The proliferation of Internet of Things (IoT) devices has ushered in a new era of connectivity, necessitating robust solutions for user authentication to address security and trust challenges. This paper explores an innovative approach to user authentication in IoT environments by leveraging the unique capabilities of Non-Fungible Tokens (NFTs) and 9NM (9NFTMANIA) tokens, with a specific focus on utilizing contract addresses. The proposed system involves the tokenization of user identities through the creation of contract addresses on blockchain networks. Each user is assigned a unique digital identity represented by an NFT or 9NM token, providing a tamper-proof association between the user and their cryptographic keys. Blockchain smart contracts are employed to manage authentication processes, dictating access control policies based on the user's contract address. The research underscores the importance of industry-wide collaboration to develop common standards for user authentication in IoT environments. By offering a comprehensive exploration of user authentication in IoT using contract address-based NFTs and 9NM tokens that are developed on Satoshi core based blockchain, this paper contributes to the advancement of secure and user-centric practices in the rapidly evolving landscape of IoT technology. The proposed framework not only enhances the overall security posture of IoT networks but also lays the foundation for a more transparent and interoperable authentication ecosystem. This paper has discussed the mechanism where web 3.0 based programming is made using Javascript, Python, ASP.NET and PHP for user authentication considering presence of smart contracts in user wallet.
Distributed ledger and blockchain technologies have revolutionized the way businesses imagine and operate across organizational boundaries. Non-repudiation plays a vital role in communications to overcome disputes and establish trust. The incorporation of blockchain-based messaging enables the usage of a decentralized network of nodes, surmounting the conventional methods. Key market players are emphasizing accessing partnerships with technology-based companies, thereby bolstering its regional demand over the forecast period. This chapter focuses on market analysis and forecasting for the forecast period of 2021–2030 in terms of revenue. Further, the chapter briefly focuses on the determinants such as drivers, restraints, and opportunities impacting the market for blockchain messaging apps in different applications and end-user segments.
Ziyuan Guo, Yiwei Wang, Anda Liang, Wyn Van Devanter · 5 authors
Traditional centralized database systems share many weaknesses, including the overhead of sharing medical documentation, data fragmentation, and susceptibility to centralized data attacks. Those problems would especially influence rare disease patient communities given their higher need for medical data interoperability and security. In this paper, we present an alternative approach to managing healthcare data that is tailored to the rare disease community. Specifically, we design and implement HealthBridge, a decentralized and interoperable mobile application with distributed ledger technology. The underlying permissioned network utilizes Hyperledger Fabric and has a modular design, empowering efficient data transactions directly between trusted entities with predefined smart contracts that regulate access permissions. For the application design, we focus on the needs of the rare disease community, prioritizing ease of use without compromising data security. In particular, our application provides a delegate feature, aimed at supporting rare disease patients with additional needs. Through this feature, if needed, patients can grant pre-defined access permissions to delegates through smart contracts. While the overall implementation of HealthBridge is still in the developmental stages, it presents a proof of concept and a promising system to support the underfunded rare disease community in terms of healthcare interoperability through a permissioned blockchain network.
Libertarian “exit” imaginaries project new social, political, and economic structures separate from existing institutions in which “sovereign individuals” can opt-in to the governing system that fits their ideals. This paper traces libertarian exit imaginaries through a variety of territorial and technological projects. Demonstrating how these imaginaries evolve, it describes a recent proposal to build a semi-autonomous, blockchain-based smart city in Nevada. Reflecting on these projects, the paper highlights (1) their inevitable failure as they confront reality, (2) their role as spectacle, spreading libertarian ideology, and (3) their real-life impacts on distinct places and communities even when they fail or never materialize.
