Blockchain Papers

Yulong Wang, Yufeng Zhang, Zhuyu Zhang, Liting Gao · 5 authors

No abstract is available for this record.

Y. Durga Tejaswi, A. Sai Divya Sree, B. Sai, R. Siva Santhi

No abstract is available for this record.

Mingyan Liu, Changli Zhang

Abstract Smart contracts hold billions of dollars worth of digital currencies, and hacking attacks can not only cause users to lose their assets but also destabilize the blockchain ecosystem.Vulnerability detection in smart contracts remains a major challenge in blockchain security. Existing methods typically rely on a fixed expert mode, which leads to low accuracy. Moreover, GNN-based models fail to effectively differentiate the significance of various interaction information, while transformer models suffer from high computational complexity. To solve this problem, we propose the GAT-Mamba framework, named GMVD, to perform the smart contract vulnerability detection task. The approach first extracts expert-defined vulnerability patterns from smart contract functions. Then, the graph features are extracted by GAT. Finally, Mamba is used to model the high-dimensional vector expression of expert mode features to improve the calculation efficiency of the model. Subsequently, graph features are extracted through GAT, and Mamba is then employed to model the high-dimensional vector representation of expert pattern features, thereby enhancing computational efficiency. Experimental results on three common vulnerabilities, reentrancy, timestamp dependency, and infinite loop, demonstrate that our framework significantly outperforms existing cutting-edge technologies. Specifically, our method achieves 94.29% accuracy in detecting reentrancy, 93.71% in timestamp dependency, and 82.49% in infinite loop detection.

Masoume Akraminasab, Mojtaba Mahdavi, Hamid Mala

: Public blockchains enable decentralized applications but continue to face persistent challenges in scalability, privacy, and decentralization. This survey employs a structured and comprehensive literature review of 114 peer-reviewed studies and reputable technical reports (2018–2025), selected using predefined search strings, inclusion/exclusion criteria, and a structured screening process, documented using a Literature selection flow diagram. Scalability techniques—including sharding, Layer 2 architectures (e.g., ZK-Rollups, Optimistic Rollups, commit chains), and privacy-enhancing technologies such as zero-knowledge proofs (ZKPs), trusted execution environments (TEEs), and protocol-native mixers—are critically analyzed. Standardized benchmarking evaluates throughput, latency, gas efficiency, and decentralization under consistent test conditions. A key contribution of this study is the first integrated, datadriven assessment of privacy–scalability trade-offs within the blockchain scalability trilemma framework. Empirical benchmarking indicates, for example, that zkSync Era demonstrates a theoretical throughput of ~2000 TPS but achieves ~0.52 TPS under measured network conditions, highlighting the computational overhead of ZKP generation. Hybrid architectures—such as zkPorter’s off-chain data availability combined with ZKPs or TEE-based routing— consistently outperform single-layer approaches in balancing performance, confidentiality, and trustlessness. Post-2021 advancements, including modular rollups, MEV-resistant sharding, and machine-learning-based load prediction, are reviewed alongside open challenges in standardized benchmarking, post-quantum privacy systems, and compliance-aware PETs. Future research directions emphasize cross-layer designs integrating ZKPs, dynamic sharding, and regulatory- ready privacy protocols to enable secure, scalable, and legally compliant blockchain ecosystems.

P. S. Adu

This study develops and evaluates a hybrid Compliance–AI cybersecurity model for unified protection of traditional banking and decentralized finance (DeFi) systems in Brazil. Using publicly available data from the NIST Cybersecurity Framework, DeFi exploit repositories (REKT and DeFiLlama), Elliptic crypto-transaction graphs, IEEE-CIS fraud data, DARPA Transparent Computing datasets, and Monte Carlo–simulated cross-domain attack scenarios, the research applies hierarchical clustering, supervised learning, Markov chain modeling, and stochastic simulation. Results show that 45% of banking controls are transferable or hybridizable to DeFi, that embedding machine-readable compliance features improves ROC–AUC from 0.842 to 0.914 and reduces false positives by nearly 47%, and that bidirectional orchestration lowers escalation probability by over 54%. Monte Carlo analysis further indicates a 62% reduction in tail financial risk under the hybrid architecture. The study recommends machine-readable regulation, compliance-aware AI deployment, orchestrated enforcement layers, and expanded RegTech and SupTech adoption to strengthen systemic financial cybersecurity. Keywords: Compliance–AI Integration, Financial Cybersecurity, Decentralized Finance, Machine-Readable Regulation, Systemic Cyber Risk.

