Abstract Online presence is becoming an important part of everyday's life and online communities may represent a significant source of engagement for the elderlies. Nevertheless, many may struggle to be online due to a lack of expertise, and a decentralised architecture may provide a solution by removing intermediaries, such as a webmaster, while not requiring expensive cloud solutions. However, issues concerning accessibility, security, and user experience have to be tackled. The paper focuses mainly on three issues: providing a human‐readable domain, moderating content, and creating a reward system based on user reputation. An architecture is proposed based on Ethereum and Swarm. Smart contracts provide an automated set of rules to handle enterprise registration, content creation, and decision‐making process, while Swarm serves both as distributed storage and the web host. Besides, in combination with Ethereum Name Service, Swarm provides a secure, distributed, and human‐readable point of access to the web interface. The paper also describes an innovative two‐token system where one token is meant to be a trustworthy reputation metre and the other is a spendable coin to get rewards. The final result is a fully decentralised, authenticated and moderated platform where users can aggregate and share their content presentations on the Internet.
Oliver Hasan Padmanegara, Ratna Komala Putri, Reva Yuliani, Eryadi K. Masli
This study explores the implementation of blockchain-based identity management in the Republic of Indonesia as well as analyse its impact on privacy and security risks. The methodology chosen for this research is a qualitative study using exploratory approach. The research propose six research propositions and a blockchain-based architecture model for citizen’s personal identity management. This research finds that blockchain could mitigate privacy and security risks, should it be implemented by the Ministry of Home Affairs of the Republic of Indonesia.
“Code is law” became a buzz term in Web3 and blockchain reality. Despite the term being already used much earlier by Lawrence Lessig in the year 2000 in his book titled “Code and Other Laws of Cyberspace,” when the internet and Web2 were emerging, the rise of smart contracts and complex algorithmic power made the term genuinely resonate with the (idealised) Web3 reality. The entrainment of technological solutionism in the brains of members of society gives an impression that a world governed by algorithms will be a fairer one. However, research has shown that many members of society are not standard statistical representations of the majority and whilst algorithmic governance leaves room for “standard deviation,” individuals that fall outside this standard deviation are, in fact, very disadvantaged. There are numerous research papers as well as popular science books that address the issue of algorithmic bias and unfairness in Web 2. The proponents of blockchain and web3 technology argue that with a DAO-governed, decentralised society, problems of biased algorithmic governance are solved as power and decision-making are decentralised, and members use their governance tokens to collectively decide on the law encoded in the smart contracts that are the ultimate law enforcement apparatus. Web3 promises a shift of power from governments and corporations to people and token holders, arguing it will make a Web3-governed society fairer. This paper is based on decoding this promise and using Althusser’s model of a state apparatus to show how the power relations changed in Web2 and Web3 realities. It shows that Web3 promises of the code becoming the law were already present in the Web2 discourse and discovers a model of an ideological apparatus power struggle between states and Web2 giants. Next, the power relations in the blockchain society are researched, starting from the idealised model of decentralised, token-holder governed power, which regulates the governments and corporations, to a discussion on what the actual power relations and struggles might result from encoding the law in the smart contract. Research shows that in Web3, “code is law” society. There will be power struggles and opposition on a vertical and horizontal level. The vertical struggle is the power enforcement (originally in the hands of the state in Althusser’s (1970) model between the code and individuals, governments and corporations not willing to conform with the code-enforced law or falling outside the standard deviation of statistics-based AI algorithms hence being disadvantaged by the smart contract enforced laws. The horizontal power struggle is based on what Althusser describes as the ideological apparatus. Here, the struggle is based on a fight between individuals (the society), corporations, and the state for code-modifying resources and/or leverage over the governance token holders. Overall, the paper argues and shows that blockchain-based “code is law” reality does not solve the issue of unequal power relations within societies but only as any technological revolution shifts the power relations and power struggles between existing and new actors. Unlike the founder of Polkadot, Gavin Wood states that blockchain, DAOs, smart contracts, and Web3 overall do not result in the new social sphere with revolutionised power relations. Where Web3 is now is much more similar to where Web1 and Web2 were 25–30 years ago—Creating a new space for social interactions and discourse yet being stuck within the same social sphere and uneven power relations that have governed our societies for centuries.
