Manuel J. Fernández Iglesias, Christian Delgado‐von‐Eitzen, Luis Anido
The growing importance of traceability in supply chains requires robust, transparent, and efficient systems to ensure the integrity and authenticity of product journeys. This paper presents a comprehensive characterisation and data model for a generic blockchain-based traceability system, highlighting its implementation using smart contracts on Ethereum-compatible networks, as the Ethereum Virtual Machine (EVM), with its pioneering implementation of smart contracts and its extensive ecosystem; it provides a robust environment for developing decentralised applications. We discuss the advantages of using blockchain technology to notarise traceability activities, ensuring immutability and transparency by exploring two main scenarios, namely one where hash keys (i.e, cryptographic digests) are stored on-chain while detailed data remain off-chain, and another where all traceability data are fully stored on-chain. Each approach is evaluated for its impact on scalability, privacy, storage efficiency, and operational costs. The hash key method offers significant advantages in reducing blockchain storage costs, enhancing privacy, and maintaining data integrity, but it depends on reliable off-chain storage. Conversely, the full on-chain approach guarantees data immutability but at a higher cost and lower scalability. By combining these strategies, a balanced solution can be achieved, leveraging the strengths of both methods to provide a reliable, efficient, and secure blockchain-based traceability system, which is illustrated with a practical implementation to support traceability in the timber sector in Galicia, Spain. This paper aims to provide valuable insights for researchers and practitioners looking to implement or enhance traceability systems using blockchain technology, demonstrating how smart contracts can be effectively utilised to meet the demanding requirements of modern supply chains.
Laura Ricci, Barbara Guidi, Andrea Michienzi, Andrea Tagarelli · 5 authors
Web3 describes the next generation of the Internet, built on top of various technologies, such as Blockchain Technology, Semantic Web, etc. Web3 proposal claims a vision of the Internet that can cut the intermediation of Big tech companies by completely decentralizing the web through blockchain technology, which enables the integration of cryptocurrencies and tokens in many social media platforms, currently referred to as Blockchain Online Social Media (BOSMs) platforms. These give the possibility both to reward users for their social actions and to define Non-Fungible Tokens (NFTs), digital assets representing real-world objects like art, collectibles, music, game items, videos, and even tickets creating a new form of decentralized finance, called Social Finance (SocialFi). BOSMs give users the possibility to monetize and tokenize their social influence, and they act as the common ground for the sale or transfer of NFTs. In this paper, we propose an overview of AWESOME, a framework for advanced analysis of Web3 BOSMs, specifically conceived to suit their nature based on intertwined and stratified social and economic contexts. We highlight the characteristics of the framework by describing the objectives and we present the preliminary results. Furthermore, the paper proposes a classification of current Web3 BOSMs, which improves the literature by taking into account the changes and the new applications of Web3 Social Media, which now include Virtual Worlds and Gaming platforms.
This paper presents an innovative Web 3.0 authentication technique, designed for a user-centric internet environment. Addressing the rising demand for authentication techniques suitable for Web 3.0, it defines the essential features of such systems and introduces a new approach using smart contracts. This approach utilizes mother and child tokens in conjunction with the lock smart contract to ensure secure authentication. The approach is thoroughly tested against various security threats, including man-in-the-middle, replay, and brute-force attacks, and its practicality is evaluated on Ethereum-based networks.
Crowd-sensing has emerged as a powerful data retrieval model, enabling diverse applications by leveraging active user participation. However, data availability and privacy concerns pose significant challenges. Traditional methods like data encryption and anonymization, while essential, may not fully address these issues. For instance, in sparsely populated areas, anonymized data can still be traced back to individual users. Additionally, the volume of data generated by users can reveal their identities. To develop credible crowd-sensing systems, data must be anonymized, aggregated and separated into uniformly sized chunks. Furthermore, decentralizing the data management process, rather than relying on a single server, can enhance security and trust. This paper proposes a system utilizing smart contracts and blockchain technologies to manage crowd-sensing campaigns. The smart contract handles user subscriptions, data encryption, and decentralized storage, creating a secure data marketplace. Incentive policies within the smart contract encourage user participation and data diversity. Simulation results confirm the system's viability, highlighting the importance of user participation for data credibility and the impact of geographical data scarcity on rewards. This approach aims to balance data origin and reduce cheating risks.