Santhi K, Aditya Hiremath, S. Sanjay

No abstract is available for this record.

B. Siva Ganesh, Aditya Basantia, Soumya Sambit Mishra, Jagdish Behera · 5 authors

Healthcare systems are essential for patient care and data management but face persistent challenges with data security, interoperability, and transparency. Traditional centralized storage models increase data breach risks and limit patients’ control over personal health information, complicating seamless data sharing across providers. However, centralized storage systems still lack the security and interoperability required for robust data sharing. To address this, our study proposes a ZKP-based verification system integrated with NFT blockchain technology, aimed at enhancing identity verification while ensuring data privacy and patient control. In our method, NFTs serve as unique digital identifiers linked to patient records, while zero-knowledge proofs (ZKPs) confirm data ownership without disclosing sensitive information. Our findings indicate that this approach mitigates identity fraud risks, strengthens data security, and offers a patient-centered system for selective data access. Beyond patient records, our solution supports transparency in clinical trials and pharmaceutical supply chains, combating counterfeiting and improving quality control. In our paper, we proposed a ZKP-based verification system integrated with NFT blockchain technology to improve identity verification in healthcare, offering a robust, patient-centered approach to data security and integrity.

A Manoj Prabaharan

The proliferation of misinformation in real-time digital media demands innovative solutions for verifiable journalism. This paper introduces SolanaNet-Journal, a pioneering framework leveraging Solana's high-throughput blockchain and multi-agent AI networks to enable immutable, real-time news dissemination with embedded credibility assurance. Autonomous agents, specialized in sourcing, cross-verification, and provenance tracking, collaborate via Solana smart contracts to process breaking stories at over 2,000 verifications per second, achieving sub-second finality unattainable on legacy blockchains. Key innovations include a hybrid proof-of-history consensus fused with agent Byzantine agreement, cryptographic hashing for tamper-evident content streams, and a dynamic credibility scoring model that adapts to evolving narratives using stake-weighted incentives. Implemented on Solana devnet, the system demonstrates 92% accuracy in fact-checking live datasets from global events, outperforming centralized tools by 4x in latency and resilience to adversarial inputs. Evaluations across scalability, security, and real-world case studies affirm its robustness against deepfakes and viral falsehoods. By decentralizing trust, SolanaNet-Journal redefines journalistic integrity in hyper-dynamic media landscapes, paving the way for ethical, scalable AI-blockchain hybrids in inclusive communication ecosystems.

Akash Maurya, A. Verma, Gopal Kumar Mishra, Akansha Bhattara · 6 authors

Abstract The pharmaceutical supply chain faces critical challenges in maintaining drug integrity, ensuring regulatory compliance, and preventing medication waste. This research presents a comprehensive quantum-resilient monitoring system integrating federated machine learning, blockchain with Proof-of-Quality consensus, hyperspectral sensing, and zero-knowledge protocols. The Temporal Attention-Enhanced Federated Ensemble (TAFE) algorithm enables privacy-preserving collaborative learning achieving 94.3% detection sensitivity, identifying degradation 45 days before conventional methods. Edge architecture with ARM Cortex-M7 reduces cloud dependency by 87% with sub-500ms latency. Blockchain achieves 1,200 + TPS with 2.8s finality. Zero-knowledge proofs enable compliance verification in 1.6s without data disclosure. Field deployment across 25 locations validates 99.7% uptime with 87% user satisfaction.

