Search Results (38)

We examine the use of a Geometric Distribution for pre-calculating the publication deadlines of blocks in a simulation of proof-of-work Blockchain. Specifically, we focus on Discrete-Event Simulation, where the simulator identifies events to be simulated, calculates their deadlines, places them in an Event Queue ordered by deadline, and processes them sequentially. In Blockchain, these events include the publication and reception of a block by each Miner. While a Geometric Distribution allows the calculation of block publication deadlines in the absence of Difficulty updates, in the case of evolving Difficulty, it must be extended to a non-homogeneous Geometric Distribution. To address this issue, we introduce the Geometric Distribution with a Variable Probability, a non-homogeneous Geometric Distribution that enables the calculation of block publication deadlines in the presence of Difficulty Regulation—a distinctive feature of proof-of-work Blockchain. We then present the architecture and operating principles of a Discrete-Event Simulator based on this distribution, along with simulation results that validate our approach. Full article

Blockchain technology has evolved beyond financial transactions to revolutionize trust systems. This paper presents a blockchain-based model for decentralized rental agreements and dispute resolution (DRADR). By leveraging smart contracts and implementing two distinct arbitration approaches, our model offers flexible solutions for rental agreement automation, transparency enhancement, and impartial dispute resolution. Our study provides a comprehensive technical analysis of both approaches through theoretical frameworks, smart contract implementation, game-theoretic modeling, and comparative evaluation across multiple legal jurisdictions. We explore the potential of blockchain technology to address long-standing challenges in traditional rental systems, such as power imbalances, inefficiencies, and legal disputes. Key contributions include the integration of decentralized and local justice systems; a detailed game-theoretic analysis of strategic behaviors; and comparative insights into gas efficiency, economic viability, and jurisdictional adaptability across both arbitration approaches. This research paves the way for a more equitable and transparent rental market and contributes to the broader acceptance of blockchain-based solutions in everyday transactions. Full article

This research presents a novel framework and experimental results that combine zero-knowledge proofs (ZKPs) with private blockchain technology to safeguard whistleblower privacy while ensuring secure digital evidence submission and verification. For example, whistleblowers involved in corporate fraud cases can submit sensitive financial records anonymously while maintaining the credibility of the evidence. The proposed framework introduces several key innovations, including a private blockchain implementation utilising proof-of-work (PoW) consensus to ensure immutable storage and thorough scrutiny of submitted evidence, with mining difficulty dynamically aligned to the sensitivity of the data. It also features an adaptive difficulty mechanism that automatically adjusts computational requirements based on the sensitivity of the evidence, providing tailored protection levels. In addition, a unique two-phase validation process is incorporated, which generates a digital signature from the evidence alongside random challenges, significantly improving security and authenticity. The integration of ZKPs enables iterative hash-based verification between parties (Prover and Verifier) while maintaining the complete privacy of the source data. This research investigates the whistleblower’s niche in traditional digital evidence management systems (DEMSs), prioritising privacy without compromising evidence integrity. Experimental results demonstrate the framework’s effectiveness in preserving anonymity while assuring the authenticity of the evidence, making it useful for judicial systems and organisations handling sensitive disclosures. This paper signifies notable progress in secure whistleblowing systems, offering a way to juggle transparency with informant confidentiality. Full article

The paper presents business models (BMs) for blockchain-based businesses. The paper is a study of IT-aligned BMs categorized by the concepts and possibilities of blockchain business applications. The research aimed to recognize and analyze the extent and directions in which blockchain architectures influence the means of conducting businesses. A set of almost 40,000 decentralized applications is examined to justify the rationale behind the presented analysis. This is an argumentative study that uses the design-oriented approach, as it is suitable for addressing real-world problems, like analyzing business models, while ensuring that artifacts are created and evaluated under methodological standards. Firstly, the concept of a business model is analyzed. Then, a theoretical analysis of different business models is made to identify the ones that are well aligned with the decentralized vision of business and the ones that are obsolete or inoperative from the blockchain business-conducting perspective. In the end, the outcome is applied to examples of existing business startups. Fifteen identified BMs in 7 business sector groups are recognized and 55 cases are detected. Full article

