1,404 research outputs found

    Consortium Blockchain for Security and Privacy-Preserving in E-government Systems

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    Since its inception as a solution for secure cryptocurrencies sharing in 2008, the blockchain technology has now become one of the core technologies for secure data sharing and storage over trustless and decentralised peer-to-peer systems. E-government is amongst the systems that stores sensitive information about citizens, businesses and other affiliates, and therefore becomes the target of cyber attackers. The existing e-government systems are centralised and thus subject to single point of failure. This paper proposes a secure and decentralised e-government system based on the consortium blockchain technology, which is a semi-public and decentralised blockchain system consisting of a group of pre-selected entities or organisations in charge of consensus and decisions making for the benefit of the whole network of peers. In addition, a number of e-government nodes are pre-selected to perform the tasks of user and transaction validation before being added to the blockchain network. Accordingly, e-government users of the consortium blockchain network are given the rights to create, submit, access, and review transactions. Performance evaluation on single transaction time and transactions processed per second demonstrate the practicability of the proposed consortium blockchain-based e-government system for secure information sharing amongst all stakeholders

    Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

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    Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

    Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination

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    Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning: How can the output of AI systems be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives

    Challenges in Blockchain as a Solution for IoT Ecosystem Threats and Access Control: A Survey

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    The Internet of Things (IoT) is increasingly influencing and transforming various aspects of our daily lives. Contrary to popular belief, it raises security and privacy issues as it is used to collect data from consumers or automated systems. Numerous articles are published that discuss issues like centralised control systems and potential alternatives like integration with blockchain. Although a few recent surveys focused on the challenges and solutions facing the IoT ecosystem, most of them did not concentrate on the threats, difficulties, or blockchain-based solutions. Additionally, none of them focused on blockchain and IoT integration challenges and attacks. In the context of the IoT ecosystem, overall security measures are very important to understand the overall challenges. This article summarises difficulties that have been outlined in numerous recent articles and articulates various attacks and security challenges in a variety of approaches, including blockchain-based solutions and so on. More clearly, this contribution consolidates threats, access control issues, and remedies in brief. In addition, this research has listed some attacks on public blockchain protocols with some real-life examples that can guide researchers in taking preventive measures for IoT use cases. Finally, a future research direction concludes the research gaps by analysing contemporary research contributions

    Unravelling Ariadne’s Thread: Exploring the Threats of Decentralised DNS

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    The current landscape of the core Internet technologies shows considerable centralisation with the big tech companies controlling the vast majority of traffic and services. This situation has sparked a wide range of decentralisation initiatives with blockchain technology being among the most prominent and successful innovations. At the same time, over the past years there have been considerable attempts to address the security and privacy issues affecting the Domain Name System (DNS). To this end, it is claimed that Blockchain-based DNS may solve many of the limitations of traditional DNS. However, such an alternative comes with its own security concerns and issues, as any introduction and adoption of a new technology typically does - let alone a disruptive one. In this work we present the emerging threat landscape of blockchain-based DNS and we empirically validate the threats with real-world data. Specifically, we explore a part of the blockchain DNS ecosystem in terms of the browser extensions using such technologies, the chain itself (Namecoin and Emercoin), the domains, and users who have been registered in these platforms. Our findings reveal several potential domain extortion attempts and possible phishing schemes. Finally, we suggest countermeasures to address the identified threats, and we identify emerging research themes

    Pathways to Online Hate: Behavioural, Technical, Economic, Legal, Political & Ethical Analysis.

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    The Alfred Landecker Foundation seeks to create a safer digital space for all. The work of the Foundation helps to develop research, convene stakeholders to share valuable insights, and support entities that combat online harms, specifically online hate, extremism, and disinformation. Overall, the Foundation seeks to reduce hate and harm tangibly and measurably in the digital space by using its resources in the most impactful way. It also aims to assist in building an ecosystem that can prevent, minimise, and mitigate online harms while at the same time preserving open societies and healthy democracies. A non-exhaustive literature review was undertaken to explore the main facets of harm and hate speech in the evolving online landscape and to analyse behavioural, technical, economic, legal, political and ethical drivers; key findings are detailed in this report

    Decentralized Telemedicine Framework for a Smart Healthcare Ecosystem

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    The healthcare sector is one of the most rapidly growing sectors globally. With the ever-growing technology, patient care, regulatory compliance, and digital transformation, there is an increased need for healthcare sectors to collaborate with all stakeholders – both within the healthcare ecosystem and in concurring industries. In recent times, telemedicine has proven to provide high quality, affordable, and predominantly adapted healthcare services. However, telemedicine suffers from several risks in implementation, such as data breach, restricted access across medical fraternity, incorrect diagnosis and prescription, fraud, and abuse. In this work, introduce blockchain-based framework that would unlock the future of the healthcare sector and improved services. Our proposed solution utilizing Ethereum smart contracts to develop a transparent, tamper-proof telemedicine healthcare framework, and ensure the integrity of sensitive patient data eliminating a central administrator. Moreover, the smart contract regulates the interaction between all the parties involved in the network and keeps the patient meticulously informed about the transactions in the network

    A Survey of COVID-19 Contact Tracing Apps

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    The recent outbreak of COVID-19 has taken the world by surprise, forcing lockdowns and straining public health care systems. COVID-19 is known to be a highly infectious virus, and infected individuals do not initially exhibit symptoms, while some remain asymptomatic. Thus, a non-negligible fraction of the population can, at any given time, be a hidden source of transmissions. In response, many governments have shown great interest in smartphone contact tracing apps that help automate the difficult task of tracing all recent contacts of newly identified infected individuals. However, tracing apps have generated much discussion around their key attributes, including system architecture, data management, privacy, security, proximity estimation, and attack vulnerability. In this article, we provide the first comprehensive review of these much-discussed tracing app attributes. We also present an overview of many proposed tracing app examples, some of which have been deployed countrywide, and discuss the concerns users have reported regarding their usage. We close by outlining potential research directions for next-generation app design, which would facilitate improved tracing and security performance, as well as wide adoption by the population at large.Comment: Paper has been accepted for publication in IEEE Access. Currently available on IEEE ACCESS early access (see DOI
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