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52,502 results · page 266 of 2,188
Muhammad Ashraf Nazir, Nazim Hussain, Khalid Hamid, Muhammad Danish Rasheed, Muaaz Akhter, Muhammad Ibrar, Muhammad Aaqib Javed, Fareeha Zafar
No abstract is available for this record.
Nunes, Rodrigo, Melo, André, Albarello, Rafael, Gomes, Reinaldo · 6 authors
The integration of Uncrewed Aerial Vehicles (UAVs) into low-altitude airspace has led authorities to adopt distributed Uncrewed Traffic Management (UTM) architectures that ensure interoperability and safety. Blockchain has been proposed as an enabler for trustworthy coordination among UTM stakeholders. Yet, its real-time performance under aeronautical constraints remains insufficiently characterized. This paper presentes a quantitative benchmark comparing two regulation compliant distributed architectures: the federated InterUSS platform maintained by the Linux Foundation and a permissioned blockchain based on Hyperledger Fabric. Both systems were evaluated through Operational Intent Reference (OIR) registration work loads generated via Hyperledger Caliper, measuring throughput, latency, and transaction loss under loads up to 50 transactions per second. Results show that InterUSS sustained sub-second latency and stable performance up to 30 TPS. At the same time, Fabric exhibited exponential degradation with median latency exceeding 3 s and tail latencies above 15 s beyond that point. These findings demonstrate that blockchain-based architectures must be redesigned to meet aeronautical timing and scalability requirements, suggesting that hybrid models combining distributed ledgers for auditability with federated frameworks for real-time coordination are more suitable for future UTM deployments.
Seung‐A Annie Jin
Metaverses have been hailed as the next arena for a wide spectrum of technovation and business opportunities. This research (∑ N = 714) focuses on the three underexplored areas of virtual commerce in AI-enabled metaverses: blockchain-powered cryptocurrencies, non-fungible tokens (NFTs), and AI-powered virtual influencers. Study 1 reports the mediating effects of (dis)trust in AI-enabled blockchain technologies and the moderating effects of consumers’ technopian perspectives in explaining the relationship between blockchain transparency perception and intention to use cryptocurrencies in AI-powered metaverses. Study 1 also reports the mediating effects of Neo-Luddism perspectives regarding metaverses and the moderating effects of consumers’ social phobia in explaining the relationship between AI-algorithm awareness and behavioral intention to engage with AI-powered virtual influencers in metaverses. Study 2 reports the serial mediating effects of general perception of NFT ownership and psychological ownership of NFTs as well as the moderating effects of the investment value of NFTs in explaining the relationship between acknowledgment of the nature of NFTs and intention to use NFTs in AI-enabled metaverses. Theoretical contributions to the literature on digital materiality and psychological ownership of blockchain/cryptocurrency-powered NFTs as emerging forms of digital consumption objects are discussed. Practical implications for NFT-based branding/entrepreneurship and creative industries in blockchain-enabled metaverses are provided.
Patan Mushiya Katoon, Anil V. Turukmane
Electronic Health Records (EHR) is the main core of modern healthcare, but interoperability across different blockchain platforms is a key challenge. This work proposes a cross-chain middleware architecture, which facilitates secure and real-time synchronization of EHR data between Hyperledger Fabric (private blockchain) and Ethereum Sepolia Testnet (public blockchain). The framework integrates AES-256 encryption and Inter Planetary File System (IPFS) as decentralized storage to enhance patient privacy. To facilitate interoperability across the blockchains the research introduces a smart middleware layer. This layer autonomously monitors the blockchain events, processes encrypted CIDs, enforces real time cross chain consistency and smart contract-based access control. The experimental evaluation shows that proposed framework achieves low synchronization times (< 195 ms), low gas and latency costs, small encryption overhead (< 4–5 KB), robust file storage and retrieval through IPFS. Such positive evaluations with scalable and real-time deployment, sets the foundation of patient centric interoperable healthcare ecosystems.
