function for facilitating data access, and an update function for the future iteration of our protocol. Tailored for CAVs with Web 3.0 use cases, DeFeed enables efficient data feed between smart contracts underpinning decentralized applications and vehicle coordination. Implemented and tested on the Ethereum official test network, DeFeed demonstrates significant improvements in contract interaction efficiency, reducing computational complexity and gas costs. Our solution represents a critical step towards seamless, decentralized communication in Web 3.0 ecosystems.
Marco A. C. da Silva, Luis Hideo Vasconcelos Nakamura, Geraldo P. Rocha Filho, Luís Veiga · 5 authors
With the advancement of technologies for data registration in distributed networks, the concern of users and developers of computerized solutions with the privacy of sensitive data has increased. Thus, this work addresses a conceptual solution for an ontology-based framework so that any entity willing to provide a service using Distributed Ledger Technology (DLT) networks can model the set of privacy attributes of its system according to the business rules of its service. The solution proposed in this work encompasses the development of an architecture aimed at providing computational support for the privacy design of the actors involved in the offering and consumption of services implemented in DLTs. The architecture also includes a framework called ONSPRIDE, which uses previously stored domain ontologies to translate business rules into requirements and privacy. We conducted a proof of context by comparing the performance of two Hyperledger Fabric networks. For this purpose, we conducted a controlled experiment in which both networks operate a smart contract that manages attendance records for outdoor events. The main difference between the networks is that one uses a Certificate Authority (CA) to issue access certificates, while the other issues certificates manually. We compared the results obtained through the reports generated by the Hyperledger Caliper tool. In addition, the performance of the initialization and connection of agents in a Self-Sovereign Identity system was measured. The results of this study provide valuable insight that can help developers choose the most suitable ledger type for their Hyperledger projects and support decision-making regarding adopting a Self-Sovereign Identity system.
This article explores the complex intersection of technological innovation and privacy considerations in cloud identity management systems. It traces the evolution from traditional authentication methods to sophisticated cloud-based frameworks that now incorporate adaptive authentication, federation protocols, biometric verification, and behavioral analytics. While these advances enhance security and user experience, they simultaneously introduce profound privacy challenges regarding data collection scope, user profiling, and cross-platform tracking. The article examines how regulatory frameworks, industry self-regulation, and stakeholder perspectives shape the governance landscape of digital identity. Drawing on interdisciplinary research, the article reveals how trust formation in digital environments correlates with transparency practices and how trust erosion carries consequences beyond immediate user relationships. Looking forward, emerging technologies like decentralized identity and zero-knowledge proofs offer promising privacy-preserving alternatives, while evolving market dynamics and user expectations create both challenges and opportunities. The article concludes with actionable recommendations for designing and implementing identity systems that achieve an optimal balance between robust security, operational efficiency, and respect for individual privacy rights—a critical imperative for sustainable digital ecosystems in increasingly connected societies.
Tarek Galal, Valeria Tisch, Katja Assaf, Andreas Polze
Railways provide a critical service and operate under strict regulatory frameworks for implementing changes or upgrades. Despite their impact on the public, these frameworks do not define means or mechanisms for transparency towards the public, leading to reduced trust and complex tracking processes. We analyse the German guideline for railway-infrastructural modifications from proposal to approval, using the guideline as a motivating example for modelling decisions in processes using digital signatures and zero-knowledge proofs. Therein, a verifier can verify that a process was executed correctly by the involved parties and according to specification without learning confidential information such as trade secrets or identities of the participants. We validate our system by applying it to the railway process, demonstrating how it realises various rules, and we evaluate its scalability with increased process complexities. Our solution is not railway-specific but also applicable to other contexts, helping leverage zero-knowledge proofs for public transparency and trust.