Sujata Sathe, Sahebrao Shinde

Blockchain technology has evolved incredibly into various domains other than cryptocurrencies such as healthcare, genomics application, agriculture, government schemes, land asset distribution, DeFi, IoT, supply chain management due to its decentralized and secured nature. Consensus mechanism in blockchain networks serves as the backbone to ensure data integrity, provenance, immutability and security. Traditional consensus mechanism faces many challenges like utilization of high energy or carbon, excessive computational resources, staking of cryptocurrency, high reputation of nodes, maximum votes received, scalability and security issues. To tackle this concerns many researchers has proposed solutions and given a comparative analysis of the performance of these algorithms. This paper gives the survey reviews of the consensus mechanism used so far with a comparative analysis on the performance metrics like scalability, latency, and throughput, degree of decentralization, energy and resources efficiency etc. We have divided the consensus algorithms based on two categories i.e Proof based and Acquiescence based. The study highlights critical trade-offs among scalability, energy efficiency, decentralization, fault tolerance, and security resilience. Furthermore, this paper sheds the light on recent innovations addressing mitigation strategies like sharding, off-chain solutions, checkpoint mechanism, and integration of machine learning for anomaly detection, prediction of attack vectors. By systematically comparing consensus protocols and identifying open research challenges, this review aims to provide researchers and practitioners with a clear understanding of current consensus landscapes and provide valuable guidance to the selection and design of suitable mechanisms for next-generation blockchain systems.

Emre Akadal

This chapter explores the intersection of data governance, data quality, and blockchain technology, presenting a paradigm shift from traditional centralized data management to decentralized architectures. As data solidifies its role as a critical asset, ensuring its integrity and trustworthiness has become paramount. We begin by establishing the principles of data governance and quality, highlighting the limitations of conventional systems that rely on trusted intermediaries, which introduce single points of failure and censorship risks. Blockchain technology emerges as a compelling alternative, offering a decentralized, immutable, and transparent ledger that fundamentally enhances data integrity and trust. Through an analysis of its core components – including cryptographic hashing, consensus mechanisms, and distributed networks – we examine the inherent advantages and disadvantages of blockchain. The chapter delves into the functional extensions of blockchain, such as smart contracts and Decentralized Autonomous Organizations (DAOs), which enable automated, transparent, and autonomous governance models. However, the transition to blockchain is not without its challenges. We critically assess issues of scalability, data privacy, the “oracle problem,” and the “garbage in, garbage out” principle, which persist in decentralized environments. The chapter concludes that the “quality” of blockchain as a data management solution is not absolute but is contingent upon the specific requirements of the use case, demanding a careful evaluation of its trade-offs.

Mohammad Abu Kausar, Arockiasamy Soosaimanickam

In the emerging trends technologies, such as blockchain, security is one of the most critical aspects to be strongly addressed. In general, confidentiality, integrity, and availability (CIA) are the concepts that are considered to provide security. To handle the public blockchain, this is always an important challenge that needs special attention. For example, in distributed systems, when copying information over the whole network, confidentiality will be the main issue. In real time, the CIA triad faces considerably more problems in terms of integrity; even the integrity of information appears to be unaffected. In blockchain, read availability is considered much higher than write availability. This chapter delves into the combination of two technologies: Generative Adversarial Networks (GANs) and blockchain. With the increasing prevalence of blockchain applications, ensuring security is a main concern. This chapter explores methods of incorporating GANs into blockchain security by introducing an approach to protect distributed ledger systems. Utilizing GANs for detecting anomalies in modern threats and adopting security measures will strengthen blockchain networks against emerging cyberthreats. This chapter focuses on obstacles, emphasizing the impact of GANs on blockchain security and offering insights for researchers looking to enhance the resilience of decentralized systems in today&s;s cybersecurity environment.

Nicola Bicocchi, Enrico Rossini, Marco Picone, Marco Mamei

The IoT-Edge-Cloud Continuum (IECC) demands data architectures capable of handling heterogeneity, distributed ownership, and governance across diverse stakeholders. This paper examines the combined use of Data Mesh and Data Spaces as complementary paradigms for addressing these challenges. Data Mesh decentralizes data management and computation across domains through autonomous data products; Data Spaces provide the trust, semantics, and policy frameworks required for sovereign and interoperable data exchange across organizations. Within the Horizon Europe NOUS project, we integrate these paradigms to form a knowledge-centric computing continuum. Using the Modena Automotive Smart Area (MASA) as a real-world testbed, we show how this integration supports scalable, trusted, and semantically aligned intelligence for smart mobility applications.

Arockia Anto Deepak R, Abishai Daniel S, S. Lakshmi Sankar M.

