As the core component of blockchain applications, smart contracts are increasingly scrutinized for their security. Among various vulnerabilities, infinite loop flaws pose significant threats due to their hidden nature and potential for exhausting system resources. This paper proposes a static detection method based on Graph Convolutional Networks (GCNs), which transforms smart contracts into control flow and data flow graphs. Through graph-based modeling and vectorized encoding, semantic features such as loop structures and function dependencies are effectively captured. An improved GCN architecture is employed to identify potential infinite execution patterns through neighborhood aggregation and graph-level representation learning. Experimental results demonstrate that the proposed method achieves high accuracy and F1-score across real-world contract datasets, offering an effective and scalable solution for smart contract vulnerability analysis.
ABSTRACT Cryptocurrency taxation poses a fundamental dilemma: how to ensure compliance while protecting privacy and enabling realâtime crossâborder coordination. This paper introduces a blockchainâdriven framework to address these challenges. First, a permissioned consortium chain with a multiâchannel architecture links OECD tax authorities, compliant exchanges and international organizations, safeguarding data sovereignty. Second, a dynamic accountâtransaction graph with ruleâguided subgraph templates detects hidden âtaxâbase dark matterâ behaviours, including mixing services, crossâchain transfers and NFT profit masking. Third, a zeroâknowledge proof protocol (zeroâknowledgeâTaxProof) encodes tax rules into verifiable arithmetic circuits, allowing taxpayers to prove taxable conditions without exposing details. Fourth, a dynamicâweight PBFT mechanism ties node voting power to data integrity, accuracy and responsiveness, enabling multinational collaboration. Fifth, offâchain identity anchoring with onâchain KYC decoupling preserves privacy while permitting traceability strictly under judicial authorization. Finally, a realâtime dashboard and adaptive earlyâwarning system monitors global taxâbase changes with subâminute responsiveness. Experiments on a Hyperledger Fabric testbed show the model achieves 87.8% identification accuracy, an average darkâmatter capture rate of 88.9%, leakage entropy of 2.3 bits and event confirmation within 53 s. These results demonstrate a feasible, sustainable paradigm for reconstructing global digital tax governance that balances privacy, compliance and efficiency.
Integrating blockchain with IoT ensures secure, transparent data exchange through immutability and consensus mechanisms, preventing data tampering. However, the increasing number of IoT devices raises risks like unauthorized access and network attacks. Blockchain scalability issues also affect throughput and latency, challenging real-time IoT applications. This thesis addresses these challenges through four contributions that aim to improve the security, scalability, and efficiency of blockchainbased IoT networks, balancing security with performance needs. Our first contribution is to develop an end-to-end security mechanism for IoT networks, called the trust-based ABAC mechanism for IoT networks (TABI). TABI integrates edge computing and blockchain technology to mitigate risks from malicious devices and offload computational tasks to edge layers. It operates on Hyperledger Fabric (HLF), a permissioned blockchain that enhances throughput and latency through its executeorder- validate architecture. Our second objective is to provide scalability within blockchain-based IoT networks using a sidechain-based trust and access control system, named sidechain-based trust and access control mechanism for IoT networks (SATI). By distributing trust evaluation and access control operations across a separate blockchain or sidechain, SATI improves the scalability of IoT networks. We implement a cross-chain transfer mechanism to ensure communication between the sidechain and the mainchain, thus overcoming a fundamental limitation of traditional blockchain architectures. Our third contribution is to improve the security of the IoT network by introducing a Zero-Knowledge Proof-based Mutual Authentication (ZPMA) mechanism, a privacy-preserving mutual authentication mechanism. Utilizing Zero-Knowledge Proofs (ZKP) based on the quadratic residue technique, Z-PMA ensures secure and private mutual authentication between edge devices and IoT devices. We also implement an incentive mechanism to select additional authenticators from the base station layer to reduce authentication latency and support the demands of low-latency IoT networks. Our fourth contribution is to detect and resolve conflicting transactions in HLF-based IoT networks at an early stage, known as the early-stage conflict transaction resolution (ECR) mechanism. ECR identifies and resolves conflicting transactions at an early stage using a local cache at the endorsement phase of the HLF transaction processing. Additionally, ECR uses dependency model and an efficient reordering process to distribute transactions in a way that minimizes conflicts. This mechanism enhances the performance of HLF-based IoT networks by reducing the impact of conflicting transactions, ultimately improving throughput and latency.