Decentralized identity frameworks grant users full sovereignty over their digital assets in the Web3 ecosystem. However, allowing arbitrary creation of identifiers makes the system susceptible to Sybil attacks and puts assets at risk when keys are lost or compromised. Moreover, the lack of identification prevents anonymous credential schemes from deterring malicious transfers. While existing solutions attempt to address these issues by linking identifiers to entities through trusted intermediaries, these entities are not always accessible and require costly offline interactions. In this work, we introduce LinkDID, a decentralized identity scheme offering Sybil resistance, trustless key recovery, and nontransferable anonymous credentials. LinkDID creates blockchainbased bindings between identifiers and gradually combines identifiers belonging to the same holder into a unified associated identifier. As all identifiers within an association are presumed to belong to one individual, any fraudulent activity can be detected. The association grows larger as interactions increase, substantially reducing the likelihood of successful Sybil attacks. This mechanism allows holders to recover identifiers with lost or stolen keys by proving knowledge of specific association structures. Additionally, LinkDID prevents unauthorized transfers through blockchain-based identifier-key bindings and proofs of ownership for credentials. The evaluation shows that LinkDID effectively achieves progressive Sybil resistance while surpassing state-of-the-art anonymous credential schemes, achieving identifier association and credential presentation times of 2.41s and 3.31s on consumer-grade devices.
As the Industrial Internet of Things (IIoT) continues to grow in scale, edge devices will generate massive amounts of data every single day. However, most of the IIoT data exists in the form of data silos, which makes it difficult to share data across domains securely. Therefore, a secured data-sharing scheme for IIoT based on blockchain and federated learning (FL) is proposed in this article. Leveraging blockchain in FL systems to enhance the tamper-proof and decentralized capabilities of IIoT devices. Model parameter validation and incentives are also added to the consensus algorithm to encourage more IIoT data owners to contribute local privacy data and arithmetic power. To address potential security issues, such as parameter leakage and inference attacks in data sharing, this article designs an adaptive differential privacy mechanism and a node contribution consensus mechanism. Without affecting the global model’s accuracy, some of the noise is also reduced. The reputation mechanism is used to resist poisoning attacks by malicious nodes. It is demonstrated on different data sets that our scheme has high global model accuracy and can effectively resist 30% model poisoning attacks.
The development of an electronic voting system that would replace traditional election procedures is a research topic of great interest for many years. Blockchain technology could provide some guarantees and fulfill strong requirements for electronic voting platforms, such as transparency, immutability, and confidentiality. From time to time research is conducted to address problems in voting systems. Many research works attempt to implement secure and reliable voting systems, which address known security, anonymity, and fraud issues that might threaten such systems. This paper presents a proposal of a secure electronic voting system, the EtherVote, using the Ethereum Blockchain network that focuses deeply on the field of identification of eligible citizens. The proposed system will be entirely based on Blockchain without any central authority servers or databases, thus improving security, privacy, and election cost. Limitations, problems, and solutions are discussed, in order to make the proposed electronic voting system ideal and ready to use for national elections.
With the rapid growth of flight operation data, how to alleviate the contradiction between data sharing and privacy protection of civil aviation corporations has become a challenging problem. Therefore, a blockchain-based flight operation data sharing scheme, named BFOD is designed to achieve the privacy protection and secure sharing of flight operation data. In BFOD, physical entities of airlines, airports and air traffic control are divided into data owners, data requesters and authorization institutes according to the business logic. First, the authorization institute grants a hash anonymous identity and different levels of access right for each civil aviation corporation. When the data are accessed, a hash anonymous identity is designed to verify the access right of the data requester, which protects identity privacy. Then, zero-knowledge succinct noninteractive argument of knowledge (zk-SNARKs) is employed to verify whether the flight operation data meets the specific requirements raised by the data requester without disclosing data privacy. Finally, a proxy re-encryption is used to improve the sharing efficiency of flight operation data. In addition, a grouped practical Byzantine fault tolerant (PBFT) algorithm is proposed to reduce consensus latency. The theoretical analysis and experimental results show that the consensus latency of the grouped PBFT algorithm reduces 91.4% under the number of consensus node$\text{N}=$100, and the BFOD meets data confidentiality, availability and privacy protection, which is feasible and efficient.