With the development of the Internet of Things technology, the smart home industry is rapidly developing, and the collection and use of sensitive user data are also increasing. The issue of user privacy protection is becoming increasingly prominent and has received widespread attention. However, related research is still in its infancy. Firstly, the technical architecture of the smart home system was introduced, and an in-depth analysis was conducted on the privacy issues and the reasons for their increasing severity in the system. Secondly, based on the degree of use of privacy data such as user personal information and behavior, existing smart home systems were classified. Once again, the research status of different technologies in smart home privacy protection, such as access control, policy control, data minimization, network traffic obfuscation, federated learning, homomorphic encryption, and zero knowledge proof, was summarized and organized, and a comparative analysis was conducted on various technologies. Finally, corresponding suggestions were proposed for privacy protection in smart home systems.
Federated learning is an emerging distributed learning paradigm which brings an efficient and privacy-preserving intelligent model for the Internet of Vehicles (IoV). Unfortunately, federated learning is vulnerable to abnormal model attacks as it is hard to authenticate model parameters. Abnormal local models may slow down the convergence rate, reduce the accuracy of global models, and even deliberately control the global model in the attackers' chosen way. Furthermore, an abnormal global model may deduce sensitive information about vehicles and hinder the execution of genuine tasks. Therefore, in this paper, we propose a parameter-authentication federated learning (PAFL) scheme that can protect privacy of vehicles, such as driving habits, and defend against abnormal model attacks simultane-ously. Concretely, we equip the federated learning framework with the zero knowledge proof and Pedersen commitment to prove and authenticate the reliability of model parameters. Security and privacy analysis, as well as performance evaluation show that the PAFL scheme can successfully detect abnormal models with higher detection rate and achieve more secure global aggregation than existing representative schemes.
Mansoor Ahmed Jumani, Du Yujie, Muhammad Owais Khan
A key component of democratic governance in modern countries is the election process. But due to worries about things like polling booth capturing, data manipulation, and vote rigging, a general mistrust in the electoral process has evolved. Because they put election data under the authority of outside organizations, both the traditional and computerized voting systems now in use lack the required transparency. Voters have few options to verify that election administrators will carefully and accurately count their votes due to a lack of openness. To create an electronic voting (e-voting) system that upholds the ideals of fairness and security, it is imperative to take advantage of developing technology, particularly blockchain. When correctly applied, blockchain technology's public distributed ledger holds the potential to make tampering almost impossible. In this regard, our research suggests a decentralized electronic voting system that makes use of blockchain technology as a remedy to deal with the aforementioned issues. Through the elimination of the possibility of centralized election control, this approach seeks to reduce the dangers connected with conventional election procedures and increase voter confidence. The suggested method offers a tamper-proof, transparent, verifiable, economical, and reliable voting process through the distribution of control across several governing and non-governing bodies. This paper examines the development and implementation of such a blockchain-based electronic voting system, shedding insight on how it may enhance the openness and accessibility of democratic elections in contemporary societies.
New digital technologies generate large amounts of information. This data is processed by Service Providers in order to improve and develop new services and products, but also to fund themselves. However, processing personal data may result in the extraction of sensitive information, which, in turn, may lead to jeopardizing the users’ privacy. To mitigate this significant risk, the European Parliament and Council of the European Union elaborated the General Data Protection Regulation (GDPR). This regulation forces Service Providers to obtain Data Subjects’ explicit consent prior to collecting and processing their personal data. Nevertheless, the GDPR’s legislative text does not define how Service Providers must transparently demonstrate that they already have these consents. Moreover, most individuals do not know the rights they have over their personal data, neither does this regulation provide them with efficient methods to be aware of what third parties are doing with such data. In order to address this situation, we propose a lightweight blockchain-based GDPR-compliant personal data management platform. The new solution provides public access to immutable evidences that reflect the reached agreements between Data Subjects and Service Providers. In this way, Service Providers can effectively demonstrate that they are fulfilling the regulation, and Data Subjects are able to control and manage their personal data according to their legitimate rights. We have implemented the new system, and we have performed a detailed study which includes: GDPR-compliance, provided functionality, security and privacy issues, and the cost in terms of gas and US dollars of the different operations to be run on the blockchain.