Information Communication Technologies, Deniz Salucu, Tunga Sayıcı, Information Communication Technologies
The rapid rise of adoption of digital identity presents a transformative opportunity to eliminate resource-intensive physical identity systems, no longer requiring printed cards, plastic credentials, or in-person office visits, thereby substantially reducing carbon footprints. This paper introduces a comprehensive Self-Sovereign Identity (SSI) model built upon Hyperledger Indy, enabling end users to securely store and manage their identities directly on personal devices. We explore two different enrollment methods: QR code-based digital credential issuance and NFC-powered chip-based identity verification, further enhanced through zero-knowledge proofs and verifiable credential protocols. The ecological advantages are emphasized through the eradication of physical identity artifacts and associated administrative processes, advancing the field of green digital technologies in support of ecological preservation and sustainable identity infrastructures.
Luigi Pavarini de Lima, Liliam Sayuri Sakamoto, Jair Minoro Abe, Jonatas Santos De Souza · 8 authors
The objective of this article is to propose a research structure to optimize this security of assets with NFT - Non- fungible Token with the use of DLP - Data Loss Prevention and Paraconsistent Logic for the identification not only preventively, but actively of the loss, theft, misuse and leakage of this type of assets during their use in the Metaverse. A bibliographic review was carried out on Metaverse, DLP, Paraconsistent Logic, Artificial Intelligence techniques [10][27][28], NFT [49][50], and Data Protection [4] with a focus on the LGPD (Brazilian Data Protection Law) [2][23], in conjunction with exploratory research. With a DLP and a database provided by the transport company with 200 articles analyzed. It was verified that a significant amount of data would be discarded in the first stage of the process (37%) since they do not present an active definition on the status of these assets. Considering the growing technological innovation with the use of the Metaverse, as an environment for educational, business and governmental interaction against the risk of cyber-attacks, there is an urgent need to strengthen its security, even more so when in this environment, where there is the possibility of moving assets with NFTs that are objects of great value acquired and traded in this medium. With the use of the Python program in the DLP, it was observed that it presented a 37% data loss in its analysis with this Artificial Intelligence [11] process only with the performance of the DLP, compared to the optimization of this analysis with the use of Paraconsistent Logic at 23%, that is, a use of more than 15% of the data.
This article introduces a hybrid blockchain architecture to enhance Electronic Medical Record (EMR) management and interoperability. It integrates a permissioned public blockchain on Polkadotâmanaging roles and permissionsâwith a private blockchain on Hyperledger Fabric responsible for EMR storage. Text data are stored in CouchDB and medical images in IPFS as Non-Fungible Tokens (NFTs), following a patient-centric model. Stress tests yielded average latencies of 2050 ms for EMR creation and 2000 ms for sharing, with 65 % CPU and 170 MB memory usage, indicating system stability and efficiency. The proposed architecture provides a scalable, secure, and interoperable solution suitable for healthcare environments that demand data confidentiality and controlled access.
Edge Artificial Intelligence (Edge AI) represents a transformative shift in the way data is processed, analyzed, and acted upon. By combining the capabilities of artificial intelligence with the decentralized architecture of edge computing, Edge AI enables faster decision-making, enhanced data privacy, and improved operational efficiency. This manuscript explores the essential aspects of Edge AI, including its real-time responsiveness, cost efficiency, and sustainability benefits. It also highlights the wide range of industrial applications â from healthcare and manufacturing to autonomous systems â while addressing key challenges such as limited device computing power and integration complexities. As organizations increasingly adopt Edge AI solutions, the technology is paving the way toward a hybrid future where edge and cloud systems coexist, driving innovation, scalability, and intelligence across every connected ecosystem.