Iacovone, L.
In service firms, where value creation increasingly depends on human interaction and intangible assets, the development of soft skills and inclusive mindsets has become a strategic priority.Yet, traditional training programs rarely generate lasting behavioral change or make unconscious biases visible.This paper explores how Web3-enabled neuro-immersive technologies can transform learning processes within service organizations, turning technology-assisted experiences into ethically managed and measurable forms of knowledge creation.Drawing on ten real-world cases developed between 2021 and 2025 across consulting, banking, healthcare, and education, the study adopts a qualitative, comparative approach to examine how immersive simulations affect individuals' awareness, emotional regulation, and decision-making.
Hongzhe Wen
Digital Asset Treasury (DAT) companies, public firms that hold large crypto reserves as a core strategy, deliver levered exposure to digital assets but face acute downside risk when equity premia over net asset value multiples (mNAV) compress in bear markets. This paper develops a survival framework that couples conservative treasury policy with an operating line that monetizes holdings independent of mark-to-market gains. Using Strategy (formerly MicroStrategy) as a case, we propose a "BTC-to-sats" payments rail that allocates a small, risk-capped liquidity sleeve of the treasury to Lightning Network channels, generating price-agnostic fee revenue (acquiring bps, routing, hedge/FX spread) while keeping settlement exposure near zero beta to BTC. We formalize a no-forced-sale condition and show how disclosed KPIs allow investors to test whether operating cash flows can bridge an 18 to 24-month bear without liquidations. The feasibility of the rail is supported by Strategy's Lightning initiative and empirical Lightning performance. Our model generalizes across DAT types and provides implementable disclosures that can sustain an mNAV premium through cycles.
Jimmy Jimmy, Kenny Rimba, Vincent Vincent, Ronsen Purba · 5 authors
E-voting systems are prone to challenges such as lack of transparency, risks of data manipulation, and dependence on centralized authorities, which can undermine trust in electoral processes. This research develops a blockchain-based e-voting system on the Polygon network, leveraging smart contracts and Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARK) to enhance security, transparency, and voter anonymity. The study employs an application development approach, implementing a structured methodology with initialization, registration, voting, and tallying phases. Smart contracts automate voter verification, vote casting, and result tabulation, while ZK-SNARK ensures voters can cast ballots anonymously without revealing their identities. The system’s transparency and immutability are tested using PolygonScan, demonstrating effective prevention of manipulations like double voting through cryptographic credentials (nullifier, commitment, and nullifier hash) and Merkle Tree structures. Results indicate that the system provides a secure, verifiable, and decentralized framework for elections. This implementation offers a robust foundation for future e-voting systems, promoting trust and integrity in digital voting processes.
Goukassian, Lev
A systemic "evidentiary deficit" now characterizes automated global civicsystems, undermining regulatory oversight, institutional accountability, and public trust in high-stakes domains. The increasing opacity of high-speed, algorithmically-driven decisions in finance, public health, and environmental governance creates un-auditable risks. This report posits Ternary Logic (TL) as a neutral, non-ideological infrastructure framework designed to remediate this deficit. TL extends traditional binary logic by introducing a formal, third logical state: 0 (Epistemic Hold), distinct from 1 (Proceed) and -1 (Halt). This 0 state functions as a mandatory, auditable "computational hesitation" triggered by predefined uncertainty or risk thresholds. By instrumenting this pause, TL transforms deliberation and uncertainty from an operational failure into a cryptographically verifiable evidentiary asset. This report details the TL architecture through its Eight Pillars, which provide an integrated "accountability stack" mapping institutional policy to cryptographic proof. It describes the tri-cameral governance model—Technical Council, Stewardship Custodians, and Smart Contract Safeguard—architected for long-term resilience and prevention of institutional capture. Furthermore, it details the technical architecture, including a dual-lane, low-latency (<300ms) design, a hybrid-shield (public/private) ledger system, and a novel cryptographic stack (combining Ephemeral Key Rotation, Zero-Knowledge Proofs, and Cryptographic Erasure) that simultaneously satisfies regulatory demands for auditability, legal requirements for privacy (e.g., GDPR), and commercial protection of trade secrets. This framework provides a sovereign-grade blueprint for establishing provable accountability in systems governed by institutions such as the Bank for International Settlements (BIS), U.S. Securities and Exchange Commission (SEC), U.S. Food and Drug Administration (FDA), and World Health Organization (WHO).