Blockchain technology has risen in recent years from its initial application in finance to gain prominence across diverse sectors, including digital forensics. The possible application of blockchain technology to digital forensics is now becoming increasingly explored with many researchers now looking into the unique inherent properties that blockchain possesses to address the inherent challenges in this sector such as evidence tampering, the lack of transparency, and inadmissibility in court. Despite the increasing interest in integrating blockchain technology into the field of digital forensics and its domains, no systematic literature review currently exists to provide a holistic perspective on this integration. It is a challenge to find a comprehensive resource that examines how blockchain is being applied to enhance the digital forensics process. This paper provides a systematic literature review to explore the application of blockchain technology in digital forensics, focusing on its potential to address these challenges and enhance forensic methodologies. Through a rigorous review process, this paper examines selected studies to identify diverse frameworks, methodologies, and blockchain-driven enhancements applied to digital forensic investigations. The discussion highlights how blockchain properties such as immutability, transparency, and automation have been leveraged to improve evidence management and forensic workflows. Furthermore, this paper explores the common applications of blockchain-based forensic solutions across various domains and phases while addressing the associated limitations and challenges. Open issues and future research directions, including unexplored domains and operational gaps, are also discussed. This study provides valuable insights for researchers, investigators, and policymakers by offering a comprehensive overview of the state of the art in blockchain-based digital forensics, summarizing key contributions and limitations, and identifying pathways for advancing the field. Full article

Decentralization is a core principle of blockchain technology and Decentralized Autonomous Organizations (DAOs), enhancing security and resilience by distributing control across a network. Traditional metrics like the Gini coefficient and Nakamoto coefficient often fall short in capturing the complex dynamics of decentralization. This paper introduces the Apokedro decentralization index, a metric that evaluates decentralization by considering the probabilities of all possible subsets of nodes that could collectively centralize control. These concepts from game theory, such as the Nash equilibrium, and the Apokedro index, when incorporated, provide a nuanced assessment of centralization risks. Key contributions include the mathematical formulation of the index, an efficient computational algorithm utilizing pruning techniques, and benchmarking experiments that compare the index performance against traditional metrics across various statistical distributions. The Apokedro index offers a comprehensive tool for measuring decentralization in blockchain networks and DAOs. Full article

The education sector has witnessed a significant shift towards digitising student records, with relevant data now stored in centralized data repositories. While traditional identity management solutions in education are functional, they often face various challenges, including data privacy concerns, limited portability, and reliability challenges. As the volume of student data continues to grow, inadequate data management practices have led to several problems. These include students losing control and empowerment over their educational information, increased vulnerability to potential data breaches and unauthorized access, a lack of transparency and accountability, data silos and inconsistencies, and administrative inefficiencies. To address these limitations, the implementation of a blockchain-assisted self-sovereign identity (Ba-SSI) concept in the education system presents a viable solution. Self-sovereign identity (SSI) represents a paradigm shift from traditional centralized identity systems, allowing individuals to maintain full control of their identity data without relying on centralized authorities. By leveraging the decentralized nature, SSI frameworks can ensure security, interoperability, and scalability, thereby improving user-centric identity management. This survey paper explores the potential of Ba-SSI within the context of education. It thoroughly reviews the current state of digital identity management in education, highlighting the limitations of conventional systems and the emerging role of blockchain technology in addressing these challenges. The paper discusses the fundamental principles of blockchain technology and how it can be utilized to enhance security, interoperability, and scalability in identity management. Additionally, it examines the insights and benefits of this approach for the education system. Finally, the paper concludes by addressing the issues, challenges, benefits, and future research directions in this domain, underscoring the potential of Ba-SSI solutions to revolutionize the management and empowerment of student data within the education sector. Full article