The evolution of mobile technology has produced new methods and policies for organisations to process data and communicate. Bring your own device (BYOD), which allows employees to bring their own personal devices to work and access organisational resources for work purposes, is one such new policy. However, as this practice poses significant risks, organisations must implement commensurate security measures to protect their integrity. This paper aimed to mitigate these risks by proposing a decentralized and unassailable security control solution tailored to the BYOD environment. The proposed architecture leveraged business blockchain with smart contracts (SCs) to automate policy compliance and strictly adhere to organisational rules and regulations. The research demonstrated that this approach effectively reduces access control (AC) threats and enhances security policies and management. The findings highlighted that the implementation of SCs within a blockchain framework significantly improves the security of the BYOD environment by minimising the risks of unauthorised access, data breaches, and insider threats. Additionally, SCs enable organisations to establish decentralised and tamper-proof security control systems, reducing the dependence on centralised authorities and bolstering overall system integrity.
In the increasingly digitized world, the privacy and security of sensitive data shared via IoT devices are paramount. Traditional privacy-preserving methods like k-anonymity and l-diversity are becoming outdated due to technological advancements. In addition, data owners often worry about misuse and unauthorized access to their personal information. To address this, we propose a secure data-sharing framework that uses local differential privacy (LDP) within a permissioned blockchain, enhanced by federated learning (FL) in a zero-trust environment. To further protect sensitive data shared by IoT devices, we use the Interplanetary File System (IPFS) and cryptographic hash functions to create unique digital fingerprints for files. We mainly evaluate our system based on latency, throughput, privacy accuracy, and transaction efficiency, comparing the performance to a benchmark model. The experimental results show that the proposed system outperforms its counterpart in terms of latency, throughput, and transaction efficiency. The proposed model achieved a lower average latency of 4.0 seconds compared to the benchmark model’s 5.3 seconds. In terms of throughput, the proposed model achieved a higher throughput of 10.53 TPS (transactions per second) compared to the benchmark model’s 8 TPS. Furthermore, the proposed system achieves 85% accuracy, whereas the counterpart achieves only 49%.
Cryptocurrencies’ popularity is growing despite short-term fluctuations. Peer-reviewed research into trust in cryptocurrency payments started in 2014. While the model created then, is based on proven theories from psychology and supported by empirical research, a-lot has changed in the past 10 years. This research finds that the original model is still valid, but it is extended to capture the current situation better. A quantitative methodology is used to validate the updated model proposed. The results from the quantitative survey show that (1) personal innovativeness in technology and (2) finance, influence (3) disposition to trust. Disposition to trust influences six variables from the specific context of the payment. Three variables related to the cryptocurrency itself are (4) stability in the value, (5) transaction fees, and (6) reputation. Institutional trust is influenced by (7) regulation, and (8) payment intermediaries. The last contextual factor is (9) trust in the retailer. The six variables from the context influence (10) trust in the payment which, finally, influences (11) the likelihood of making the cryptocurrency payment.
Blockchain technology provides a technical solution for the challenges faced by e-government, such as low efficiency, excessive energy consumption, and lack of trust mechanisms. It can promote the establishment of a more efficient and high-quality government service system, thereby enhancing the public trust of the government. Although blockchain technology provides theoretical innovation to traditional governance structures with its decentralization, consensus mechanisms, and enhanced trust, its impact and ability to transform existing governance structures still have limitations in practical applications. Based on an in-depth analysis of the concept and application boundaries of blockchain, this article explores its value in the field of e-government. At the same time, it systematically proposes strategic suggestions to promote the development of blockchain technology in the field of e-government from multiple aspects such as institutional construction, technical standardization, and professional talent cultivation, in response to its limitations and application risks. By accelerating technology research and development and standard construction, strengthening high-level promotion, optimizing promotion competition mechanisms, and conducting rooted research, the application and promotion of blockchain in government governance can be accelerated, laying a solid foundation for building a future intelligent and transparent government service model.
Richard Richard, Muhammad Ammar Marsuki, Gading Aryo Pamungkas, Felix Irwanto
The surge in cryptocurrency usage has increased reliance on cryptocurrency wallet applications. However, the usability, security, and feature richness of crypto wallets require significant enhancements. This research aims to identify critical factors that should guide the future design of mobile cryptocurrency wallets. The first step was to collect user reviews on several popular crypto wallets as the dataset. A total of 5,466 mobile wallet-related reviews from mobile application stores were filtered and analyzed. A machine-learning approach was used to cluster the user reviews. The analysis shows that customer issues are divided into four main themes: domain-specific challenges, security and privacy concerns, misconceptions, and trust issues. A software process assessment was also conducted to examine the current state of crypto wallets in terms of security, usability, and feature richness. Around 21 crypto wallet platforms were explored and assessed. Based on the thematic analysis and software process assessment, feature recommendations are proposed to address these shortcomings and enhance the credibility of mobile cryptocurrency wallets.