Dusabimana Emmanuel, KN Jonathan, Djuma Sumbiri
Decentralized Finance (DeFi) has been identified as an emerging technology for a transformative force in financial intermediation, introducing a trustless, programmable, and inclusive financial ecosystem. This paper identifies, show, and explores the integration of DeFi into traditional finance, focusing on how DeFi platforms are redefining financial intermediation and incorporates not only the financial perspective but also an IT-systems perspective, detailing architectures, data structures, and integration frameworks that enable collaboration between DeFi platforms and traditional financial institutions. The research identifies the limitations of current financial systems, evaluates the technical and regulatory challenges of integration, and highlights how DeFi innovations can increase efficiency, transparency, and inclusivity. Key components of this integration, such as smart contracts, decentralized lending, and interoperable frameworks, are analyzed along with their potential to overcome limitations in traditional finance. The paper concludes with recommendations for a mutually beneficial model combining DeFi and traditional finance to create a robust, secure, and inclusive global financial ecosystem.
Lumengo Bonga‐Bonga, Muhammad Khalique
This paper investigates the relationship between cryptocurrencies and other financial assets, with a particular focus on the dynamics of information flow between developed and emerging markets. To achieve this objective, the study applies a combined methodology of spillover index analysis and network topology based on graph theory. The analysis covers key cryptocurrencies (Bitcoin and Ethereum), stocks, and conventional currencies over the period November 2017 to September 2022, and distinguishes between short-term and long-run dynamics. The empirical findings show that in the short run, Bitcoin and Ethereum predominantly act as net shock transmitters, whereas in the long run, stocks and conventional currencies, together with Bitcoin and Ethereum, become the principal conveyors of spillover shocks. The network topology analysis corroborates these results by revealing the centrality of these assets in the spillover structure. By integrating spillover and network approaches across different markets and time horizons, this study contributes to the literature by providing a more nuanced understanding of how cryptocurrencies interact with traditional financial assets under varying market conditions.
Khoi Minh Nguyen, Lý Thị Trần, Binh-Hau Nguyen, Minh T. Nguyen · 7 authors
Blockchain functions as a “distributed ledger network,” ensuring immutability, transparency, and non-retroactivity of data, making it a key technology for sustainable development. This study explores how blockchain-enabled traceability systems influence consumer perceptions of environmental transparency, trust in technology, and purchase intentions for sustainable food in Vietnam. Using a digital survey of 450 participants and SmartPLS 4.0 with PLS-SEM analysis, findings reveal that both blockchain reviews and traceability systems significantly improve perceptions of transparency (β = 0.292; β = 0.364, p < 0.001) and technological trust (β = 0.268; β = 0.348, p < 0.001). The research bridges the gap between transparency perceptions and purchase behavior in sustainable development and foodservice strategy. It is one of the first studies to examine the combined impact of blockchain reviews and traceability. The article adds to existing literature by expanding understanding of blockchain’s effect, supporting businesses in aligning with the UN’s Sustainable Development Goals.