Ozan Solmaz, Lioba Heimbach, Yann Vonlanthen, Roger Wattenhofer
Layer 2 rollups are rapidly absorbing DeFi activity, securing over $40 billion and accounting for nearly half of Ethereum's DEX volume by Q1 2025, yet their MEV dynamics remain understudied. We address this gap by defining and quantifying optimistic MEV, a form of speculative, on-chain MEV whose detection and execution logic reside largely on-chain in smart contracts. As a result of their speculative nature and lack of off-chain opportunity verification, optimistic MEV transactions frequently decide not to execute any trades. In this work, we focus on cyclic arbitrage, which we find is predominantly executed as optimistic MEV on Layer 2s. Using our multi-stage identification pipeline on Arbitrum, Base, and Optimism, we show that in Q1 2025, transactions from cyclic arbitrage contracts account for over 50% of on-chain gas on Base and Optimism and 7% on Arbitrum, driven mainly by "interaction" probes (on-chain computations searching for arbitrage). This speculative probing indicates that cyclic arbitrage on Layer 2s is predominantly executed as optimistic MEV and contributes to generally keeping blocks on Base and Optimism persistently full. Despite consuming over half of on-chain gas, these optimistic MEV transactions pay less than one quarter of total gas fees. Cross-network comparison reveals divergent success rates, differing patterns of code reuse, and sensitivity to varying sequencer ordering and block production times. Finally, OLS regressions link optimistic MEV trade count to ETH volatility, retail trading activity, and DEX aggregator usage. Together, these findings show that optimistic MEV has become a major source of persistent spam-like transaction activity on Layer 2s, dominating blockspace with low-value probes and reshaping the composition of on-chain activity.
La blockchain rappresenta una delle piuÌ rilevanti innovazioni tecnologiche degli ultimi decenni, capace di ridefinire il modo in cui la fiducia viene costruita e mantenuta nei sistemi digitali. Il presente contributo intende analizzare le radici tecnologiche di tale paradigma, concentrandosi su due concetti fondativi: lâimmutabilitaÌ dei dati e il meccanismo di consenso. LâimmutabilitaÌ deriva dalla struttura crittografica della catena di blocchi, in cui le funzioni di hash collegano ogni elemento al precedente rendendo impraticabile la modifica retroattiva delle informazioni senza invalidare lâintera sequenza. Il consenso, invece, consente ai nodi della rete distribuita di concordare sulla validitaÌ delle transazioni senza ricorrere a unâautoritaÌ centrale, sostituendo la fiducia istituzionale con una validazione matematica. I principali protocolli di consenso â Proof of Work e Proof of Stake â incarnano due differenti logiche di sicurezza, rispettivamente basate sul costo computazionale e sulla partecipazione economica, ma condividono lâobiettivo di garantire la coerenza del registro distribuito. Lâanalisi mostra come lâaffidabilitaÌ della blockchain emerga dallâinterazione tra queste componenti, configurandosi come una forma di «disintermediazione tecnica» che produce fiducia attraverso il calcolo. Tuttavia, le stesse caratteristiche che assicurano integritaÌ e trasparenza pongono questioni aperte in termini di scalabilitaÌ, interoperabilitaÌ, governance e sicurezza di fronte al calcolo quantistico. Comprendere lâequilibrio tra immutabilitaÌ e consenso significa, dunque, cogliere la natura dinamica di una tecnologia che coniuga matematica e cooperazione distribuita per creare un nuovo modello di infrastruttura affidabile, capace di dialogare con i principi giuridici e istituzionali della societaÌ digitale.
Shahbaz Siddiqui, Sufian Hameed, Muhammad Rafi, Syed Attique Shah · 5 authors
The development of blockchain consensus mechanisms has put sustainability, scalability, and efficiency first in the list of cryptocurrency studies. As Bitcoin still uses the energy-intensive Proof-of-Work (PoW) algorithm, Ethereum is in the process of switching from PoW to Proof-of-Stake (PoS) with the Ethereum Merge in September 2022. The cause of this change was the rising energy prices, bottlenecks in scalability, and increased concerns among the global population regarding the environmental effects of PoW-based mining. Our study provides a rationale for the Ethereum transition by comparing and contrasting the volume of transactions, network performance through hash rate, and electricity consumption of Bitcoin and Ethereum in their PoW stages.With the help of both historical trend and predictive modelling in the form of the ARIMA framework, the obtained results showed that Bitcoin and Ethereum had different dynamics of growth under PoW, which was increased hash and energy expenditures but limited throughput. The ARIMA-based analysis achieved a mean absolute error (MAE) of 27.76, a root mean square error (RMSE) of 31.16, and a mean absolute percentage error (MAPE) of 26.08, which provided an overall forecast accuracy of 73.9%. These measures show that there is a medium predictive reliability, and volatility is mainly caused by sudden changes in mining intensity and market forces. The predictions further indicated that under PoW, Ethereum would have experienced a steep rise in operational energy consumption and congestion of its network transactions, which would have weakened network sustainability.Results thus confirm that the switch of Ethereum to PoS was not only an environmental need but also a strategic optimization of a transaction to scale higher, operational overhead reduction, and alignment with sustainable and ESG (Environmental, Social, and Governance) goals on a global scale. This piece leads to a better comprehension of the trade-offs between PoW and PoS, as well as the Ethereum consensus shift as the turning point in the evolution of blockchainsâestablishing a precedent of other cryptocurrencies that can select a balance between performance, security, and sustainability.
