Juan Manuel Sobral, Mario De los Santos, Martin Solari
et al.
Blockchain technology continues to promise transformative impact across domains such as supply chains, finance, and the Internet of Things (IoT). However, the rapid growth and increasing heterogeneity of blockchain platforms have made architectural decision-making progressively more complex for software architects. This study extends and updates a previous Multivocal Literature Review (MLR) to systematically identify and characterize active blockchain networks across foundational protocol layers. We analyze key architectural dimensions including consensus mechanisms, decentralization and access control models, smart contract support, block and ledger structures, interoperability features, and architectural lineage. Drawing on both academic and gray literature, we characterize a total of 147 blockchain networks spanning Layers-0 through-2. Our findings reveal an ecosystem largely driven by industrial innovation, with limited consolidation in the formal academic literature. The resulting architectural mappings aim to support software architects in making informed, evidence-based decisions when integrating blockchain technologies into software-intensive systems.
Petar Radanliev, Petar Radanliev, Carsten Maple
et al.
IntroductionDigital identity infrastructures used in electronic passports, national eID schemes, and federated authentication systems rely predominantly on centralised registries and classical public key cryptography. These architectures enable large-scale identity correlation, mass data aggregation, and single points of compromise, while remaining vulnerable to quantum attacks against RSA and elliptic-curve cryptography. There is no deployed identity framework that simultaneously provides post-quantum security, cryptographic privacy guarantees, and decentralised trust.MethodsThis study proposes a quantum-proof digital passport architecture combining lattice-based post-quantum cryptography, decentralised blockchain identifiers, and transformer-based decentralised artificial intelligence. The framework employs NIST-aligned post-quantum key encapsulation and digital signatures, zero-knowledge proofs for selective disclosure of identity attributes, and homomorphic encryption for encrypted identity verification. Blockchain oracles and decentralised identifiers enforce credential integrity and auditability without reliance on central identity providers. Transformer attention mechanisms support adaptive identity validation while preventing persistent identity profiling.ResultsArchitectural analysis shows that the proposed system prevents quantum-enabled credential forgery, retrospective decryption, and cross-service identity linkability. Zero-knowledge verification removes plaintext exposure of personal data, and decentralised credential control eliminates central compromise vectors. The design remains interoperable with existing passport and eID infrastructures.DiscussionThe results demonstrate that secure post-quantum digital identity requires the combined application of quantum-resistant cryptography, decentralised governance, and cryptographic privacy enforcement.
Abstract Consensus is a fundamental problem of distributed computing. While this problem has been known to be unsolvable since 1985, existing protocols were designed these past three decades to solve consensus under various assumptions. Today, with the recent advent of blockchains, various consensus implementations were proposed to make replicas reach an agreement on the order of transactions updating what is often referred to as a distributed ledger. Very little work has however been devoted to explore its theoretical ramifications. As a result existing proposals are sometimes misunderstood and it is often unclear whether the problems arising during their executions are due to implementation bugs or more fundamental design issues. In this paper, we discuss the mainstream blockchain consensus algorithms and how the classic Byzantine consensus can be revisited for the blockchain context. In particular, we discuss proof-of-work consensus and illustrate the differences between the Bitcoin and the Ethereum proof-of-work consensus algorithms. Based on these definitions, we warn about the dangers of using these blockchains without understanding precisely the guarantees their consensus algorithm offers. In particular, we survey attacks against the Bitcoin and the Ethereum consensus algorithms. We finally discuss the advantage of the recent Blockchain Byzantine consensus definition over previous definitions, and the promises offered by emerging consistent blockchains.
In this work, we acknowledge the need for software engineers to devise specialized tools and techniques for blockchain-oriented software development. Ensuring effective testing activities, enhancing collaboration in large teams, and facilitating the development of smart contracts all appear as key factors in the future of blockchain-oriented software development.
