Distributed Ledger Technology (DLT) has been contentious since the emergence of blockchain in 2008. Security and compatibility with the personal data rights in the EU General Data Protection Regulation (GDPR) are among the controversies that have erupted. Thus, various studies have concluded that the decentralisation and immutability of DLT conflict with personal data rights. This dissertation illustrates that the DLT can be compatible with the GDPR personal data rights.
This thesis tells the story of DTube, a blockchain-based social media (BSM) platform positioned as an alternative to YouTube. BSM platforms are situated at the intersection of the emergent Web3 discourse and the dominant platform paradigm. These novel initiatives attempt to develop community-led alternatives to mainstream commercial platforms by leveraging emergent Web3 technologies. Using the platform biography approach, the thesis traces DTube’s evolution between 2017-2022, locating these changes within the history of the web and digital media platforms. It contributes to a broader understanding of changing discourses, technologies, and practices of the web at a crucial historical juncture.
Smart cities represent a promising paradigm aimed at enhancing citizens’ quality of life through cutting-edge infrastructure and technological advancements. Collaborative services serve as a cornerstone for any smart city, fostering seamless cooperation among diverse entities, including government agencies, businesses, and individuals, thereby enhancing community outcomes. These services are pivotal, promoting seamless communication and collaboration among various smart applications, and facilitating data exchange, resource sharing, and functional interactions within smart city environments to optimize efficiency, effectiveness, and user experiences. However, the development and deployment of secure, interoperable services in smart cities present significant challenges. These issues encompass, ensuring data security compliance during interoperation, effective management of interconnected services, securely handling sensitive data across services, and addressing issues related to confidentiality, integrity, and availability (CIA) traits. To tackle these challenges, this research proposes an innovative adaptive security governance framework tailored for smart cities. This framework relies on dynamic security policies implemented through smart contracts to guarantee data security and privacy during smart service interoperation. Real-world use cases in collaborative smart city environments validate the framework, integrating multi-chain blockchain technology, smart services APIs, and Software-Defined Networking (SDN), showcasing its ability to enhance security and efficiency in collaborative services. This study contributes to the development of safe and efficient collaborative services inside smart cities, tackling administrative issues while emphasizing data security and privacy. Smart cities may improve citizens’ living conditions while successfully addressing crucial security problems in an ever-changing environment by using this architecture.
The increased digitalization of society raises concerns regarding data protection and user privacy, and criticism on how the companies handle user data without being transparent and without providing adequate mechanisms for users to control how their own data is being processed or shared. To address this problem and open the way for a secure and efficient society, where the privacy of citizens is paramount, the identity concept and proof of identity mechanisms need to be redesigned from the ground up. In this paper we discuss how the emerging Web3 technologies like distributed ledger technology (DLT), blockchain, smart contracts, decentralized storage systems, and crypto wallets can be leveraged to design and implement a decentralized digital identity system based on decentralized identifiers (DID) and self-sovereign identities (SSI). Such a system puts the users in full control over their own data while also providing a solid backbone for building interoperable systems that are secure, scalable, and efficient. We propose different architectures for the decentralized identity infrastructure and storage layer, and also discuss the mapping of these architectures on cloud platforms. The main goal is to provide an architectural blueprint for a scalable, secure, privacy-preserving and trusted system.
In the current digital landscape, almost everyone is on social media or various social media platforms. People use social media for a plethora of purposes, which include staying connected with friends and family, accessing information and updates about ongoing events, entertainment, networking with professionals, expressing themselves to a wide range of users, promoting businesses, joining online communities and engaging in various activities which has led to an increase in the consumption and usage of online social networks (OSN). One of the reasons for such a growth is their features such as ubiquitous access, on-demand service, friendship networks, user engagement strategies like recommendation engines, etc. However, there are various limitations to the current approach, such as the centralization of control, lack of data ownership, poor access control, fake news, bot accounts, censorship, digital rights management issues, etc. To address these limitations, a paradigm shift is necessary. This paper aims to develop a social media application where every post can be converted to a Non-Fungible Token (NFT) and be sold to earn money. Interplanetary File System (IPFS) is used as the decentralized storage. Algorithms for all the functionalities of the applications are given along with an algorithm for a reputation score for every user and their posts in social media are also proposed.
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Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Here, we embark on a comparative analysis of token definitions as articulated by leading financial regulatory bodies across the globe. The chosen regulators represent the financial epicentres of the modern world – entities that not only influence global financial trends but also signal the regulatory future of burgeoning technologies. This section underscores the importance of understanding token definitions, given their critical role in determining the scope of regulation, compliance requirements and the overarching legal treatment of digital assets.