Despite the many consensus algorithms being used in blockchains, proof of work (PoW) is still the most common nowadays. The state-of-the-art mining strategy for PoW-based blockchain protocols consists of including as many transactions as possible in a block to maximize the block reward. Unfortunately, this strategy maximizes the block orphaning probability too. Recently, we proposed a rational mining strategy aimed at carefully balancing the trade-off between the block reward and the risk of block orphaning. In this work, we present PROACTION, a PROfitable transACTions selectION greedy algorithm that implements such a strategy. We evaluate the algorithm both analytically and experimentally on Bitcoin by assuming a variable random percentage of winning miners adopting PROACTION. Experiments show that when executing PROACTION, miners gain higher long-term rewards than when using the state-of-the-art strategy. The gain is in the order of the block orphaning probability. This result is particularly relevant for those PoW-based blockchain protocols in which such a probability is significant. Full article

Federated learning (FL) has emerged as an efficient machine learning (ML) method with crucial privacy protection features. It is adapted for training models in Internet of Things (IoT)-related domains, including smart healthcare systems (SHSs), where the introduction of IoT devices and technologies can arise various security and privacy concerns. However, as FL cannot solely address all privacy challenges, privacy-enhancing technologies (PETs) and blockchain are often integrated to enhance privacy protection in FL frameworks within SHSs. The critical questions remain regarding how these technologies are integrated with FL and how they contribute to enhancing privacy protection in SHSs. This survey addresses these questions by investigating the recent advancements on the combination of FL with PETs and blockchain for privacy protection in smart healthcare. First, this survey emphasizes the critical integration of PETs into the FL context. Second, to address the challenge of integrating blockchain into FL, it examines three main technical dimensions such as blockchain-enabled model storage, blockchain-enabled aggregation, and blockchain-enabled gradient upload within FL frameworks. This survey further explores how these technologies collectively ensure the integrity and confidentiality of healthcare data, highlighting their significance in building a trustworthy SHS that safeguards sensitive patient information. Full article

The proliferation of Internet of Things (IoT) devices has facilitated the exchange of information among individuals and devices. This development has introduced several challenges, including increased vulnerability to potential cyberattacks and digital forensics. IoT forensic investigations need to be managed in a forensically sound manner using a standard framework. However, adopting traditional digital forensics tools introduces various challenges, such as identifying all IoT devices and users at the crime scene. Therefore, collecting evidence from these devices is a major problem. This paper proposes a permissioned blockchain integration solution for IoT forensics (PBCIS-IoTF) that aims to observe data transactions within the blockchain. The PBCIS-IoTF framework designs and tests Hyperledger blockchains simulated with a Raspberry Pi device and chaincode to address the challenges of IoT forensics. This blockchain is deployed using multiple nodes within the network to avoid a single point of failure. The authenticity and integrity of the acquired evidence are analysed by comparing the SHA-256 hash metadata in the blockchain of all peers within the network. We further integrate webpage access with the blockchain to capture the forensics data from the user’s IoT devices. This allows law enforcement and a court of law to access forensic evidence directly and ensures its authenticity and integrity. PBCIS-IoTF shows high authenticity and integrity across all peers within the network. Full article

The integrity of global elections is increasingly under threat from artificial intelligence (AI) technologies. As AI continues to permeate various aspects of society, its influence on political processes and elections has become a critical area of concern. This is because AI language models are far from neutral or objective; they inherit biases from their training data and the individuals who design and utilize them, which can sway voter decisions and affect global elections and democracy. In this research paper, we explore how AI can directly impact election outcomes through various techniques. These include the use of generative AI for disseminating false political information, favoring certain parties over others, and creating fake narratives, content, images, videos, and voice clones to undermine opposition. We highlight how AI threats can influence voter behavior and election outcomes, focusing on critical areas, including political polarization, deepfakes, disinformation, propaganda, and biased campaigns. In response to these challenges, we propose a Blockchain-based Deepfake Authenticity Verification Framework (B-DAVF) designed to detect and authenticate deepfake content in real time. It leverages the transparency of blockchain technology to reinforce electoral integrity. Finally, we also propose comprehensive countermeasures, including enhanced legislation, technological solutions, and public education initiatives, to mitigate the risks associated with AI in electoral contexts, proactively safeguard democracy, and promote fair elections. Full article