Ricardo Martins Gonçalves, Miguel Mira da Silva, Paulo Rupino da Cunha
Abstract Blockchain has been gaining significant interest in several domains. However, this technology also raises relevant challenges, namely in terms of data protection. After the General Data Protection Regulation (GDPR) has been published by the European Union, companies worldwide changed the way they process personal data. This project provides a model and implementation of a blockchain system to store personal data complying with GDPR. We examine the advantages and challenges and evaluate the system. We use Hyperledger Fabric as blockchain, Interplanetary File System to store personal data off-chain, and a Django REST API to interact with both the blockchain and the distributed file system. Olympus has three possible types of users: Data Subjects, Data Processors and Data Controllers and a fourth participant, Supervisor Authority, that, despite not being an explicit role, can perform all verifications that GDPR mandates. We conclude that it is possible to create a system that overcomes the major challenges of storing personal data in a blockchain (Right to be Forgotten and Right to Rectification), while maintaining its desirable characteristics (auditability, verifiability, tamper resistance, distributed—remove single points of failure) and complying with GDPR.
The rise of digital globalization necessitates robust cross-border data sharing mechanisms, presenting challenges in security, privacy, and regulatory compliance. This paper introduces a novel blockchain-based framework to address these challenges, facilitating secure and efficient data exchange while meeting diverse international compliance requirements. Our approach combines advanced cryptographic techniques with smart contracts to create a dual-layered blockchain architecture. The first layer provides participant anonymity through zero-knowledge proofs, and the second ensures traceable, compliant data transactions. This solution streamlines compliance with varied data protection laws, offering a transparent and privacy-preserving platform for global data sharing initiatives. It promises significant benefits for entities engaged in multinational operations, enhancing security, simplifying regulatory adherence, and protecting user privacy.
This paper will explore the ability to implement Blockchain technology within electronic voting systems. The goal of this paper is to present an overview and high-level practical solution for this development. To achieve this, aim the Estonian electronic voting system will be used as a base which we will enhance with the functionalities of smart contracts. In the research it will be made a comparison between two of the biggest Blockchain platforms – Ethereum and Cardano, which will help the scientists choose the right system. In conclusion, a small piece of smart contact code will be presented in addition to the summary, placed at the end of the document.
Nidhi Desai, Damiano Di Francesco Maesa, Nishanth Sastry, Steve Schneider · 5 authors
This paper is concerned with helping people who are vulnerable during important transitions in life, such as 'coming out' as LGBTQIA+, experiencing serious illness, undergoing relationship breakdown etc. Rich sensor streams derived from so-called 'smart' Internet of Things (IoT) devices can be highly beneficial, for example in ensuring the safety of such individuals during their sensitive life transitions, or in providing functionality that can mitigate some of the difficulties faced by them. However, the data that needs to be extracted to provide these benefits can itself be highly sensitive and needs to be processed with safeguards to protect privacy. We develop scenarios that highlight issues arising from having to merge data streams from multiple devices, including data governance issues that are relevant when the sensors are owned by multiple individuals. We propose a "Transition Guardian" architecture that leverages "Smart Experts" written as smart contracts operating on homomorphically encrypted sensor data streams to provide real-time protection without disclosing their sensitive information. We have also implemented a proof-of-concept on the Ethereum protocol to validate our proposed solution.
Abstract Privacy concerns the majority of individuals, governments, and organizations that share data over dissimilar networks of nodes. Every kind of participant requires awareness of the data journey that unfolds inside a blockchain network with its own trustworthy rules of data management and accessibility. This paper provides a methodological approach on privacy for data sharing within blockchain environments. Specific technological aspects of blockchains that relate to on‐chain privacy such as network nature, party join, smart contracts, blockchain states, transactions, and ledger flows, are analysed with respect to the involvement and impact of privacy in distributed ledgers. A high‐level architectural approach is suggested that is intended to address significant privacy concerns on data sharing among different kinds of users in the context of blockchain networks deployment and the broader Web 3.0 ecosystem building. Simultaneously, many pertinent challenges are discussed regarding network nature, configurable privacy, ownership, confidentiality, secured computation, and data monetization that appear in the field and ought to be carefully tackled for the future mass adoption of privacy‐matured distributed ledgers that interconnect delivering the future Internet.