Abstract This chapter has two purposes. First, we describe how information system (IS) scholars approach privacy research and summarize major findings. IS scholars are concerned with information privacy and have discovered that individuals have serious information privacy concerns. These concerns, however, do not prevent individuals from disclosing personal identifiable information (PII) with centralized platform providers, a phenomenon called the privacy paradox . We highlight four common explanations for the privacy paradox: privacy calculus, privacy fatigue, trust, and lack of choice. Most IS research investigated Web2 applications. Web2 is the foundation for today’s global economy. With Web2, users rely on centralized platforms for online searching, shopping, banking, data storage, social media, and other services. Second, we introduce readers to the new paradigm of Web3. Privacy protection has been the paramount logic behind the grand design of Web3 applications. Web3 is the era of the Internet that is based on decentralized infrastructures and applications, like Bitcoin and Ethereum. Web3 applications enhance information privacy compared to Web2 because individuals can access services without disclosing PII to a central authority. The privacy objective is achieved technically through a combination of digital wallets, cryptography, and distributed ledgers (a.k.a blockchain). While Web3 is still in its early days, education is an important driver of adoption.
With the popularity of Non-Fungible Tokens (NFTs), the high value of NFTs makes them a target for phishing scammers, which harms the security and reliability of the Web3 NFT ecosystem. Despite the significance of this issue, there is a lack of systematic research in the area of emerging NFT phishing scams. To address this gap, we are the first to conduct a case retrospective analysis and empirical measurement study of real-world historical NFT phishing scams on Ethereum. We collect and publicly release the first NFT phishing dataset which includes 1,625 NFT phishing accounts and transaction records as of August 2023. We further categorize the existing scams into four phishing patterns and investigate their distinguishable behaviors. Then, we reveal the modus operandi preferences and economic impacts to characterize NFT phishing scams. We find that NFT phishers stole 67,188 NFTs, with a total direct selling profit of${\$}$20.92 million. We also observe that scammers favor certain categories and collections of NFTs, coupled with signs of gang theft. Furthermore, we design a variety of account features for the classification task of NFT phishers based on empirical conclusions. Experimental results on real-world NFT transaction data demonstrate the effectiveness of these features in detecting NFT phishing accounts, and outperform traditional phishing detection methods with 41% average Precision and 44% average Recall.
Self-sovereign identity models and decentralized, blockchain-based identity management can prevent digital ecosystem data breaches and misuse, the study finds. As digital services proliferate and personal data becomes more valuable, central database-based identity systems expose users to single-point failures, unauthorized access, identity theft, and large-scale breaches. This paper analyzes how decentralized IDs, verifiable credentials, and cryptographic verification reduce middlemen, enable selective disclosure, and promote identity governance privacy. Important academic, industrial, and technical contributions show that blockchain anchors credentials in distributed ledgers rather than institutional repositories, improving authentication, traceability, and tamper resistance while limiting undesired access. Immutable audit trails, user-controlled credentials, and reduced central authority dependency have been touted, but empirical performance data, scalability, interoperability, and comparative evaluations of public and permissioned blockchain environments are lacking. These findings explain self-sovereign identity architecture, which lets trusted authority issue credentials but users store and control them directly through digital wallets utilizing cryptographic proofs instead of database lookups. Users can control or withdraw data sharing while maintaining identity. Transparency, limited disclosure, and contextual data presentation prevent cross-platform tracking and increase user autonomy. The research shows how zero-knowledge proofs and predicate-based validation verify credentials without disclosing sensitive data, protecting privacy. Birthdates and locations are not needed to verify age- and location-based limits. SSI master key-derived domain-specific identities reduce correlation hazards and prevent service surveillance. Consent-based sharing, selective disclosure, and cryptographic compartmentalization decrease data collection and profiling. Decentralised blockchain verification maintains credentials usable when the issuer is offline, preventing service disruptions and third-party participation.
Most of the countries throughout the world is democratic where voting plays crucial role. Government is formed by people via election. People choose their representatives through the election process. Election should be of a trustworthy process and voting system should be secure, tamper-free, and fraud resistant. It is very difficult to build such a system in large democratic country like India which has population about billion. In this paper, new way of electronic voting using blockchain technology i.e., a system that utilize a decentralized and distributed ledger is suggested. Blockchain technology can make the voting system a simple, secure, and reliable. Moreover, it can save time and money and deal with large amounts of data in real time. The main feature of blockchain technology is that a secure hash algorithm is used to safeguard each block of vote.