Abstract: Blockchain technology is a transformative distributed ledger paradigm that enables secure, transparent, and tamper-resistant data management without centralized authorities. At its core lies the consensus mechanism-the protocol through which distributed nodes agree on a single canonical transaction history. This paper presents a structured review of major blockchain consensus schemes including Proof-of-Work (PoW), Proof-of-Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT), as well as emerging hybrid models such as Avalanche and Polkadot. The analysis evaluates sustainability, scalability, security, and decentralization characteristics, offering a comprehensive comparison across these mechanisms. The findings highlight inherent trade-offs related to energy consumption, throughput, finality, validator governance, and fault tolerance. The study concludes by identifying open research challenges important for designing next-generation blockchain systems capable of supporting large-scale, mission-critical applications. Keywords: Avalanche, Blockchain, Consensus Mechanisms, PBFT, PoS, PoW, Scalability, Security, Sustainability. Title: Study and Comparative Analysis of Blockchain Consensus Mechanisms Author: Dr. N. R. Ananthanarayanan, Mr. Suresh Subbu International Journal of Recent Research in Mathematics Computer Science and Information Technology ISSN 2350-1022 Vol. 12, Issue 2, October 2025 - March 2026 Page No: 1-15 Paper Publications Website: www.paperpublications.org Published Date: 25-November-2025 DOI: https://doi.org/10.5281/zenodo.17711245 Paper Download Link (Source) https://www.paperpublications.org/upload/book/Study%20and%20Comparative%20Analysis%20of%20Blockchain-25112025-2.pdf
The public ledger characteristic of blockchain grants data immutability but simultaneously introduces privacy leakage risks, making association analysis between on-chain behaviors and real-world identities possible. Existing privacy protection schemes struggle to balance the anonymity of the querier with the traceability of malicious behaviors. On one hand, legitimate inquiry behaviors are easily reverse-tracked by third parties through on-chain records (i.e., "human flesh search" targeting the querier); on the other hand, a completely anonymous environment may lead to data abuse without the possibility of accountability.To address this issue, this paper proposes an anti-"human flesh search" privacy protection system based on blockchain and zero-knowledge proofs. Addressing the aforementioned contradictions, this paper presents a blockchain data sharing scheme that balances privacy and regulation. The scheme utilizes IPFS to implement graded encrypted storage for large files. The core innovation lies in combining the Schnorr protocol and Chameleon Hash to construct a Blockchain Designated Verifier Proof (BDVP). While verifying user query permissions through blockchain smart contracts, the system utilizes the trapdoor property of the Chameleon Hash to achieve the non-transferability of proofs, preventing third parties from reverse-tracking the querier's identity by analyzing on-chain records<sup>[<xref ref-type="bibr" rid="R2">2</xref>]</sup>. Furthermore, the system introduces a threshold private key held by regulatory agencies to ensure that, in the event of data abuse, malicious users can be de-anonymized and held accountable according to the law.