The pharmaceutical industry faces critical challenges related to counterfeit drugs, poor traceability, and lack of transparency in supply chain management. To address these issues, this project proposes MedSupplyChain, a blockchain-based drug tracking and verification system that ensures secure, transparent, and tamper-proof management of pharmaceutical supply chains. The system leverages Ethereum smart contracts to automate key operations such as drug batch registration, transfer of ownership, and recall management with role-based access control for manufacturers, distributors, and regulators. Decentralized storage using IPFS is integrated to securely store certificates, testing reports, and product images, while only their hash values are recorded on the blockchain to maintain efficiency and scalability. The frontend DApp, built with React.js and connected via Web3.js/Ethers.js, provides user specific dashboards for stakeholders and enables real-time verification of drug authenticity. Patients, pharmacists, and regulators can easily track and verify drug batches using batch IDs, ensuring accountability and trust across the supply chain. This approach not only reduces the risks of counterfeit drugs but also improves regulatory compliance, operational transparency, and stakeholder collaboration. By combining blockchain's immutability with decentralized storage, MedSupplyChain establishes a secure, efficient, and trustworthy foundation for modernizing pharmaceutical logistics.

Chiara Braghin, Stelvio Cimato, Simone Pesci, Elvinia Riccobene

• A novel Framework for Secure and Efficient Healthcare Data Management • A Blockchain-Based Identity Management and Access Control • Data Integrity Verification with Merkle Trees • Scalable and Compliant Data Storage • Secure Data Sharing via Proxy Re-Encryption The healthcare sector increasingly relies on digital infrastructures to manage large volumes of sensitive medical data. Ensuring integrity, controlled access, interoperability, and auditability remains a fundamental challenge. We propose BlockHealth, a hybrid blockchain-based framework that integrates smart contracts, distributed databases, and proxy re-encryption to support secure and verifiable healthcare data management. The system leverages Ethereum and NFT-based identities for access control, Merkle-tree commitment for tamper-evident integrity verification, and a distributed Cassandra storage layer for scalable and regulation-compliant off-chain data management. Proxy re-encryption enables secure delegation of access without exposing private keys, while a coordinating API service ensures interoperability with existing hospital infrastructures. Our evaluation demonstrates the feasibility and efficiency of core operations — including hashing, on-chain commits, and re-encryption — indicating that the proposed framework can provide a practical balance among verifiability, performance, and deployability in realistic healthcare environments.

Johannes Sederl

Nach dem anfänglichen Hype um die Blockchain-Technologie, die erstmals durch Satoshi Nakamotos Bitcoin bekannt wurde, hat sich der Bereich in Richtung der Entwicklung ausgereifter Blockchain-basierter Systeme und Anwendungen weiterentwickelt. In dieser weitläufigen Landschaft fungieren die einzelnen Blockchain-Plattformen und Ökosysteme häufig als isolierte Silos, die strikt von anderen Plattformen getrennt sind und über keine inhärenten Interoperabilitätsfunktionen verfügen. Trotz der Existenz etablierter Mechanismen für den Austausch von Coins und Tokens über heterogene Blockchains hinweg müssen Entwickler von Web3-Anwendungen, die aus Smart Contracts bestehen, möglicherweise auf individuelle Anpassungen zurückgreifen, um Blockchain-übergreifende Anwendungen zu ermöglichen. In vielen Fällen sind diese Ansätze nicht ausreichend skalierbar, wenn die Anwendung auf zusätzlichen Blockchain-Plattformen verteilt werden muss. Folglich sind weitere Anpassungen erforderlich. Darüber hinaus stellt sich die Frage der Speicherung gemeinsamer Anwendungsdaten, die mit Smart Contracts kompatibel und für das dezentrale Konzept der Blockchain geeignet sein muss. Diese Arbeit präsentiert einen Vorschlag für eine Blockchain-übergreifende Datenspeicherlösung, die das InterPlanetary File System (IPFS) als dezentrale Off-Chain-Persistenzschicht und Blockchain-Oracles nutzt, um Lese- und Schreibvorgänge zu ermöglichen. Der Einsatz von incentivierten Vermittlern in Verbindung mit einem neuartigen Oracle-Verifizierungsmechanismus für Schreibzugriffe erlaubt die Formulierung eines Lösungsentwurfs für ein vollständig dezentrales System. Dieser Ansatz ermöglicht die lose gekoppelte Verbindung von Blockchain-übergreifenden Anwendungen, wobei die einzelnen Blockchain-Plattformen nicht direkt aufeinander zugreifen müssen. Wir präsentieren eine prototypische Implementierung des Lösungsentwurfs und bewerten anschließend den Prototyp hinsichtlich Kosten, Leistung und Sicherheit. Im Vergleich zu einer hypothetischen Referenzlösung, die eine zentralisierte Persistenzschicht verwendet, zeigen wir, dass vollständige Dezentralisierung die Betriebskosten und die Leistung sowie die Integrität der gemeinsam genutzten Daten erheblich negativ beeinträchtigt.