To improve the accuracy of diagnosis and the effectiveness of treatment, a framework of parallel healthcare systems (PHSs) based on the artificial systems + computational experiments + parallel execution (ACP) approach is proposed in this paper. PHS uses artificial healthcare systems to model and represent patients’ conditions, diagnosis, and treatment process, then applies computational experiments to analyze and evaluate various therapeutic regimens, and implements parallel execution for decision-making support and real-time optimization in both actual and artificial healthcare processes. In addition, we combine the emerging blockchain technology with PHS, via constructing a consortium blockchain linking patients, hospitals, health bureaus, and healthcare communities for comprehensive healthcare data sharing, medical records review, and care auditability. Finally, a prototype named parallel gout diagnosis and treatment system is built and deployed to verify and demonstrate the effectiveness and efficiency of the blockchain-powered PHS framework.
Blockchain technology has received great attention in recent years. However, the data volume of blockchain grows continuously due to the features that cannot be deleted and can only be added. Currently, the total size of Bitcoin blockchain ledger has reached 200GB. Its high demand for storage space and bandwidth to synchronize data with the network prevents many nodes from joining the network.This is not only not conducive to the expansion of this decentralized network, but also becomes the bottleneck of the development of blockchain technology. This paper proposes an IPFS-based blockchain data storage model to solve this problem.In this paper, the miners deposit the transaction data into the IPFS network and pack the returned IPFS hash of transaction into the block. Utilizing the characteristics of the IPFS network and the features of the IPFS hash, the blockchain data is greatly reduced. The scheme is applied to the Bitcoin blockchain. According to the experimental results, the compression ratio can reach 0.0817. According to the analysis, it also has good performance in terms of security and synchronization speed of new node.
Federico Calandra, Marco Bernardo, Andrea Esposito
et al.
Blockchains are widely recognized for their immutability, which provides robust guarantees of data integrity and transparency. However, this same feature poses significant challenges in real-world situations that require regulatory compliance, correction of erroneous data, or removal of sensitive information. Redactable blockchains address the limitations of traditional ones by enabling controlled, auditable modifications to blockchain data, primarily through cryptographic mechanisms such as chameleon hash functions and alternative redaction schemes. This report examines the motivations for introducing redactability, surveys the cryptographic primitives that enable secure edits, and analyzes competing approaches and their shortcomings. Special attention is paid to the practical deployment of redactable blockchains in private settings, with discussions of use cases in healthcare, finance, Internet of drones, and federated learning. Finally, the report outlines further challenges, also in connection with reversible computing, and the future potential of redactable blockchains in building law-compliant, trustworthy, and scalable digital infrastructures.
Asadullah Tariq, Tariq Qayyum, Saed Alrabaee
et al.
Cyberthreat intelligence sharing is a critical aspect of cybersecurity, and it is essential to understand its definition, objectives, benefits, and impact on society. Blockchain and Distributed Ledger Technology (DLT) are emerging technologies that have the potential to transform intelligence sharing. This paper aims to provide a comprehensive understanding of intelligence sharing and the role of blockchain and DLT in enhancing it. The paper addresses questions related to the definition, objectives, benefits, and impact of intelligence sharing and provides a review of the existing literature. Additionally, the paper explores the challenges associated with blockchain and DLT and their potential impact on security and privacy. The paper also discusses the use of DLT and blockchain in security and intelligence sharing and highlights the associated challenges and risks. Furthermore, the paper examines the potential impact of a National Cybersecurity Strategy on addressing cybersecurity risks. Finally, the paper explores the experimental set up required for implementing blockchain and DLT for intelligence sharing and discusses the curricular ramifications of intelligence sharing.