Jingnan Dong, Guangxia Xu, Chuang Ma, Jun Liu · 5 authors
In Industrial Internet, mutual authentication between enterprises is a prerequisite for establishing reliable upstream and downstream relationships. Existing authentication methods suffer from complicated certificate management and key escrow problems. Moreover, many authentication mechanisms cannot resist common security attacks and have high computational overhead and communication costs. Therefore, this paper proposes a blockchain-based certificate-free cross-domain authentication mechanism for Industrial Internet. By establishing an Ethereum consortium blockchain as the trusted cornerstone among different regions, industrial enterprises in each region generate the user’s private key with the key generation center in the region, thus avoiding the key escrow problem. This consortium blockchain adopts the proof of authority consensus mechanism for scalability and throughput. Industrial enterprises in different regions invoke smart contracts and query other industrial enterprises for mutual authentication and key negotiation. SVO logic proves the proposed scheme achieves the intended authentication goal, and the automated formal verification tool Scyther proves the scheme’s security. In addition, compared with seven related schemes in the last three years, the experimental results show that the proposed scheme has low communication overhead and computational cost in the authentication key negotiation phase. The experiments on the Ethereum consortium blockchain built by Raspberry Pi prove the effectiveness of the proposed scheme. Finally, the comparative analysis of common security properties proves the reliability of the scheme.
Arnab Mukherjee, Souvik Majumdar, Anup Kumar Kolya, S. Nandi
Within a modern democratic nation, elections play a significant role in the nation's functioning. However, with the existing infrastructure for conducting elections using Electronic Voting Systems (EVMs), many loopholes exist, which illegitimate entities might leverage to cast false votes or even tamper with the EVMs after the voting session is complete. The need of the hour is to introduce a robust, auditable, transparent, and tamper-proof e-voting system, enabling a more reliable and fair election process. To address such concerns, we propose a novel solution for blockchain-based e-voting, focusing on the security and privacy aspects of the e-voting process. We consider the security risks and loopholes and aim to preserve the anonymity of the voters while ensuring that illegitimate votes are properly handled. Additionally, we develop a prototype as a proof of concept using the Ethereum blockchain platform. Finally, we perform experiments to demonstrate the performance of the system.
With the rapid development of internet technology, it has become increasingly straightforward for people to seek and share health information in online health communities (OHCs). However, the current OHCs are mainly centralized systems fraught with data breaches, identity theft, and censorship problem. Some researchers proposed that Web3 technology can provide potential solutions to current problems. In this research, we identify three core components that should empathize in developing OHCs: trust, privacy, and information quality. Accordingly, we surveyed and analyzed Web3 literature and generated the spectrum of Web3 research. Then we applied text analysis to 6 articles we had collected to conduct a co-occurrence network and generate minimum spanning trees. We then discussed the important factors in the technical, application, and service aspects for applying Web3 technology in future OHCs development.
Smart home devices generate a substantial amount of local data, and finding effective ways to utilize this data while ensuring privacy has become an increasingly pressing concern. Technologies such as Smart Homes, Federated Learning and Blockchain offer promising solutions to address this challenge. We introduce a blockchain-based federated learning approach that leverages edge nodes to maintain a decentralized blockchain, thus mitigating the risks associated with single points of failure. Furthermore, this method utilizes local data from home IoT devices for model training, ensuring efficient learning while preserving data privacy. To address the challenges posed by non-independent and homogeneous data distribution, we propose a clustering method. This strategy effectively tackles the issues arising from non-homogeneous data distribution, consequently improving model accuracy. Finally, experimental results demonstrate that our proposed approach significantly enhances model accuracy and generalization while safeguarding user privacy.
Decentralized systems have proven themselves as a dominant authentication and storage paradigm for IoT systems where smartwatches are integrated with MQTT messaging framework for transmitting medical data to doctors. However, the security concerns with centralized frameworks presented vital security challenges regarding data privacy and network security for healthcare systems. This paper will present an integrated framework involving a reliable and lightweight e-health data-sharing framework that combines the decentralized interplanetary file system (IPFS) and blockchain on a smartwatch platform. Particularly, this framework helps in trustworthy control mechanisms which use smart contracts to achieve authentication and storage for both subscribers and publishers. We presented a simulation using Ethereum blockchain and IPFS in a real data-sharing scenario with the MQTT protocol. Our analysis proved that our approach satisfies lightweight access control requirements since it demonstrates the low latency of the framework and optimized energy consumption with high security and data privacy levels.