Authors unavailable

No abstract is available for this record.

Mauricio Carvalho

In March 2025, the United States established a Strategic Bitcoin Reserve by executive order. Bhutan had been quietly mining Bitcoin with hydroelectric power, accumulating over $1 billion without public announcement. By February 2026, more than 145 publicly traded companies held Bitcoin on their balance sheets, collectively exceeding one million BTC. No established academic framework predicted these developments. In his 2023 MIT thesis Softwar, Major Jason Lowery proposed that Bitcoin is best understood not as money or a hedge but as a power projection technology rooted in thermodynamic proof of work. This paper presents the first empirical evaluation of that framework. Nine falsifiable predictions are tested against observed data; five have been confirmed and one partially realized within three years of publication. The developments that monetary, financial, environmental, and security models fail to explain (strategic reserves, geopolitical competition for hash rate, sovereign mining operations) are precisely those the power projection framework predicts.

Shalini, Abhay Bhatia, Dr. Parag Jain, Dr. Lokesh Kumar

Exceptional connectivity across global networks has been driven by the expansion of Internet of Things devices, while significant weaknesses in security, scalability, and data management have emerged. Distributed ledger technology offers creative solutions to these fundamental limitations. This article reviews the blending of Blockchain technology with IoT, analyzing its potential, challenges and current advances. The article also highlights various applications and future research directions. This review aims to provide a comprehensive understanding by synthesizing existing knowledge, identifying research gaps, and establishing the context for future studies of blockchain-IoT integration, emphasizing critical design considerations and practical implementations.

Monica Singhania, Surabhi Seth, Chanchal Saini

No abstract is available for this record.

Bolun Yang, Jiamin Hao, Yao Ma, Li Zhou

The integration of distributed data storage, P2P networks, consensus mechanisms, cryptography and other technologies, the application of blockchain technology has expanded from the initial financial field to many other areas, such as logistics and auditing. The consensus mechanism is the soul of blockchain technology, and it is of great significance to conduct a rigorous mathematical analysis. As far as we know, the Proof of Stake (PoS) consensus mechanism is only a qualitative description of the rich and the poor, the rich are richer, the poor are poorer, and there is no quantitative mathematical analysis. This paper presents a novel quantitative framework to quantitatively analyze the PoS consensus mechanism. Under the premise of not carrying out the attack, we use the expected reward and the reward ratio as the evaluation indicators, quantitatively analyze the optimal fund allocation strategy of the two parties game under the PoS consensus mechanism from the perspective of rich miners, and construct the reward function as the objective function. The inequality constrains the optimization problem and solves it using the Karush-Kuhn-Tucker condition. We consider the two schemes of assignment strategy and random strategy, and get the optimal fund allocation strategy. At the same time, it is compared with the general strategy to obtain the optimization effect of the optimal strategy. After that, we compare the situation in which both sides of the game use the optimal strategy. We found that for assignment strategy, the mining activity will not indicate that the rich are richer and the poor are poorer. However, for the random strategy, this will not happen. The random strategy is also the most common strategy in practice. We also use Markov decision process (MDP) to give the optimal strategy calculation method under the rational miner game, which is also applicable to the n-parties game. The work of this paper helps the blockchain developers to analyze the PoS consensus mechanism, and the adoption strategy of the assignment strategy and the random strategy can be used as the future research direction.

