Compliance with the GDPR while using blockchain technology for data processing results in compliance issues, due to the fact that the blockchain and the GDPR employ different methods to ensure privacy-by-design and privacy-by-default. The blockchain is built on disintermediation and relative decentralization, whereas the GDPR aims for re-intermediation and relative centralization of the data protection process. This paper provides an overview of and suggestions on how to secure compliance with the GDPR while processing data using the blockchain. A focus is placed on the data protection impact assessment on the blockchain network, issues in identifying and determining the role(s) of sole and joint data controllers and data processors, obstacles to exercising the right to rectification and right to be forgotten when the data is recorded on the blockchain, GDPR data transfer requirements as applied to the blockchain, and the protection of privacy in the process of creating blockchain-based smart contracts.
Zusammenfassung In zunehmend vernetzten Systemen erstreckt sich die gesamte Datenwertschöpfungskette über eine Vielzahl an Systemen, wobei unterschiedliche Akteure mit unterschiedlichen und möglicherweise gegensätzlichen Interessen beteiligt sind. Es ist daher erforderlich, die Prozesse der Datenerfassung, Verarbeitung und Speicherung so abzusichern, dass Manipulationen durch externe Angriffe oder einzelne Akteure erkannt werden können. Dieser Beitrag legt den Fokus auf drei unterschiedliche technische Maßnahmen, durch welche Vertrauen in die ausgetauschten Daten selbst und letztendlich auch zwischen unterschiedlichen Akteuren hergestellt werden kann: Maßnahmen zur Kommunikationssicherheit schützen Daten während des Transports, digitale Kalibrierzertifikate erlauben eine Aussage über die Genauigkeit der erfassten Daten, Distributed-Ledger-Technologien wie zum Beispiel eine Blockchain erfassen Aktionen sowie beteiligte Akteure und legen diese Informationen manipulationsgeschützt ab. Dieser Beitrag bezieht sich auf das Forschungsprojekt GEMIMEG-II , das durch das Bundesministerium für Wirtschaft und Klimaschutz (BMWK) gefördert wird.
Phuc Nguyen Trong, Hong Khanh Vo, Huong Hoang Luong, Khiem Huynh Gia · 13 authors
YouTube connects people with each other through an online video sharing service platform. With the great devel-opment of the entertainment industry, content on YouTube is accessible to many people of different ages. However, verifying the content posted on YouTube is clean or not is a difficult problem. Dirty content is violent, pornographic and vulgar content that causes serious psychological harm to the segment of users under the age of 18, i.e., especially those of an age who are not yet aware of the harmful effects of content. Toxic will bring to the child’s behavior. Agree that Google (i.e., YouTube) has developed a YouTube Kid application where the videos are only for children under the age of 13. However, cultural and educational differences between regions strongly influence the choice of children. Select content for children. Therefore, the content restrictions on the YouTube Kid application have not yet met all the requirements of parents around the world. There have been many development directions to identify videos containing malicious content based on deep learning. However, there is no method to build a tool to support parents of children to share and identify videos with objectionable content (e.g., violence, pornography, obscene words) on the YouTube platform. In this research paper, we introduce YVC, a YouTube-verified content platform by applying blockchain’s distributed, public validation. This tool helps parents validate YouTube content and issue a report to reduce dirty content on YouTube. To demonstrate the effectiveness of our approach, we implement the proof-of-concept in the three most popular EVM platforms: Ethereum, Fantom, and the Binance smart chain. Compared to the YouTube Kids (i.e., the most common shared video platform for the under 13-year-old kid), our approach is able to capture the video preferences of the parents covering the difference areas/countries.
Abstract Trust is a key resource in financial transactions. Traditional financial institutions, and novel blockchain‐based decentralized financial (DeFi) services rely on fundamentally different sources of trust and confidence. The former relies on heavy regulation, trusted intermediaries, clear rules (and restrictions) on market competition, and long‐standing informal expectations on what banks and other financial intermediaries are supposed to do or not to do. The latter rely on blockchain technology to provide confidence in the outcome of rules encoded in protocols and smart contracts. Their main promise is to create confidence in the way the blockchain architecture enforces rules, rather than to trust banks, regulators, and markets. In this article, we compare the trust architectures surrounding these two financial systems. We provide a deeper analysis of how proposed regulation in the blockchain space affects the code‐ and confidence‐based architectures which so far have underwrote DeFi. We argue that despite the solid safeguards and guarantees which code can offer, the confidence in DeFi is still very much dependent on more traditional trust‐enhancing mechanisms, such as code governance, and antifraud regulation to address some of the issues which currently plague this domain, and which have no immediate, purely software‐based solutions. What is more, given the risks of bugs or scams in the DeFi space, regulation and trusted intermediaries may need to play a more active role, in order for DeFi to gain the trust of the next generation of users.