Haoxin Sun, Yu Xiao, Jiale Li, Yiwen Xu · 8 authors
Since the advent of smart contracts, security vulnerabilities have remained a persistent challenge, compromsing both the reliability of contract execution and the overall stability of the virtual currency market. Consequently... | Find, read and cite all the research you need on Tech Science Press
Rana Alaa, Darío González-Ferreiro, Carlos Beis-Penedo, Manuel Fernández‐Veiga · 6 authors
Split learning is an approach to collaborative learning in which a deep neural network is divided into two parts: client-side and server-side at a cut layer. The client side executes its model using its raw input data and sends the intermediate activation to the server side. This configuration architecture is very useful for enabling collaborative training when data or resources are separated between devices. However, split learning lacks the ability to verify the correctness and honesty of the computations that are performed and exchanged between the parties. To this purpose, this paper proposes a verifiable split learning framework that integrates a zk-SNARK proof to ensure correctness and verifiability. The zk-SNARK proof and verification are generated for both sides in forward propagation and backward propagation on the server side, guaranteeing verifiability on both sides. The verifiable split learning architecture is compared to a blockchain-enabled system for the same deep learning network, one that records updates but without generating the zero-knowledge proof. From the comparison, it can be deduced that applying the zk-SNARK test achieves verifiability and correctness, while blockchains are lightweight but unverifiable.
M.Z. Haider, M.U. Ghouri, Tayyaba Noreen, M. Salman
Blockchain systems face persistent challenges of scalability, latency, and energy inefficiency. Existing consensus protocols such as Proof-of-Work (PoW) and Proof-of-Stake (PoS) either consume excessive resources or risk centralization. This paper proposes \textit{Proof-of-Spiking-Neurons (PoSN)}, a neuromorphic consensus protocol inspired by spiking neural networks. PoSN encodes transactions as spike trains, elects leaders through competitive firing dynamics, and finalizes blocks via neural synchronization, enabling parallel and event-driven consensus with minimal energy overhead. A hybrid system architecture is implemented on neuromorphic platforms, supported by simulation frameworks such as Nengo and PyNN. Experimental results show significant gains in energy efficiency, throughput, and convergence compared to PoB and PoR. PoSN establishes a foundation for sustainable, adaptive blockchains suitable for IoT, edge, and large-scale distributed systems.
saiprasad
The contemporary Internet, a cornerstone of modern society, is characterized by a high degree of centralization. This centralization concentrates data and power within a few large corporations, raising significant concerns regarding data privacy, censorship, single points of failure, and monopolistic control. The "Decentralized Internet," often associated with the Web3 paradigm, proposes a fundamental shift toward a more open, trustless, and user-centric network. This paper presents a comprehensive survey of the decentralized Internet, beginning with an exploration of its core principles—trustlessness, censorship resistance, and user-controlled data. We then examine the key enabling technologies that underpin the decentralized Internet, including distributed ledger technologies (DLT), peer-to-peer (P2P) data protocols such as the InterPlanetary File System (IPFS), and smart contracts. Finally, we discuss the significant open challenges and research questions that must be addressed, including scalability, usability, governance, and regulatory uncertainty. This paper aims to provide a structured overview for researchers, developers, and policymakers interested in the future of Internet architecture. Index Terms—Decentralized Internet, Web3, Blockchain, Peer-to-Peer (P2P), IPFS, Distributed Ledger Technology (DLT), Smart Contracts, Decentralized Applications (dApps), Scalability, Governance.
Liang, Hanzhong, Yue Duan, Xing Su, Xiao Li · 8 authors
As the Web3 ecosystem evolves toward a multi-chain architecture, cross-chain bridges have become critical infrastructure for enabling interoperability between diverse blockchain networks. However, while connecting isolated blockchains, the lack of cross-chain transaction pairing records introduces significant challenges for security analysis like cross-chain fund tracing, advanced vulnerability detection, and transaction graph-based analysis. To address this gap, we introduce ConneX, an automated and general-purpose system designed to accurately identify corresponding transaction pairs across both ends of cross-chain bridges. Our system leverages Large Language Models (LLMs) to efficiently prune the semantic search space by identifying semantically plausible key information candidates within complex transaction records. Further, it deploys a novel examiner module that refines these candidates by validating them against transaction values, effectively addressing semantic ambiguities and identifying the correct semantics. Extensive evaluations on a dataset of about 500,000 transactions from five major bridge platforms demonstrate that ConneX achieves an average F1 score of 0.9746, surpassing baselines by at least 20.05\%, with good efficiency that reduces the semantic search space by several orders of magnitude (1e10 to less than 100). Moreover, its successful application in tracing illicit funds (including a cross-chain transfer worth $1 million) in real-world hacking incidents underscores its practical utility for enhancing cross-chain security and transparency.