A donation-tracking system leveraging smart contracts and blockchain technology holds transformative potential for reshaping the landscape of charitable giving, especially within the context of Web 3.0. This paper explores how smart contracts and blockchain can be used to create a transparent and secure ledger for tracking charitable donations. We highlight the limitations of traditional donation systems and how a blockchain-based system can help overcome these challenges. The functionality of smart contracts in donation tracking, offering advantages such as automation, reduced transaction fees, and enhanced accountability, is elucidated. The decentralized and tamper-proof nature of blockchain technology is emphasized for increased transparency and fraud prevention. While elucidating the benefits, we also address challenges in implementing such a system, including the need for technical expertise and security considerations. By fostering trust and accountability, a donation-tracking system in Web 3.0, empowered by smart blockchain networks, aims to catalyze a profound positive impact in the realm of philanthropy.
Electronic communications security has gained a considerable significance in parallel with the increasing usage of the information and communication technologies. Being one of these technologies, distributed ledger technologies (DLTs), more specifically the blockchains, are regarded as a revolution which propose a new era, called “blockchain of things” following the era of “internet of things”. While DLTs promoted the business functionalities and compliance with information security obligations, it has also some vulnerabilities. By the DLTs the cost of intermediaries could easily be eliminated while at the same time assets/transactions are recorded and secured digitally. Nevertheless, this has simultaneously resulted in decentralised power/anarchy. Besides, majority of the studies focus on the contributions of the DLTs. This article aims to concentrate on the security aspect of this technology, which is often disregarded. Thus, after addressing fundamental characteristics of DLTs, it will unfold their tools and advantages in terms of compliance to information security obligations, then, exercise its vulnerabilities and related risks with respect to information security legal frameworks from over the world.
The challenge of safeguarding user data privacy becomes pronounced when private data is outsourced to cloud services, potentially exposing it to unauthorized access. The challenge of centralized storage of user data introduces heightened security risks and a dependence on a single authority, posing difficulties in safeguarding against internal breaches. This study is dedicated to advancing user privacy and data security, especially in scenarios involving the sharing of sensitive information within or across organizations, including small enterprises functioning in a distributed environment. The research introduces a consent management framework built on Blockchain technology, with a particular focus on user consent management. This framework is designed to prioritize the principles of privacy, security, scalability, and data integrity. It utilizes Hyperledger Fabric which is a permissioned distributed ledger solution, and incorporates Hyperledger Composer to establish and maintain a secure record of user data. To enhance the security of stored data, the framework incorporates the Interplanetary File System (IPFS) and employs a unique cryptographic public key encryption algorithm for data encryption. The overarching aim of this research is to establish a robust security solutions foundation against cyber threats by harnessing the inherent capabilities of blockchain technology, ultimately strengthening the security landscape for sharing user information.
Gaining significant attention within decentralized contexts, Federated Learning (FL) has been positioned as a highly desirable method for machine learning. By enabling multiple entities to train a shared model cooperatively, data privacy and security are preserved by Federated Learning. Harnessing inherent transparency and accountability of blockchain technology to trace and authenticate updates effectively in federated learning has transpired as an up-and-coming avenue to tackle data challenges related to confidentiality, protection, and reliability. This study examines the viability of federated learning and blockchain integration across multiple dimensions. The technological components of this integration., including incentive systems, consensus mechanisms, data validation, and smart contracts, are delved into. In the study, a novel proposed model for federated learning integrated with blockchain is designed and implemented. It is observed that the mean cypher size is 100 bytes for varying values of gradients. The average throughput recorded is 1.7 bytes per second, while the mean accuracy is 87.1% for 50 epochs.