S Santhiya, S MadhanKumar, K Poongodi

Although cloud storage offers the much-needed scalability, flexibility, and economic efficacy, it also presents significant security and privacy issues, which are mostly caused by the fact that, since data are encrypted, the traditional plaintext search approaches are compromised. To overcome this shortcoming, we introduce the Enhanced Aware Record Maintenance (EARM) architecture, a compound, privacy-aware architecture that supports ranked, multi-keyword encrypted data retrieval in the cloud. The fundamental retrieval process of EARM is novel, incorporating ontology-based keyword mapping, enhanced association rule mining, and inner-product similarities to produce highly accurate and relevant search results. The framework deploys a strong multi-layer defense model, which integrates quantum-resistant cryptography (Zero-Knowledge Proofs/Homomorphic Encryption), high-grade cipher suites (AES/RSA), and granular Attribute-Based Encryption (ABE) access controls (such as geofencing and decentralized identity management). Moreover, EARM also brings intelligent defensive layers of AI-based orchestration, which include ransomware, intrusion, and anomaly detection, behavioral biometrics, and a tamper-proof blockchain audit trail. Secure file versioning, rollback, and an encrypted trash bin are other ancillary features that improve the system's resilience. Empirical analyses performed on actual data sets indicate that EARM maintains high privacy and high retrieval rates and suffers only a few system overheads, hence making it an effective and highly secure encrypted cloud storage solution for modern challenges.

Tajreean Ahmed, Rupam Ghosh, Ahmed Faizul Haque Dhrubo, Khushnur Binte Jahangir · 5 authors

This paper presents a novel architecture for developing Decentralized Applications (DApps) on Blockchain that integrate Artificial Intelligence (AI) and decentralized storage for the age of Web3 applications. As these emerging technologies continue to evolve, the synergy among them offers not only unprecedented opportunities for innovation and advancement but also raises confusions, incompatibilities and unreliability. The proposed architecture aims to harness the strengths of Blockchain's distributed computation and ledger technology for transparency and security, AI's capabilities for fraud detection and penalization, and Social Media's network effects for user engagement and decentralized storage's reliability for trust. Through the integration of these technologies, DApps can offer enhanced privacy, autonomy, and trust while fostering inclusive and participatory ecosystems. The paper discusses the design principles, components, and potential use cases of such a hybrid architecture, highlighting its potential to revolutionize various domains, including content creation, social networking, land registration, and property market. To verify and validate the architecture, we have developed two DApps- one for social media and another for land registration and property market. Our developed DApps provided upto 100 fold gains in speed, 10 folds gains in cost, more reliably and automation than existing similar centralized applications.

Taiske

In the Web3 ecosystem, "dead assets" such as micro-token fractions (dust) and abandoned low-value NFTs continue to accumulate on networks, losing liquidity due to transaction fee constraints. This paper proposes the concept of the "Scavenger Protocol," which leverages the object-oriented architecture and parallel processing capabilities of the Sui blockchain to automatically detect, melt down, and recirculate these dormant assets back into the market as reusable resources (Scrap tokens). By implementing a smart contract-based mechanism where "abandoned value is automatically shuffled" without the need for central administrators, we aim to achieve the autonomous revitalization of the on-chain economy. Charitable Pledge: In the event that the implementation of this protocol generates any personal revenue or financial returns for the author, 60% of those proceeds will be donated to charitable causes. This commitment aligns with the Web3 ethos of supporting public goods and giving back to society. Disclaimer: This paper is for informational, academic, and conceptual purposes only and does not constitute financial, investment, legal, or regulatory advice. The "Scavenger Protocol" presented herein is a theoretical framework and thought experiment. The authors do not guarantee the realization of this protocol, its technical feasibility, or any financial returns. Any future implementation of this protocol by third parties must be executed strictly in compliance with applicable local and international laws. The authors assume no liability or responsibility for any damages, legal disputes, or financial losses arising from the use, interpretation, or implementation of the concepts described in this document. Open Design and Protocol Revenue Model (Tokenomics) This protocol is designed as a universal foundational primitive, unconstrained by specific applications or use cases. Other developers and projects are encouraged to freely fork, adapt, and build upon this mechanism to construct systems with their own customized rules. To ensure the system's long-term sustainability, we define a minimal baseline rule: the system automatically collects a flat 1% protocol fee during operations—specifically at the time of melting down dormant assets and generating new ones. The revenue generated from this 1% fee is directly applied to the "Charitable Pledge" outlined above. This creates the financial engine where 60% of the proceeds are directed toward social givebacks and donations, while the remaining 40% is allocated to protocol maintenance and the founder.