This thesis presents a generalised comprehensive framework for evaluating anonymity of cryptocurrency schemes. The framework was developed using security modelling with emphasis on a wide range of factors affecting anonymity, irrespective of the underlying implementation. The case studies presented in the thesis demonstrate how this framework facilitates the evaluation of anonymity of different cryptocurrencies in a standardised manner and the analysis of these findings reveals the complexity of the notion of anonymity.
The ever-increasing acceptance of cryptocurrencies has fueled applications beyond investment purposes. Crypto-payment is one such application that can bring radical changes to financial transactions in many industries, particularly e-commerce and online retail. However, characteristics of the technology such as transaction disintermediation, lack of central authority, and lack of adequate regulations may introduce new privacy and security concerns among the users. This coincides with another trend of rising individuals’ concerns pertaining to information privacy and security issues in online transactions. The current paper investigates how consumer trust in crypto-payment, a key determinant of consumer intentions and relational exchanges over the long-term, is formed based on their perceptions towards privacy and security aspects of the technology. Using data from 327 survey participants, the study found that perceived information privacy risk, perceived anonymity, and perceived traceability of transactions are significant determinants of consumer trust in crypto-payment; but their perceptions of information security fraud risk have no significant effect. It also provided support for the hypothesis that perceived trust contributes to consumers’ intention to adopt crypto-payment. The findings highlight the need to enhance consumer understanding and awareness of information privacy and potential security issues in crypto-payment as well as what needs to be done to address consumer concerns in this regard. The paper creates novel insights into the requirements of trust in crypto-payment services and the consequences of consumers’ perceptions of privacy and security in this domain.
As a service platform, blockchain has faced compliance issues since the General Data Protection Regulation (GDPR) came into effect in May 2018. Although many technical solutions have been proposed to solve the compatibility issues between blockchain and the GDPR, unresolved challenges remain. This study presents the gaps between the blockchain and the GDPR and explores solutions to bridge the gap.We review 91 previously published articles using a systematic literature review methodology. Then, we answer the following research questions: 1) Which solutions have been explored to allow the blockchain to comply with the GDPR? 2) What are the research gaps in the blockchain compliance field? Finally, we present five research gaps in this field: 1) development of a consent ontology model; 2) development of a methodology for monitoring fairness in the blockchain; 3) resolution of the contradiction between auditing and obfuscation; 4) development of a methodology for tracking controllers in the blockchain; and 5) integration of the different-purposed technical solutions without conflicts. Our research can raise the compatibility level of the blockchain and GDPR and guide the company adopting a blockchain to comply with the GDPR. Furthermore, it can advise the regulator to embrace new technologies into the GDPR while protecting a blockchain’s nature.
Mohammed Shuaib, Noor Hafizah Hassan, Sahnius Usman, Shadab Alam · 8 authors
The land registry system is one of the essential components of any governance model required to ascertain the ownership records uniquely. This paper reviews the existing literature and provides a detailed literature review consisting of 3 stages based on three research questions (RQ) that highlight the step by step evaluation and analysis. We selected 48 primary articles out of 477 extracted from different scientific databases based on criteria and RQ defined in the research method section. The majority of these papers focus on assessing the identity issues related to the land registry system and reviewing the existing identity models to find the best possible identity model to resolve the identified identity problems in the land registry. This paper examines the current land registry model and its shortcomings. It explains the various blockchain types and their characteristics. It further evaluates the usability of blockchain technology in different aspects of the land registry. Identity management is one of such weaknesses in the blockchain‐based land registry model that has been assessed in detail. Identity issues of blockchain‐based models have been further evaluated on defined criteria. The paper ends with a discussion on possible identity models and their comparative analysis to ascertain the most suitable identity model to resolve the identity issues of land registry systems.
As a kind of distributed, decentralized and peer-to-peer transmitted technology, blockchain technology has gradually changed people’s lifestyle. However, blockchain technology also faces many problems including selfish mining attack, which causes serious effects to the development of blockchain technology. Selfish mining is a kind of mining strategy where selfish miners increase their profit by selectively publishing hidden blocks. This paper builds the selfish mining model from the perspective of node state conversion and utilize the function extremum method to figure out the optimal profit of this model. Meanwhile, based on the experimental data of honest mining, the author conducts the simulation of selfish mining and discovers that selfish miners are able to acquire more revenue than honest miners when they account for more than 1/3 computing power of the whole system. Lastly, to defend the selfish mining attack, the author also summarizes the existing defending strategies and evaluates every kind of strategy briefly.