Spatial crowdsourcing (SC) has become a fundamental and emerging technology in Metaverse, facilitating the creation of immersive experiences through location-based services. In these systems, a central SC server leverages SC workers who physically travel to task locations to gather spatiotemporal environment data. However, conventional SC systems face two significant challenges: (1) the SC server, functioning as a centralized authority, can sometimes be unreliable, either due to intentional or unintentional misconduct, (2) to ensure efficient task assignment and validation, the location privacy of tasks and workers is openly accessible. In this study, we formally define location privacy preserved proof generation and verification problem (LP-PGVP) within an SC task matching scenario, with the aim to the above two challenges. Our proposed solution is a blockchain-based SC system (BlockSC), which provides a decentralized platform for task requesters and workers in the Metaverse context through calling smart contracts. We also introduce a ciphertext-based task matching scheme where task location access is granted only to eligible workers executing a task, benefiting from the design of geographic coordinate transformation and bilinear mapping methodology. To further demonstrate the task matching scheme’s operation and impact, we present an easy-to-understand case study. Our evaluation findings confirm that the proposed system effectively maintains location privacy for both SC workers and task requesters, without a considerable sacrifice in task matching efficiency.
Anthony Anyanwu, Samuel Onimisi Dawodu, Adedolapo Omotosho, Odunayo Josephine Akindote · 5 authors
This study examines blockchain applications in the USA's government systems, analyzing its effectiveness in public administration and governance. Blockchain technology, initially introduced as the underlying infrastructure for cryptocurrencies, has garnered substantial attention for its potential to transform various sectors, including government systems. This paper provides a comprehensive review of the applications and impacts of blockchain technology in the United States' governmental landscape. As governments worldwide seek innovative solutions to enhance transparency, efficiency, and security, blockchain emerges as a disruptive force with the capacity to reshape administrative processes. The study elucidates the fundamental principles of blockchain technology, emphasizing its decentralized and tamper-resistant nature. It also explores diverse applications within government systems, ranging from identity management and voting systems to supply chain traceability and public finance. The analysis delves into specific use cases, detailing how blockchain enhances data integrity, reduces fraud, and streamlines bureaucratic processes. Furthermore, the paper assesses the implications of blockchain adoption for government operations, highlighting potential benefits such as cost reduction, increased accountability, and enhanced citizen trust. Challenges and considerations, including scalability, interoperability, and regulatory frameworks, are scrutinized to provide a balanced understanding of the technology's limitations. The review extends to the United States' federal and state-level initiatives, examining pilot projects and ongoing implementations that leverage blockchain in areas such as land registries, healthcare data management, and procurement. Insights into the collaborative efforts between public and private sectors are explored, shedding light on the collaborative frameworks essential for successful blockchain integration. Ethical considerations and privacy concerns are addressed within the context of blockchain applications in government, emphasizing the need for robust safeguards to protect sensitive information while harnessing the transformative potential of the technology. This paper synthesizes the current state of blockchain technology in the United States' government systems, offering a nuanced understanding of its applications and impacts. As blockchain continues to mature and gain traction, this review contributes valuable insights for policymakers, researchers, and practitioners, fostering a deeper appreciation for the transformative potential of blockchain in shaping the future of government operations.
Blockchain technology (BT) is increasingly important in digital government as a means of efficient information management, decision making and an instrument for reform. This study presents a systematic review of BT's potential and application in land registration within low-income countries. The study uncovers diverse approaches to BT implementation that are influenced by local conditions and government structures. The study reveals that while there is a burgeoning interest in this field, actual implementations remain limited. The key barriers include resistance from government officials and a lack of local BT skills. Public blockchains have shown a high tendency for adoption, indicating a shift towards more transparent relationships between governments and citizens. The Hyperledger Fabric platform emerges as a popular choice due to its ability to provide secure, scalable, and robust solutions. However, there is a lack of clarity regarding the consensus mechanisms used, indicating a potential gap in current research practices. The study recommends an incremental approach to BT implementation, starting with non-threatening, transparent processes that could be expanded as part of broader government reform programs. Despite the potential of BT to revolutionize land registration systems and democratize tracking, it also poses a threat to existing power structures. Therefore, more robust empirical research is needed to evaluate the impacts and navigate the associated sociotechnical, legal, and institutional challenges. The study also proposes the establishment of a BT collaborative network among low-income countries to leverage shared experiences and develop a common framework for implementation. In the single instance where it was implemented in Georgia, public trust in government was restored. The study contributes to understanding how BT can be effectively harnessed to improve land registration systems in low-income countries.