Federated Learning (FL) is a technique in the field of machine learning that prioritizes privacy by allowing collaborative model training without revealing data. This article explores the basics of FL and its importance in protecting data privacy in sectors such as healthcare, finance, and industrial engineering. By using data sources FL enables the development of strong and adaptable AI models without centralizing sensitive information. We delve into the methodologies behind FL including secure multiparty computation, differential privacy, and homomorphic encryption. Additionally, we look at the ways FL is used, such as speeding up medical research improving financial security and streamlining industrial processes. The challenges related to FL - like communication diverse data distributions and scalability - are also addressed. Lastly, we discuss trends, in FL that focus on enhancing privacy techniques and complying with regulations. This thorough overview highlights how FL can revolutionize AI advancement while upholding privacy standards. Keywords: Federated Learning, Privacy Preservation, Decentralized Machine Learning, Secure Multiparty Computation, Differential Privacy, Healthcare AI, Industrial Engineering, Data Silos, Collaborative Learning.
Decentralizing crowdsourcing through blockchain technology eliminates the need for trusted third-party intermediaries that may introduce social biases in data aggregation, thereby enhancing transparency and ensuring appropriate rewards for workers. However, open permissionless blockchain platforms typically disclose all transaction data on public ledgers, which compromises the privacy and anonymity of workers and encourages free-riding. Blockchain-based anonymous crowdsourcing systems have recently emerged, offering anonymity but requiring identity registration for workers and a trusted setup for key generation. These systems in general, fail to support anonymous payments, potentially compromising worker identities. In this paper, we integrate anonymous payments into crowdsourcing, eliminating the need for identity registration and trusted setup, thus fostering open and anonymous participation from any worker. Our solution utilizes the decentralized anonymous payment system framework, such as Zerocoin, and includes staking mechanisms for participation in crowdsourcing as well as efficient one-out-of-many zero-knowledge proofs. Additionally, our empirical evaluations reveal that the system incurs moderate and practical gas costs.
Digitalization has far-reaching yet under-researched impacts on state–society relations. This article addresses this gap and explores digitalization as a driver of change to social contracts. The conceptual framework explains how it changes (a) the state’s duty to grant protection, provision, and participation in exchange for legitimacy; (b) the modes of state–society interaction; and (c) the contracting parties with respect to their location and their relative power position. Based on a literature review and recent developments in digitalization, the article then discusses how this plays out in the MENA region. It shows that digital surveillance by authoritarian regimes often dominates over the states’ duty to protect their citizens. Spaces for political participation increase through social media and online platforms but often fail to translate into ‘offline’ mobilization. Digitalization can improve public service provision, but only for digitally-connected citizens. Thus, digitalization tends to enhance the relative power positions of MENA states even if states themselves partly depend on external actors for access to and control over digital technologies. Overall, digitalization is an important, structural driver of change to social contracts but pre-existing state–society relations and governance framework conditions lead to either more inclusive or rather more authoritarian social contracts.
In this era of rapid technological evolution and ever-changing regulatory landscapes, this chapter explores the transformative journey of data accountability. Beginning with an exploration of data accountability in cloud environments, the narrative sets the stage by defining its scope and surveying the current research landscape. Navigating the intricate terrain of regulatory compliance in the cloud, the discussion unfolds with a focus on prominent regulations such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA). A comparative analysis sheds light on the varying compliance requirements and the consequential impact on Cloud Service Providers. This chapter then navigates through diverse accountability models in cloud computing, reevaluating the shared responsibility model and introducing advanced frameworks. It advocates for the integration of accountability directly into the fabric of cloud service level agreements. An in-depth examination of advanced auditing and monitoring mechanisms follows suit, featuring real-time auditing tools, log analysis techniques, and insights into monitoring tool kits offered by major cloud platforms like Google Cloud and AWS. Grounding the discourse in practicality, the narrative showcases case studies that illuminate successful implementations of data accountability. These narratives not only celebrate achievements but also outline encountered challenges and the strategies employed for effective mitigation. A comparative analysis of accountability practices in the realms of Google Cloud and AWS enriches the practical insights. Looking ahead, the narrative concludes with a forward-thinking exploration of future trends in data accountability. It envisions the application of machine learning for anomaly detection, the integration of blockchain and distributed ledger technologies, and anticipates the evolving landscape of regulatory frameworks. As a compass for professionals, researchers, and policymakers, this text serves as an invaluable guide through the dynamic intersection of technology and data governance.