Ram Kumar Solanki, Ganesh R. Pathak, Amit Gadekar, Abhishek Dhore · 6 authors
The spread of Distributed Ledger Technology (DLT) beyond its roots in cryptocurrency has led to a proliferation of blockchain frameworks with differing architectural philosophies, performance attributes, and applications in mind. This non-uniformity poses a significant problem for enterprises and developers who aim to find the best platform that suits them. The paper is based on a rigorous, multi-dimensional comparison of the four most crucial blockchain frameworks that encompass the breadth of the current DLT: Ethereum as an early smart contracts and decentralized application pioneer, Hyperledger Fabric for permissioned blocks designed to work in enterprise consortia, R3 Corda as a privacy-oriented ledger that is suitable to regulated industries, and Solana as a high-performance public blockchain that was developed to support web-scale applications. The paper breaks down the major architectural building blocks of each framework, including their permissioning models, data models, consensus models, and execution environments for smart contracts. Next, it compares their scalability and performance by combining the findings of notable benchmark experiments with relevant performance metrics (throughput and latency). Moreover, the paper investigates practical adoption by examining notable examples in financial services, supply chain management, and the fundamental growth of the Web3 economy. The most valuable output of this study is a synthesized framework selection matrix, which aligns platform abilities with the particular business and technical requirements as an evidence-based (observed in the field) guide that practitioners can use; at the same time, it will serve as a well-structured point of departure in future academic studies and research on the topic of distributed systems.
Ahmad Musamih, Khaled Salah, Raja Jayaraman, Samer Ellahham · 6 authors
Non-fungible tokens (NFTs) are unique digital assets stored on blockchains. NFTs are ideally suited for tokenizing genomic data, as they empower individuals with complete control over them. Next-generation sequencing (NGS) technology creates repositories of sequenced data from individualsâ raw genomic data, which raises challenges related to data ownership, management, and secure sharing. In this paper, we propose a blockchain and NFT-based solution that addresses the challenges of managing, sharing, and monetizing genomic data while preserving privacy using Threshold Cryptography and Fully Homomorphic Encryption (FHE). We integrate the proposed solution with the Interplanetary File System (IPFS), a decentralized storage system, to handle the substantial amount of genomic data off-chain. We develop three smart contracts to facilitate genomic data management, sharing, and monetization. We introduce composable NFTs to ensure that sequenced genomic data (SGD) NFTs are always linked to the parent raw genomic data (RGD) NFTs to maintain traceability. We present various diagrams and algorithms to illustrate the functionality of our solution. Our testing and validation results demonstrate that smart contracts function as intended. The cost evaluation shows that implementing the solution on a private blockchain is more feasible and user-friendly. Our solution provides a comprehensive framework for genomic data management, sharing, and monetization, with privacy-preserving mechanisms and traceability. We provide guidelines for the generalizability of our solution beyond genomics and outline the challenges and limitations of the proposed solution. We make the source code of the smart contracts publicly available on GitHub.
Blockchain has received a lot of attention for multiple use cases and applications since the first works emerged about 15 years ago, with its use targeting cryptocurrencies. During this period, a wide variety of platforms (e.g. Ethereum, Hyperledger, and others web3 Blockchain platforms), tools, programming languages and other resources such as smart contracts were proposed. With the aim of better understanding the use of smart contracts in Blockchain-based systems, this article presents a systematic review of the literature on Blockchain application architectures that make use of smart contracts, applied in different areas. It is expected to bring together approaches for the design and implementation of smart contracts on the Blockchain.
Michael Wijaya, Franscelino Melvyn, Reina Setiawan, Reinert Yosua Rumagit
Blockchain technology has emerged as a breakthrough in decentralized systems. The development of applications, systems, programs, and financial solutions can now be managed in a decentralized manner, revolutionizing the previously centralized paradigm. In this new system, performance, scalability, transaction costs, and network security present both challenges and compelling topics for research. This paper conducts a comparative analysis through experiments and evaluations of Ethereum and Solana, the two largest Layer 1 blockchain networks today. The comparison focuses on performance, consensus mechanisms, security, and ecosystem development. Performance is assessed through Transactions Per Second (TPS) and latency, while gas fees are compared under different network conditions. The study also analyzes Ethereumâs Proof-of-Stake (PoS) versus Solanaâs Proof-of-History (PoH) + PoS consensus mechanisms. Network security is examined by reviewing historical vulnerabilities and corresponding responses. The DApp (Decentralized Application) ecosystem is evaluated based on Adoption Efficiency Index (AEI) and sector specialization (DeFi, NFT, gaming). Through this analysis, the paper aims to provide a deeper understanding of the differences, strengths, and weaknesses of both networks, helping developers choose the most suitable blockchain platform.