This study explores the integration of Fast Healthcare Interoperability Resources (FHIR) standards in a system designed for secure and efficient management of Personal Health Records (PHRs). PHRs are crucial for patients to have control over their healthcare information and make informed decisions. Ensuring the security of this sensitive data is vital, and blockchain technology offers robust protection. However, the high cost of storing PHRs on the blockchain has led us to investigate the use of the Interplanetary File System (IPFS) alongside blockchain. Our proposed system comprises a PHR Decentralized Application (DAPPS), IPFS, Metamask, and the Ethereum Blockchain. Users input their PHR data through the DAPPS, which is stored in IPFS, and its location is registered on the Ethereum Blockchain via Metamask. Comprehensive testing validates the system's performance, with success across all test cases, confirming the feasibility of utilizing the Interplanetary File System and Ethereum Blockchain for secure PHR management while adhering to FHIR standards, fostering interoperability in healthcare data exchange.
This paper delves into the crucial aspects of authentication and authorization in modern web applications with a focus on enhancing data security. It explores the use of Node.js, a versatile server-side language, for building web applications and discusses the significance of a secure website for establishing trust between clients and servers. The research covers the implementation of authentication using packages and hashing algorithms, emphasizing the importance of "salt" and "pepper" for password security. Authorization methods, including cookies, sessions, and middleware, are also explored. The paper highlights the necessity of robust security measures to safeguard user data from the dark web and points to future directions in web security, including the role of blockchain and artificial intelligence in the WEB3 landscape.
Federated learning (FL) and blockchains exhibit significant commonality, complementarity, and alignment in various aspects, such as application domains, architectural features, and privacy protection mechanisms. In recent years, there have been notable advancements in combining these two technologies, particularly in data privacy protection, data sharing incentives, and computational performance. Although there are some surveys on blockchain-based federated learning (BFL), these surveys predominantly focus on the BFL framework and its classifications, yet lack in-depth analyses of the pivotal issues addressed by BFL. This work aims to assist researchers in understanding the latest research achievements and development directions in the integration of FL with blockchains. Firstly, we introduced the relevant research in FL and blockchain technology and highlighted the existing shortcomings of FL. Next, we conducted a comparative analysis of existing BFL frameworks, delving into the significant problems in the realm of FL that the combination of blockchain and FL addresses. Finally, we summarized the application prospects of BFL technology in various domains such as the Internet of Things, Industrial Internet of Things, Internet of Vehicles, and healthcare services, as well as the challenges that need to be addressed and future research directions.
Blockchain technology is increasingly being used in personal data protection. Inspired by the importance of data security, this paper proposes a personal data protection mechanism based on blockchain, combined with distributed hash tables and cryptography, to enhance users' control over the data generated using web applications. This paper designs this mechanism's system model and describes the three aspects in detail: data storage mechanism, data encryption mechanism, and data trading mechanism. Among them, the data storage mechanism restricts user data to be stored only in the local storage space of the user terminal, the decentralized blockchain network, and the distributed hash table network to ensure that enterprises providing network applications cannot privately store user interaction data, the encryption mechanism is responsible for encrypting all user data recorded in the network and allows users to control the key of the data to ensure the security of the user data in the blockchain and distributed hash tables, the data transaction mechanism allows users to trade their data, and to incentivize enterprises to assist users in collecting personal data, data transaction contracts are built into the data transaction mechanism, allowing enterprises to receive a share of the revenue from user data transactions. Then, for data transactions, use the Stackelberg game to simulate the revenue sharing between users and service providers in data trading to incentivize enterprises providing web services to assist users in collecting their data. The simulation results show that when the number of users is 1000, the revenues of this scheme for service providers are 31%, 561%, and 19% higher than the existing scheme. Finally, the personal data protection platform is implemented by code to verify the feasibility of the theory proposed in this paper in personal data protection.
Mobile crowdsourcing (MCS) is an emerging paradigm that enables the outsourcing of a complex task to a group of mobile devices. The ability to utilize the collective power of mobile devices and human intelligence makes MCS a significant tool in various scenarios. Nevertheless, it faces practical challenge in protecting user privacy due to the sensitive nature of information collected by mobile devices. Additionally, the inherent openness of MSC and the heterogeneity of mobile devices raise reliability concerns among participants. To address these challenges, by integrating Federated Learning with the pairwise additive masking technique and the Chinese Remainder Theorem, we propose a Blockchain-based Privacy-preserving Federated Learning (BPFL) framework for mobile crowdsourcing, which allows mobile participants to collaboratively solve a crowdsourced machine learning task while preserving privacy. Besides, it employs blockchain technology to record the training process in a transparent and tamper-proof ledger. This ledger guarantees the verifiability of aggregation results and the fair distribution of training rewards, thereby enhancing trust and fairness. We prove that our BPFL supports privacy protection and trust mechanism simultaneously and resists inference and collusion attacks. Experimental results show that our BPFL can achieve high performance in terms of computation cost, communication cost and model accuracy, which is friendly for mobile users with resource-constrained devices in MCS ecosystems.