M. Albrecht, Matilda Backendal, Daniele Coppola, Kenneth G. Paterson
Nextcloud is a leading cloud storage platform with more than 20 million users. Nextcloud offers an end-to-end encryption (E2EE) feature that is claimed to be able “to keep extremely sensitive data fully secure even in case of a full server breach”. They also claim that the Nextcloud server “has Zero Knowledge, that is, never has access to any of the data or keys in unencrypted form”. This is achieved by having encryption and decryption operations that are done using file keys that are only available to Nextcloud clients, with those file keys being protected by a key hierarchy that ultimately relies on long passphrases known exclusively to the users. We provide the first detailed documentation and security analysis of Nextcloud's E2EE feature. Nextcloud's strong security claims motivate conducting the analysis in the setting where the server itself is considered malicious. We present three distinct attacks against the E2EE security guarantees in this setting. Each one enables the confidentiality and integrity of all user files to be compromised. All three attacks are fully practical and we have built proof-of-concept implementations for each. The vulnerabilities make it trivial for a malicious Nextcloud server to access and manipulate users' data. We have responsibly disclosed the three vulnerabilities to N extcloud. The second and third vulnerabilities have been remediated. The first was addressed by temporarily disabling file sharing from the E2EE feature until a redesign of the feature can be made. We reflect on broader lessons that can be learned for designers of E2EE systems.
Blockchain’s decentralization, transparency, and tamper‐resistance are celebrated properties for auditability and trust, yet they collide with core data protection duties under the EU General Data Protection Regulation (GDPR). This manuscript analyzes the principal compliance challenges that arise when blockchain processes personal data and proposes a practical, design-oriented framework to address them. First, we synthesize legal and regulatory positions on what counts as “personal data,” the difference between anonymization and pseudonymization, and the implications of the right to erasure, data protection by design and by default, allocation of controller/processor roles, and international data transfers. We then map these requirements to blockchain architectures (public permissionless, public permissioned, and private permissioned) and data patterns (on-chain, off-chain, hybrid). Building on recent guidance from the European Data Protection Board (EDPB) and national authorities, we outline concrete technical and governance controls—off-chain storage and on-chain commitments, keyed hashing, encryption/key-revocation strategies, chameleon-hash/redactable-ledger designs, selective-disclosure credentials/zero-knowledge proofs, and robust consortium governance—to reduce risk and improve demonstrable compliance. Applying a six-step assessment methodology to three realistic use cases (NFT profile registry, supply-chain provenance, and consortium KYC), we show that while no single pattern fully reconciles immutability with erasure, practicable combinations can align processing with GDPR’s principles of minimization, purpose limitation, storage limitation, and accountability. The paper concludes with a prioritized checklist for engineering “compliance-by-design” blockchains, and delineates scope and limitations for practitioners and researchers.
A. Bendada, Mouhamed Amine Bouchiha, Mourad Rabah, Yacine Ghamri-Doudane
Current blockchain-based reputation solutions for crowdsourcing fail to tackle the challenge of ensuring both efficiency and privacy without compromising the scalability of the block chain. Developing an effective, transparent, and privacy-preserving reputation model necessitates on-chain implementation using smart contracts. However, managing task evaluation and reputation updates alongside crowdsourcing transactions on-chain substantially strains system scalability and performance. This paper introduces RollupTheCrowd, a novel blockchain-powered crowdsourcing framework that leverages zkRollups to enhance system scalability while protecting user privacy. Our framework includes an effective and privacy-preserving reputation model that gauges workers' trustworthiness by assessing their crowdsourcing interactions. To alleviate the load on our blockchain, we employ an off-chain storage scheme, optimizing RollupTheCrowd's performance. Utilizing smart contracts and zero-knowledge proofs, our Rollup layer achieves a significant 20x reduction in gas consumption. To prove the feasibility of the proposed framework, we developed a proof-of-concept implementation using cutting-edge tools. The experimental results presented in this paper demonstrate the effectiveness and scalability of RollupTheCrowd, validating its potential for real-world application scenarios.
Emerging technology products would benefit hugely from the introduction of voluntary standards. Those, however, are costly to adopt, especially for smaller players. Further, popularizing the standards and policing compliance is difficult. This paper makes the case for empowering the users to police the voluntary standards. Utilizing Distributed Ledger Technology (DLT), more precisely Directed Acyclic Graph will reduce the costs of recording and storing individual measurements for each product allowing users to claim compensation every time the product doesn't perform according to specifications. The paper discusses the specific requirements the product should meet to utilize DLT as compliance tool. It is also discussing the specific legal issues that entail from empowering users to police standard compliance.