Saad Mutlaq Alluhaydan, Mohammed Obaid Alshammari, Yousef Jazaa Obaid Alshmilan, Ahmed Hamoud Alshammari · 12 authors
Background: The rise of AI health assistants and digital tools raises concerns about data security and consent management. Traditional systems are prone to failures and provide limited transparency in data sharing. Blockchain technology offers a decentralized, immutable, and secure solution to these issues. Aim: This narrative review critically examines the real-world implementations and security trade-offs of blockchain technology when applied specifically to health assistant audit trails and consent management, moving beyond theoretical propositions. Methods: A systematic search of peer-reviewed literature (2010-2024) was conducted across Scopus, IEEE Xplore, PubMed, and ACM Digital Library. Implementation case studies, prototypes, and theoretical frameworks were analyzed to assess technical architectures, performance metrics, and security evaluations. Results: Findings indicate an emerging landscape where blockchain proves useful for creating secure audit logs in AI decision-making and dynamic consent models using smart contracts. However, challenges persist, including performance and scalability issues, key management complexities, data linkage risks, and conflicts between immutability and regulatory requirements such as the GDPR's "right to be forgotten." Conclusion: Blockchain serves as a foundational layer to improve security and transparency in health assistant ecosystems. Its future potential relies on hybrid architectures, advanced cryptographic methods such as zero-knowledge proofs, and an awareness of the new security and operational challenges that arise. It is not merely a database but a comprehensive solution for integrity and control.
This article presents a blockchain reconciliation framework that improves transparency, automation, and trust within the SAP supply chain and finance processes. The implemented system with smart contracts on SAP modules FI, MM, and SD permits real-time verification of supply chain activities and financial transactions, thus minimizing manual matching and third-party verification processes. The framework enables automated three-way matching and updates across modules by storing transaction states in a distributed ledger that captures changes. Based on experiments conducted using SAP simulation data, the accuracy of reconciliations increased by 92%, processing time was cut by 41%, and manual processing steps were reduced by 67%. The results demonstrate the capability of blockchain technology to solve pervasive challenges related data integrity and reconciliation within enterprise ERP systems.
This chapter explores the critical intersection of consensus mechanisms and performance metrics in blockchain systems for the Internet of Things (IoT). As IoT networks expand, the demand for scalable, efficient, and secure blockchain solutions intensifies. This chapter evaluates the trade-offs between energy efficiency, latency, scalability, and security within IoT-integrated blockchain frameworks. Key consensus protocols such as PoW, Proof of Stake (PoS), and Delegated DPoS) are analyzed for their applicability in IoT environments, highlighting their impact on transaction speed, resource utilization, and network resilience. Hybrid consensus models are examined for their potential to balance performance with robust security. The chapter also provides real-world case studies that benchmark latency and energy efficiency, offering insights into the practical challenges and opportunities for IoT-based blockchain applications. Key findings contribute to the ongoing development of optimized blockchain solutions for IoT networks.
5G networks provide secure and reliable information transmission services for the Internet of Everything, thus paving the way for 6G networks, which is anticipated to be an AI-based network, supporting unprecedented intelligence across applications. Abundant computing resources will establish the 6G Computing Power Network (CPN) to facilitate ubiquitous intelligent services. In this article, we propose BECS, a computing sharing mechanism based on evolutionary algorithm and blockchain, designed to balance task offloading among user devices, edge devices, and cloud resources within 6G CPN, thereby enhancing the computing resource utilization. We model computing sharing as a multi-objective optimization problem, aiming to improve resource utilization while balancing other issues. To tackle this NP-hard problem, we devise a kernel distance-based dominance relation and incorporated it into the Non-dominated Sorting Genetic Algorithm III, significantly enhancing the diversity of the evolutionary population. In addition, we propose a pseudonym scheme based on zero-knowledge proof to protect the privacy of users participating in computing sharing. Finally, the security analysis and simulation results demonstrate that BECS can fully and effectively utilize all computing resources in 6G CPN, significantly improving the computing resource utilization while protecting user privacy.