Shashank Motepalli, N. Garg, Gengrui Zhang, Hans‐Arno Jacobsen
Geospatial decentralization is essential for blockchains, ensuring regulatory resilience, robustness, and fairness. We empirically analyze five major Proof of Stake (PoS) blockchains: Aptos, Avalanche, Ethereum, Solana, and Sui, revealing that a few geographic regions dominate consensus voting power, resulting in limited geospatial decentralization. To address this, we propose Geospatially aware Proof of Stake (GPoS), which integrates geospatial diversity with stake-based voting power. Experimental evaluation demonstrates an average 45% improvement in geospatial decentralization, as measured by the Gini coefficient of Eigenvector centrality, while incurring minimal performance overhead in BFT protocols, including HotStuff and CometBFT. These results demonstrate that GPoS can improve geospatial decentralization {while, in our experiments, incurring minimal overhead} to consensus performance.
Wen Yang, Qiming Ye, Onur Ascigil, Saidu Sokoto · 7 authors
This paper presents the first empirical analysis of how diverse token-based reward mechanisms impact platform dynamics and user behaviors. For this, we gather a unique, large-scale dataset from Farcaster. This blockchain-based, decentralized social network incorporates multiple incentive mechanisms spanning platform-native rewards, third-party token programs, and peer-to-peer tipping. Our dataset captures token transactions and social interactions from 574,829 wallet-linked users, representing 64.25% of the platform's user base. Our socioeconomic analyses reveal how different tokenomics design shape varying participation rates (7.6%--70%) and wealth concentration patterns (Gini 0.72--0.94), whereas inter-community tipping is 1.3--2x more frequent among non-following pairs, thereby mitigating echo chambers. Our causal analyses further uncover several critical trade-offs: (1) while most token rewards boost content creation, they often fail to enhance -- sometimes undermining -- content quality; (2) token rewards increase follower acquisition but show neutral or negative effects on outbound following, suggesting potential asymmetric network growth; (3) repeated algorithmic rewards demonstrate strong cumulative effects that may encourage strategic optimization. Our findings advance understanding of cryptocurrency integration in social platforms and highlight challenges in aligning economic incentives with authentic social value.
Qi Xia, Hu Xia, Isaac Amankona Obiri, Adjei-Arthur Bonsu · 11 authors
Blockchain technology facilitates the development of decentralized systems that ensure trust and transparency without the need for expensive centralized intermediaries. However, existing blockchain architectures particularly consortium blockchains face critical challenges related to scalability and efficiency. State sharding has emerged as a promising approach to enhance blockchain scalability and performance. However, current shard-based solutions often struggle to guarantee fair participation and a balanced workload distribution among consortium members. To address these limitations, we propose Trusted Intelligent NetChain (TINC), a multi-plane sharding architecture specifically designed for consortium blockchains. TINC incorporates intelligent mechanisms for adaptive node assignment and dynamic workload balancing, enabling the system to respond effectively to changing network conditions while maintaining equitable shard utilization. By decoupling the control and data planes, TINC allows control nodes to focus on consensus operations, while data nodes handle large-scale storage, thus improving overall resource efficiency. Extensive experimental evaluation and formal analysis demonstrate that TINC significantly outperforms existing shard-based blockchain frameworks. It achieves higher throughput, lower latency, balanced node and transaction distributions, and reduced transaction failure rates. Furthermore, TINC maintains essential blockchain security guarantees, exhibiting resilience against Byzantine faults and dynamic network environments. The integration of Dynamic Decentralized Identifiers (DDIDs) further strengthens trust and security management within the consortium network.