This study investigates the determinants of token valuation in blockchain ecosystems, focusing on the roles of crowdfunding support and network centrality. Using a dynamic panel dataset of token projects from 2015 to 2023, we apply the Arellano-Bond Generalized Method of Moments (GMM) estimator to control for valuation persistence and address potential endogeneity. The analysis reveals that crowdfunding backing significantly increases token valuation, while network centrality exerts a positive but nonlinear effect. Additionally, ownership concentration negatively impacts valuation, whereas project age contributes positively. Robustness checks using a nonlinear specification and instrumental variable (2SLS) approach confirm these findings. The results underscore the importance of transparent crowdfunding, diversified network ties, and decentralized ownership structures in driving sustainable token performance. Policy recommendations include enhancing disclosure standards for token offerings, incentivizing decentralized governance, and supporting long-term ecosystem development to ensure healthier digital asset markets.
Federated learning has emerged as a promising distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, the increasing sophistication of privacy attacks and evolving regulatory requirements have exposed critical vulnerabilities in current FL systems. This paper provides a comprehensive analysis of privacy threats in federated learning, identifying three primary attack surfaces: gradient-based reconstruction, aggregation-phase breaches, and membership leakage during participant selection. This paper examines how these vulnerabilities manifest differently across healthcare, financial, and industrial applications, with sector-specific risks ranging from medical image reconstruction to inference of sensitive financial attributes. The study systematically evaluates three categories of defense mechanisms: differential privacy techniques (including adaptive noise injection and hybrid approaches), cryptographic methods (homomorphic encryption and secure multi-party computation), and blockchain-based distributed architectures. This paper analyzes the inherent trade-offs between privacy protection and model performance, presenting optimization strategies such as adaptive privacy budgeting and lightweight encryption to mitigate accuracy degradation. The paper further discusses compliance challenges posed by emerging regulations like the EU AI Act and FDA guidelines, highlighting the need for verifiable privacy proofs in sensitive domains. Finally, this paper concludes with a summary and outlook.
The Indian aquaculture industry, a global leader, faces persistent challenges in marketing, pricing, and supply chain management that limit profitability and market expansion. This study investigates how marketing channels, pricing strategies, and supply chain practices influence commercial success, focusing on West Godavari (Andhra Pradesh), Hooghly (West Bengal), and Kollam (Kerala). Semi-structured interviews with 45 stakeholders, including farmers, marketers, and supply chain managers—reveal that using online platforms and targeting export markets significantly enhances reach and profitability. Value-based pricing improves margins by aligning prices with product quality and customer perception. Efficient supply chain management, particularly through blockchain and automation, is vital for maintaining product integrity and meeting market demands. However, high implementation costs, lack of technical expertise, and resistance to change hinder adoption, especially among smaller operators. The study concludes that sustainable growth requires integrating diversified marketing strategies, value-driven pricing, and tech-enabled logistics. Key recommendations include investing in digital tools, embracing innovation, and fostering stakeholder collaboration to address operational barriers and strengthen the industry’s economic impact.
Business ethics, Social responsibility of business
This study evaluates the role of Generative AI in optimizing digital supply chain performance, focusing on IoT integration, predictive analytics, and blockchain security. The primary objective is to determine which AI-driven initiatives offer the greatest benefits in enhancing resilience and operational efficiency. A structured multi-criteria decision-making approach is applied using the ELECTRE III method, leveraging quantitative data from DHL’s operational records (2022–2025). The evaluation is conducted with a panel of 18 industry experts, including logistics professionals and AI specialists, who participated in structured interviews and expert assessments to establish weighting criteria and performance metrics. Findings indicate that IoT-driven real-time tracking and predictive analytics for maintenance rank highest in enhancing supply chain resilience, improving operational responsiveness, and reducing downtime. Additionally, blockchain-supported security mechanisms reinforce data integrity and transparency, strengthening logistics security. Conversely, OCR-based automation and NLP-powered logistics systems demonstrate comparatively lower impact, emphasizing the need for targeted AI adoption strategies. This study contributes to structured AI evaluation methodologies by establishing a repeatable decision-making framework, ensuring scalability beyond DHL’s logistics operations. Limitations include the reliance on industry-specific datasets, which require further validation across diverse supply chain environments.