Zoe L. Jiang, Min Xie, Hanlin Chen, Yijian Pan · 9 authors
Smart contracts have been widely used to develop decentralized applications on account-based blockchain. The privacy issues of smart contracts have also received attention from researchers, and many privacy-preserving schemes and applications have been proposed. However, most existing schemes cannot achieve flexible conversion between private and public data. And the overly secure privacy-preserving scheme directly makes the regulation impossible. To mitigate these limitations, we propose a flexible privacy-preserving smart contracts with regulation (RPSC) system over the account-based blockchain. We first design a two-layer commitment structure that enables the fine-grained privacy protection (identity anonymity and data confidentiality) and flexible data state transitions. Then we combine a public-key encryption scheme with a zk-SNARKs scheme to achieve regulation property while keeping user's identity from others. Moreover, we prove that our scheme is secure, including privacy, soundness and traceability. Finally, we integrate RPSC into an account-based blockchain and implement two applications to evaluate the system performance. The evaluation results show our system performs effectively in practical settings.
This research evaluates how blockchain technology transforms data security functions, especially regarding privacy protection. The rise of decentralized systems led to Blockchain emerging as an answer for resolving traditional data security problems from breaches to centralization risks. This research investigates blockchain technology, which advanced from its initial cryptocurrency framework into an all-encompassing data protection solution. Research shows that Blockchain improves privacy through encryption methods and distributed operations. A qualitative research approach enables examination of blockchain solutions with privacy components alongside analysis of zero-knowledge proofs and decentralized storage facilities. Technology solutions provide users with comprehensive data visibility and reduce exposure to unauthorized intruders and free them from central control systems. The adaptive security structure of blockchain technology functions as the industry-leading answer to privacy breaches by establishing strengthened data protection protocols for all operational activities.
Linda Weigl, Tamara Roth, Alexandre Amard, Liudmila Zavolokina
User-centricity in e-government is a double-edged sword. While it helps governments design digital services tailored to the needs of citizens, it may also increase the burden on users and deepen the digital divide. From an institutional perspective, these fundamental conflicts are inevitable. To better understand the role and effect of user-centricity in e-government, this paper analyses academic literature on user-centricity and public values. The analysis leads to three main insights: First, there is a conflict in citizen representation that may result from the normative dominance of decision-makers. Second, we identify an accountability conflict that can prevent user-centric innovation from thriving in a highly institutionalized environment. Third, we identify a pluralism conflict that emerges from a clash between the reality of a diverse society and the assumed homogeneity of actors. The need to address these conflicts increases with rapid technological innovation, such as distributed ledger technologies, artificial intelligence, and trust infrastructures. These technologies put the user at the center stage and permeate aspects of social life beyond government. In response to these insights, we outline suggestions for further research and practice.
Open access
E-Government and Public Services
Privacy, Security, and Data Protection
Innovative Approaches in Technology and Social Development
Gulshan Kumar, Rahul Saha, Manish Gupta, Tai-hoon Kim
The correctness and the true validated data in Human Resource Management (HRM) are important for organizations as the data plays an impactful role in recruiting, developing, and retaining a skilled workforce. On one hand, the validated data in an organization helps in recruiting legitimate skillful employees; on the other hand, keeping the employee's data safe and maintaining privacy laws such as compliance with the General Data Protection Regulation (GDPR) is also an organization's responsibility. Besides, transparency in human resource management operations is crucial because it promotes trust and fairness within an organization. The present HRM systems are centralized in nature and their verifiable credential system is ineffective; this leads to the intentions of internal data sabotage or internal threats. Besides, the organizations' biases also become more prominent. In this paper, we address the above-mentioned problems with a blockchain framework for HRM to utilize the privacy of data access through a Privacy Information Retrieval (PIR) process. To be specific, our proposed framework called Blockchained piR of resOurces as humaN (BRON) , is the first blockchain framework to show an effective mechanism to access data from organizations globally without hampering privacy. BRON uses a generalized user registration process to use the services of data access and in the background, it uses Zero-Knowledge Proofs (ZKPs) for global verification and PIR for privacy-based data retrieval. More specifically, credential verification and ZKP-based PIR are the highlights of our proposed BRON. Another interesting aspect of BRON is the use of Proof-of-Authority (PoA) to validate the anonymity and unlinkability of any HR operation. Finally, BRON has also contributed with a smart contract to incentivize the employees. BRON is very generic and easily be customizable as per the HR requirements. We run a set of experiments on BRON and observe that it is successful in providing privacy-assured data access and decentralized human resource data management. Overall, BRON provides 30% reduced latency and 35% better throughput as compared to the existing blockchain solutions in the direction of HRM.