Blockchain technologies have the potential to fundamentally change logistics and supply chain management. By leveraging the capabilities of blockchain technology, businesses can increase efficiency, reduce costs, and improve security and trust in operations. However, there are still difficulties to overcome in terms of uptake and implementation. This article examines the various blockchain technologies applicable in the field of logistics, presents the benefits and limitations of blockchain technologies in this aspect, and offers a summary of the existing technologies used in the logistics sector. According to this, blockchain-based models applicable both to a specific stage of the logistics process (e.g., transportation of goods, materials, and feedstocks; management of warehouse operations; cargo tracking; etc.) and related insurance services have been proposed. The proposed models have been tested in a lab environment on the HyperLedger Fabric platform, and the results show that they are fully functional. Full article

When migrating smart contracts from one blockchain platform to another, there are potential security risks. This is because different blockchain platforms have different environments and characteristics for executing smart contracts. The focus of this paper is to study the security risks associated with the migration of smart contracts from Ethereum to Arbitrum. We collected relevant data and analyzed smart contract migration cases to explore the differences between Ethereum and Arbitrum in areas such as Arbitrum cross-chain messaging, block properties, contract address alias, and gas fees. From the 36 types of smart contract migration cases we identified, we selected four typical types of cases and summarized their security risks. The research shows that smart contracts deployed on Ethereum may face certain potential security risks during migration to Arbitrum, mainly due to issues inherent in public blockchain characteristics, such as outdated off-chain data obtained by the inactive sequencer, logic errors based on time, failed permission checks, and denial of service (DOS) attacks. To mitigate these security risks, we proposed avoidance methods and provided considerations for users and developers to ensure a secure migration process. It is worth noting that this study is the first to conduct an in-depth analysis of the secure migration of smart contracts from Ethereum to Arbitrum. Full article

The integrity of democratic processes relies on secure and reliable election systems, yet achieving this reliability is challenging. This paper introduces the Post-Quantum Secured Multiparty Computed Hierarchical Authoritative Consensus Blockchain (PQMPCHAC-Bchain), a novel e-voting system designed to overcome the limitations of current Biometric Electronic Voting Machine (EVM) systems, which suffer from trust issues due to closed-source designs, cyber vulnerabilities, and regulatory concerns. Our primary objective is to develop a robust, scalable, and secure e-voting framework that enhances transparency and trust in electoral outcomes. Key contributions include integrating hierarchical authorization and access control with a novel consensus mechanism for proper electoral governance. We implement blockchain sharding techniques to improve scalability and propose a multiparty computed token generation system to prevent fraudulent voting and secure voter privacy. Post-quantum cryptography is incorporated to safeguard against potential quantum computing threats, future-proofing the system. Additionally, we enhance authentication through a deep learning-based face verification model for biometric validation. Our performance analysis indicates that the PQMPCHAC-Bchain e-voting system offers a promising solution for secure elections. By addressing critical aspects of security, scalability, and trust, our proposed system aims to advance the field of electronic voting. This research contributes to ongoing efforts to strengthen the integrity of democratic processes through technological innovation. Full article

Blockchain has emerged as a solution for ensuring accurate and truthful environmental variable monitoring needed for the management of pollutants and natural resources. The immutability property of blockchain helps protect the measured data on pollution and natural resources to enable truthful reporting and effective management and control of polluting agents. However, specifics on what to measure, how to use blockchain, and highlighting which blockchain frameworks have been adopted need to be explored to fill the research gaps. Therefore, we review existing works on the use of blockchain for monitoring and managing environmental variables in this paper. Specifically, we examine existing blockchain applications on greenhouse gas emissions, solid and plastic waste, food waste, food security, water usage, and the circular economy and identify what motivates the adoption of blockchain, features sought, used blockchain frameworks and consensus algorithms, and the adopted supporting technologies to complement data sensing and reporting. We conclude the review by identifying practical works that provide implementation details for rapid adoption and remaining challenges that merit future research. Full article