Since the mid-1990s, the evolution of internet technologies has significantly transformed global connectivity and digital interaction. Today, advances in computing and networking continue to support the development of emerging paradigms such as the metaverse and digital twins—concepts that aspire to bridge physical and digital experiences. Parallel to this, blockchain technology is reshaping traditional notions of trust by enabling immutable transaction records and smart contract automation, thereby fostering the rise of decentralized autonomous organizations (DAOs). Building on these foundations, this study presents a biometric blockchain-based e-passport system designed to improve the operational efficiency of automated border control (ABC) systems. At the core of our approach is the concept of a DAO-inspired framework for border control wherein identity verification and management tasks are executed through atomic smart contracts and recorded immutably on the blockchain. Our system incorporates biometric authentication and decentralized identity features to digitize border documentation and automate verification processes. This creates a secure, verifiable digital representation of an individual’s identity that can interact with ABC workflows. Performance evaluations conducted using Hyperledger Caliper demonstrate the potential of the proposed system, showing a 3.5-fold improvement in processing efficiency compared to traditional ABC setups.
Privacy, facilitated by a confluence of cryptography and decentralization, is one of the primary motivations for the adoption of cryptocurrencies like Bitcoin. Alas, Bitcoins privacy promise has proven illusory, and despite growing interest in privacy-centric blockchains, most blockchain users remain susceptible to privacy attacks that exploit network-layer information and access patterns that leak as users interact with blockchains. Understanding if and how blockchain-based applications can provide strong privacy guarantees is a matter of increasing urgency. Many researchers advocate using anonymous communications networks, such as Tor, to ensure access privacy. We challenge this approach, showing the need for mechanisms through which non-anonymous users can (i) publish transactions that cannot be linked to their network addresses or to their other transactions, and (ii) fetch details of specific transactions without revealing which transactions they seek. We hope this article inspires blockchain researchers to think beyond Tor and tackle these important access privacy problems head-on.
The food supply chain is a complex system that involves a multitude of “stakeholders” such as farmers, production factories, distributors, retailers and consumers. “Information asymmetry” between stakeholders is one of the major factors that lead to food fraud. Some current researches have shown that applying blockchain can help ensure food safety. However, they tend to study the traceability of food but not its supervision. This paper provides a blockchain-based credit evaluation system to strengthen the effectiveness of supervision and management in the food supply chain. The system gathers credit evaluation text from traders by smart contracts on the blockchain. Then the gathered text is analyzed directly by a deep learning network named Long Short Term Memory (LSTM). Finally traders’ credit results are used as a reference for the supervision and management of regulators. By applying blockchain, traders can be held accountable for their actions in the process of transaction and credit evaluation. Regulators can gather more reliable, authentic and sufficient information about traders. The results of experiments show that adopting LSTM results in better performance than traditional machine learning methods such as Support Vector Machine (SVM) and Navie Bayes (NB) to analyze the credit evaluation text. The system provides a friendly interface for the convenience of users.
Abstract Blockchain is one of the most disruptive and promising emerging technologies, and it appears to have the potential for significantly affecting the accounting and auditing fields. Using blockchain technology, zero-knowledge proof, and homomorphic encryption, this paper presents a design for a blockchain-based transaction processing system (TPS) and develops a prototype to demonstrate the functionality of the blockchain-based TPS in real-time accounting, continuous monitoring and fraud prevention. The computational performance of a blockchain-based TPS versus relational databases is evaluated and discussed. In anticipation of the wider applicability of blockchain technology to support enterprise information systems and continuous monitoring systems, this paper presents an innovative design that utilizes the advantages of blockchain technology while overcoming some of the key barriers to its adoption.
Blockchain is a fast-disruptive technology becoming a key instrument in share economy. In recent years, Blockchain has received considerable attention from many researchers and government institutions. This paper aims to present the Blockchain and smart contract for a specific domain which is real estate. A detailed design of smart contract is presented and then a use case for renting residential and business buildings is examined.