Junqin Huang, Linghe Kong, Long Cheng, Hong‐Ning Dai · 8 authors
Mobile crowdsensing (MCS) can promote data acquisition and sharing among mobile devices. Traditional MCS platforms are based on a triangular structure consisting of three roles: data requester, worker (i.e. , sensory data provider) and MCS platform. However, this centralized architecture suffers from poor reliability and difficulties in guaranteeing data quality and privacy, even provides unfair incentives for users. In this paper, we propose a blockchain-based MCS platform, namely BlockSense, to replace the traditional triangular architecture of MCS models by a decentralized paradigm. To achieve the goal of trustworthiness of BlockSense, we present a novel consensus protocol, namely Proof-of-Data (PoD), which leverages miners to conduct useful data quality validation work instead of “useless” hash calculation. Meanwhile, in order to preserve the privacy of the sensory data, we design a homomorphic data perturbation scheme, through which miners can verify data quality without knowing the contents of the data. We have implemented a prototype of BlockSense and conducted case studies on campus, collecting over 7,000 data from workers' mobile phones. Both simulations and real-world experiments show that BlockSense can not only improve system security, preserve data privacy and guarantee incentives fairness, but also achieve at least 5.6x faster than Ethereum smart contracts in verification efficiency.
Abdullah Yousafzai, Latif U. Khan, Umer Majeed, Owais Hakeem · 5 authors
Federated learning (FL) enables the training of a shared collaborative machine learning model while keeping all the confidential training data on distributed devices. The FL state-of-the-art considers a monopolist FL task publisher. However, we present a FL marketplace where multiple FL task publishers and mobile devices co-exist for a set of diverse and varying learning tasks. Mobile devices participating in the training of FL models provides pay-as-you-go (i.e. using blockchain-based cryptocurrencies) FL training services to the FL task publishers. In the proposed framework, multiple FL task publishers may compete with each other and the participating workers (i.e. mobile devices) can choose one FL task publisher over another for participation in the training of a global model. We utilize code offloading for enabling customized FL pipelines in mobile devices and mitigating the model heterogeneity inherent in varying and changing FL tasks published by the task publishers. Experimental results indicate the efficacy of the proposed framework.
Silvia Gabrielli, Stephan Krenn, Donato Pellegrino, Juan Carlos Pérez Baún · 7 authors
Abstract The KRAKEN project aims to enable the sharing, brokerage, and trading of personal data including sensitive data (e.g., educational and health records and wellbeing data from wearable devices) by returning its control to both data subjects/data providers throughout the entire data lifecycle. The project is providing a data marketplace which will allow the sharing of personal data and its usage for research and business purposes, by using privacy-preserving cryptographic tools. KRAKEN is developing an advanced platform to share certified information between users and organizations by leveraging on distributed ledger technology, promoting the vision of self-sovereign identity solutions (ensuring users’ consent and data control in a privacy-friendly way), preserving security, privacy, and the protection of personal data in compliance with EU regulations (e.g., GDPR). The feasibility of the KRAKEN solution will be tested through two high-impact pilots in the education and healthcare fields.
May Alhajri, Carsten Rudolph, Ahmad Salehi Shahraki
Wearable fitness devices are widely used to track an individual’s health and physical activities to improve the quality of health services. These devices sense a considerable amount of sensitive data processed by a centralized third party. While many researchers have thoroughly evaluated privacy issues surrounding wearable fitness trackers, no study has addressed privacy issues in trackers by giving control of the data to the user. Blockchain is an emerging technology with outstanding advantages in resolving consent management privacy concerns. As there are no fully transparent, legally compliant solutions for sharing personal fitness data, this study introduces an architecture for a human-centric, legally compliant, decentralized and dynamic consent system based on blockchain and smart contracts. Algorithms and sequence diagrams of the proposed system’s activities show consent-related data flow among various agents, which are used later to prove the system’s trustworthiness by formalizing the security requirements. The security properties of the proposed system were evaluated using the formal security modeling framework SeMF, which demonstrates the feasibility of the solution at an abstract level based on formal language theory. As a result, we have shown that blockchain technology is suitable for mitigating the privacy issues of fitness providers by recording individuals’ consent using blockchain and smart contracts.
Montassar Naghmouchi, Hella Kaffel Ben Ayed, Maryline Laurent
Nowadays, open standards for self-sovereign identity and access management enable portable solutions that are following the requirements of IoT systems. This paper proposes a blockchain-based identity and access management system for IoT -- specifically smart vehicles -- as an example of use-case, showing two interoperable blockchains, Ethereum and Hyperledger Indy, and a self-sovereign identity model.