Elections are an important way of conveying one's choice in a democratic system. Many new technologies have been introduced to carry out the process of elections over the years. Even after so many developments in the voting system, there are still many issues faced regarding the results of voting. The voting approaches available are vulnerable to malfunctions and the results of voting are not reliable. This paper compares the different methods of voting while discussing their advantages and drawbacks. Blockchain based polling is a decentralized voting system which offers transparency and protection from any malpractice. The voting results obtained from this process are reliable. An Ethereum platform based decentralized application (DApp) along with a smart contract in solidity is proposed in this work to execute the process of voting through blockchain based technology.
The move from traditional healthcare to smart healthcare systems is greatly aided by current technology. It is now necessary that the patient retains ownership of his or her personal medical data, organizes it securely, and shares it with those who remain anonymous in the system. Transparency, security, and privacy of health data are three major drawbacks of conventional healthcare systems. Utilizing blockchain technology, which has several uses in the healthcare industry because of characteristics like decentralization (no need for a central authority), immutability, accountability, and openness, is one potential remedy for this. The proposed system allows patients to enter their medical data and access the doctor's prescription that has been uploaded to the platform. Registered doctors can access patient reports and provide feedback as necessary. To maintain privacy, both patients and doctors will remain anonymous to each other, and all data and activity will be encrypted and unchangeable. This ensures that the information remains secure and cannot be tampered with. In this study, we developed a blockchain-based system using Ethereum for storing personal health records and conducted a comparative analysis with SQL-based health record systems. Our experimental results demonstrate that the Ethereum-based system offers superior security and data privacy compared to traditional SQL-based systems. Moreover, the blockchain transactions were found to be 87% faster on average than transactions processed through traditional SQL databases according to our study.
We propose a middleware solution designed to facilitate seamless integration of privacy using zero-knowledge proofs within various multi-chain protocols, encompassing domains such as DeFi, gaming, social networks, DAOs, e-commerce, and the metaverse. Our design achieves two divergent goals. zkFi aims to preserve consumer privacy while achieving regulation compliance through zero-knowledge proofs. These ends are simultaneously achievable. zkFi protocol is designed to function as a plug-and-play solution, offering developers the flexibility to handle transactional assets while abstracting away the complexities associated with zero-knowledge proofs. Notably, specific expertise in zero-knowledge proofs (ZKP) is optional, attributed to zkFi's modular approach and software development kit (SDK) availability.
This chapter examines the implications of blockchain technology on the processing of personal data and its compliance with the general data protection regulation (GDPR) within the European Union. While the internet has revolutionized communication and database systems, it has also posed challenges to legally process personal data. However, the introduction of blockchain technology, with its cryptographic features and decentralized peer-to-peer ledger system, raises questions about the applicability of the GDPR. This chapter analyzes personal data processed in public blockchains, including the right to erasure. Additionally, the chapter explores the complexities of establishing accountability within distributed ledger technology, considering the innovative nature of blockchain and the traditional database framework upon which the GDPR was constructed. By examining the relationship between blockchain participants and fundamental data protection rights, this research aims to shed light on the intersection of blockchain technology and personal data protection.
Stanisław Barański, Julian Szymański, Higinio Mora
Abstract Lawyers, laboratories, auditors, and banks often need access to sensitive personal data to provide services such as genetic testing, paternity testing, STD testing, credit scoring, or legal advice. Processing such data exposes both service providers (SPs) and users to privacy risks: SPs risk violating laws like the General Data Protection Regulation (GDPR) and the Consumer Protection Act (CPA), while users risk losing their privacy. We observe that personal data is often only needed for logistical purposes like payment or communication and could be provided anonymously if suitable methods existed. To address this, we present a solution that enables services to be delivered without collecting personal data. Our protocol combines anonymous payment methods (e.g., cash, privacy-preserving cryptocurrencies), blockchain for fairness, and distributed content-addressable storage networks to deliver results. Compared to existing approaches, our protocol achieves anonymity under weaker assumptions, supports the transfer of physical materials and conflict resolution, and eliminates the need for customer interaction with a trusted arbiter in conflict-free cases-making it more practical. We analyze the protocol’s fairness and implement a prototype using Ethereum as a message board, Monero for anonymous payments, and Powergate (IPFS/Filecoin) as a decentralized storage solution.