O.I. Musii
The article explores the potential of blockchain technology and smart contracts in the field of public administration. The emphasis is on the legal challenges that arise in the process of implementing relevant innovations, as well as on the opportunities they open up for increasing transparency, efficiency, and trust in state institutions. The relevance of the topic is due to global digitalization processes, the need to modernize public administration, and the growing demand from society for openness and public control over the work of state authorities. The novelty of the study lies in the study of the legal aspect of integrating decentralized technologies into the public sphere, which has not yet been sufficiently developed in the Ukrainian legal community. The international experience of regulating smart contracts is analyzed, legal gaps in Ukrainian legislation are identified, and proposals for its improvement are formulated. The results obtained may be useful for legislators, representatives of state bodies, and researchers in the field of digitalization of processes in public administration. Furthermore, the research highlights practical applications of blockchain and smart contracts in various public administration sectors, including digital identity management, tax collection, social welfare distribution, and property registration. By examining pilot projects and international case studies, the study demonstrates how these technologies can streamline administrative processes, reduce bureaucracy, and minimize the risk of corruption. The findings suggest that a gradual, regulated integration of blockchain solutions could significantly enhance operational efficiency and citizen satisfaction. Finally, the study addresses the potential risks and limitations associated with blockchain adoption in the public sector, including high implementation costs, technological challenges, and legal uncertainty. It emphasizes the importance of developing comprehensive regulatory frameworks, establishing clear standards for smart contract usage, and ensuring that public sector employees are equipped with the necessary technical skills. The paper concludes that while blockchain offers transformative opportunities, its successful adoption in public administration depends on a balanced approach that combines technological innovation with legal and institutional preparedness.
Abhirup Khanna, Divya Srivastava, Anushree Sah, Sarishma Dangi · 8 authors
The increasing complexity of urban energy systems requires decentralized, sustainable, and scalable solutions. The paper presents a new multi-layered framework for smart energy management in microgrids by bringing together advanced forecasting, decentralized decision-making, evolutionary optimization and blockchain-based coordination. Unlike previous research addressing these components separately, the proposed architecture combines five interdependent layers that include forecasting, decision-making, optimization, sustainability modeling, and blockchain implementation. A key innovation is the use of Temporal Fusion Transformer (TFT) for interpretable multi-horizon forecasting of energy demand, renewable generation, and electric vehicle (EV) availability which outperforms conventional LSTM, GRU and RNN models. Another novelty is the hybridization of Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), to simultaneously support discrete and continuous decision variables, allowing for dynamic pricing, efficient energy dispatching and adaptive EV scheduling. Multi-Agent Reinforcement Learning (MARL) which is improved by sustainability shaping by including carbon intensity, renewable utilization ratio, peak to average load ratio and net present value in agent rewards. Finally, Ethereum-based smart contracts add another unique contribution by providing the implementation of transparent and tamper-proof peer-to-peer energy trading and automated sustainability incentives. The proposed framework strengthens resilient infrastructure through decentralized coordination and intelligent optimization while contributing to climate mitigation by reducing carbon intensity and enhancing renewable integration. Experimental results demonstrate that the proposed framework achieves a 14.6% reduction in carbon intensity, a 12.3% increase in renewable utilization ratio, and a 9.7% improvement in peak-to-average load ratio compared with baseline models. The TFT-based forecasting model achieves RMSE = 0.041 kWh and MAE = 0.032 kWh, outperforming LSTM and GRU by 11% and 8%, respectively.