Federated learning (FL) has been proposed as an emerging paradigm to perform privacy-preserving distributed machine learning in the Internet of Things (IoT). However, the communication overhead caused by partial model aggregations will increase the model training latency. In this article, a multilayer blockchain-enabled hierarchical FL (HFL) network is proposed for low-latency model training while ensuring data security. Meanwhile, we theoretically analyze the bottleneck of the model accuracy with the total data distance due to the imbalanced data distribution. Moreover, the mathematical expression of the model error with respect to IoT devices (IDs) association and local data distribution is provided, then the upper bound of the model error is represented by the total data distance. To further improve the learning performance, the distance-aware HFL (DAHFL) algorithm is investigated, which optimizes ID association strategy based on dual-distance, and allocates computing and communication resources alternatively. Finally, the working process of the blockchain-enabled HFL system is exhibited by the blockchain simulation platform and the efficiency of the proposed DAHFL algorithm is demonstrated by the simulation results.
The novel sensing paradigm known as crowdsensing leverages ubiquitous smart devices to collect data in Internet of Things (IoT) applications. Traditional crowdsensing schemes assume a central framework to execute truth discovery algorithm to assure data quality, which may introduce reliability and privacy issues. Blockchain is a promising technology that provides a decentralized, transparent, and immutable platform. However, designing a blockchain-based quality assurance scheme in crowdsensing is not a trivial problem. First, truth discovery is a time-consuming iterative algorithm, which is not practical to execute on blockchain. Second, privacy-preserving schemes always require that the participants join in multiround communications, which is not acceptable in open blockchain because of users’ highly unpredictable behaviors. Finally, on-chain data are publicly accessible, and achieving a good balance between data utility and privacy is an important issue. In this article, we propose a lightweight quality assurance framework atop blockchain to build a reliable, privacy preserving, and fair crowdsensing system. Specifically, we carefully design two kinds of smart contracts to cooperatively maintain a long-term reliable platform to execute crowdsensing tasks. In the contracts, we devise a reputation-based aggregator selection algorithm to reach the consensus on truthful results while avoiding expensive on-chain iterative processes. The participant selection scheme and reward policy are further utilized to filter appropriate participants to complete the task. Our scheme also protects data privacy and does not require communications between participants. Finally, we implement and deploy the contracts on Ethereum and conduct extensive experiments to demonstrate that the contracts can practically execute crowdsensing tasks.
Federated learning can effectively alleviate the data privacy problem of the participants, but the parameters or gradients passed in the model training may still leak the private data of the participants. Worse, aggregation server may return fake aggregation results. Existing solutions either use complex cryptographic primitives such as zero-knowledge proofs, or require interaction among participants, causing them high computation or communication overhead. Therefore, this paper proposes a secure and verifiable federated learning (SVFL) scheme. Specifically, SVFL performs privacy protection by introducing noise that can be offset during the aggregation process, and utilizes linear homomorphic hash to verify the correctness of the aggregation results. Compared with existing schemes, SVFL hardly loses accuracy due to the introduced security mechanism, and has low computation and communication overhead. Experimental results show that the performance of SVFL is almost consistent with the original federated learning without any protection, which makes SVFL applicable to edge devices. The computation and communication overhead of SVFL does not increase with the number of participants, which makes SVFL applicable to high-concurrency scenarios.
With the recent hype around the Metaverse and NFTs, Web3 is getting more and more popular. The goal of Web3 is to decentralize the web via decentralized applications. Wallets play a crucial role as they act as an interface between these applications and the user. Wallets such as MetaMask are being used by millions of users nowadays. Unfortunately, Web3 is often advertised as more secure and private. However, decentralized applications as well as wallets are based on traditional technologies, which are not designed with privacy of users in mind. In this paper, we analyze the privacy implications that Web3 technologies such as decentralized applications and wallets have on users. To this end, we build a framework that measures exposure of wallet information. First, we study whether information about installed wallets is being used to track users online. We analyze the top 100K websites and find evidence of 1,325 websites running scripts that probe whether users have wallets installed in their browser. Second, we measure whether decentralized applications and wallets leak the user's unique wallet address to third-parties. We intercept the traffic of 616 decentralized applications and 100 wallets and find over 2000 leaks across 211 applications and more than 300 leaks across 13 wallets. Our study shows that Web3 poses a threat to users' privacy and requires new designs towards more privacy-aware wallet architectures.