Authors unavailable
In the evolving landscape of cybercrime and digital investigations, the integrity and traceability of digital evidence are paramount.Traditional chain-of-custody (CoC) mechanisms in digital forensics rely heavily on centralized systems, manual logging, and institutional trust, all of which are prone to human error, tampering, and data loss.This study introduces a blockchain-based chain-of-custody model aimed at ensuring immutable, transparent, and verifiable tracking of digital evidence across its entire lifecycle-from acquisition and analysis to presentation in court.Leveraging blockchain's decentralized architecture and cryptographic immutability, the proposed framework records every interaction with digital evidence, including transfers, access logs, and analysis events, in a tamper-proof ledger distributed across trusted nodes in a forensic network.Smart contracts automate procedural compliance, access permissions, and time-stamping, thereby reducing reliance on third-party oversight and enhancing procedural integrity.The system was designed and simulated using Hyperledger Fabric, integrating role-based access control and hash-based evidence fingerprinting.Benchmark testing demonstrated the model's robustness in preserving forensic timelines under various adversarial scenarios, including internal breaches and unauthorized access attempts.In addition to enhancing evidentiary credibility, this blockchain-enhanced CoC model offers interoperability with existing digital forensic tools and forensic readiness systems.By aligning with legal admissibility standards and ensuring end-to-end accountability, the framework strengthens the evidentiary chain, particularly in multi-jurisdictional and cloudbased investigations.As digital forensics faces increasing scrutiny regarding evidentiary handling, this research presents a scalable and future-proof alternative to conventional CoC practices-crucial for maintaining the rule of law in cybercrime prosecutions.
Ridwan Abdulsalam
The increasing complexity and sophistication of financial fraud have necessitated more effective and real-time solutions for monitoring, detecting, and preventing illicit activities in the financial sector. Blockchain technology, with its inherent features of decentralization, immutability, and transparency, has emerged as a promising tool to address these challenges, particularly when integrated with Regulatory Technology (RegTech) systems. This explores the potential of blockchain-powered RegTech solutions for enhancing fraud detection and supporting legal oversight in financial institutions. Blockchain’s decentralized ledger system provides a secure and transparent environment where financial transactions can be monitored in real time. The integration of machine learning algorithms with blockchain analytics allows for the identification of suspicious patterns and anomalies, enabling rapid detection of fraudulent activities. Additionally, blockchain facilitates the automation of compliance reporting, reducing operational costs and ensuring regulatory standards are met with minimal human intervention. The use of smart contracts further streamlines the enforcement of compliance rules, providing a seamless and tamper-proof audit trail. Furthermore, blockchain has the potential to harmonize international compliance standards, enabling more efficient cross-border regulatory enforcement. Through its use in decentralized identity verification and AML (Anti-Money Laundering) systems, blockchain can enhance the traceability and transparency of financial transactions, addressing the challenges of jurisdictional fragmentation and inconsistent regulations across countries. Privacy-preserving technologies, such as zero-knowledge proofs, also ensure that data protection laws like GDPR are respected while maintaining regulatory oversight. This concludes by highlighting the substantial benefits blockchain-powered RegTech systems offer for real-time fraud detection and regulatory compliance, urging financial institutions and regulators to collaborate on adopting these technologies to safeguard the integrity of global financial systems. Keywords: Harnessing, Blockchain-powered, RegTech systems, Real-Time, Fraud Detection, Legal Oversight, Financial Institutions.
John Adeyemi O, Folasade Yetunde Ayankoya, Kuyoro S. O
The advancement of technology has positioned blockchain and machine learning (ML) as transformative forces in finance. Blockchain’s decentralized structure ensures secure and transparent transactions, while ML processes vast data to identify patterns and enhance decision-making. Their integration offers significant potential for fraud detection, risk assessment, and transaction optimization. Blockchain provides a tamper-proof environment, ensuring data integrity and reducing fraud. Meanwhile, ML detects anomalies, predicts market trends, and automates processes, improving financial security and efficiency. However, challenges such as scalability, computational demands, and data privacy hinder widespread adoption. Blockchain struggles with high costs and limited throughput, while ML requires significant resources and quality data. Emerging solutions like federated learning for privacy-preserving ML, zero-knowledge proofs for secure transactions, and hybrid blockchain models for scalability aim to address these challenges. Overcoming these barriers will enable a more secure, efficient, and data-driven financial ecosystem.