The accelerating geopolitical rivalry between major powers has renewed interest in diversifying central bank reserves. Traditionally dominated by the US dollar and gold, global reserve composition is now being reconsidered amid de-dollarization trends and the growing relevance of crypto assets – particularly Bitcoin. This study examines the rationale, risks, and strategic implications of incorporating Bitcoin into sovereign reserve portfolios, with a focus on the financial confrontation between the United States (US) and the People’s Republic of China (China).Adopting an interdisciplinary approach, the paper integrates macroeconomic, legal, and geopolitical analysis. It explores the United States’ gradual institutional accommodation of Bitcoin, culminating in the 2025 establishment of a Strategic Bitcoin Reserve, contrasted with China’s prohibitive stance and promotion of the centralized digital yuan (e-CNY). The study further analyzes the legal instruments, regulatory strategies, and infrastructural controls through which the US exerts influence over crypto markets, including indirect market interventions and custodial frameworks.Findings indicate that, despite high volatility and limited adoption, Bitcoin is increasingly perceived as a strategic hedge by states seeking to reduce dependence on traditional financial hegemony. While its formal inclusion in reserves remains marginal and politically constrained, its symbolic and geopolitical utility is growing – particularly for sanctioned or financially isolated economies.The article concludes that Bitcoin’s role in global finance may expand under specific conditions: market stabilization, regulatory convergence, and persistent geopolitical fragmentation. To support structured evaluation, the paper introduces two novel analytical concepts – the Sovereign Crypto Reserve Readiness Index (SCRRI) and the Bitcoin Reserve Exposure Threshold (BRET), which together provide a framework for assessing both institutional feasibility and risk-adjusted limits for sovereign Bitcoin integration.
The demand for privacy-preserving machine learning has led to the rise of Federated Learning (FL), where multiple clients collaboratively train a model without sharing raw data. Despite its privacy benefits, FL is vulnerable to Byzantine failures, where malicious or faulty participants inject corrupted updates, threatening model integrity. To address this, a range of Byzantine-resilient aggregation techniques have been proposed, including statistical filters (e.g., Trimmed Mean, Krum), trust-based weighting, cryptographic protocols, and hybrid strategies. This paper presents a systematic literature review (SLR) of these defenses, evaluating their robustness, scalability, and suitability for real-world applications. Challenges such as non-IID data, adaptive attacks, and trade-offs between security and efficiency are critically examined. In addition, we explore emerging trends such as domain-specific defenses, energy-aware FL, quantum-resilient methods, and federated zero-knowledge proofs. A novel classification of hybrid approaches and a standardized benchmarking framework are proposed to guide future research. This review aims to support the development of resilient, efficient and scalable decentralized learning systems in adversarial environments.
Shilpa Kottapally, Sr. Software Development Engineer, Adjudication - Rxclaim developement Application, CVS Health, 2100 E lake cook road , Buffalo grove Illinois 60047, USA
International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
As in many areas of talent and creativity, the field of musical talent and creativity has also entered into new debates with recent technological developments. In this study, I aimed to examine the transformative effects of blockchain technology and NFTs (Non-Fungible Tokens) on copyright management and the creation of “value” in musical creativity (within the music industry). This research comprehensively analyzes the structural inadequacies of traditional copyright systems and the transformative potential of blockchain-based solutions. The research model is based on a methodological synthesis of case studies and theoretical paradigms. The findings demonstrate that blockchain’s decentralized architecture and the unique nature of NFTs provide artists with greater autonomy over their intellectual property; smart contracts automate royalty payments, democratize financial flows, and restructure the creator-audience relationship by eliminating intermediaries. Case studies such as the electronic musician RAC and the decentralized platform Audius concretely show how this technological integration reshapes artistic production and distribution mechanisms. However, the existing legal frameworks lag behind technological innovation. There are significant challenges to be addressed, such as inconsistencies between national and international copyright laws and uncertainties regarding the legal status of NFTs. Blockchain and NFTs have the potential to transform the ontological structure of the music industry by offering creative control, transparent copyright management, direct fan engagement, and alternative income streams for artists. These technologies also carry the potential to evolve the music sector toward a more transparent, fair, and artist-centered model. Therefore, all stakeholders in the industry may need to adopt this technological transformation strategically. Nevertheless, the ecological impacts of blockchain-based copyright systems, including energy consumption and digital carbon footprint, must also be discussed from a critical sustainability perspective. In evaluating the value of musical talent and creativity, it is now essential for disciplines such as musicology, technology studies, economics, and law to work together and adopt a holistic approach to the evolving dynamics of the digital art economy. In this context, blockchain applications in the music industry are interpreted through the cultural, socioeconomic, and epistemological dimensions of the global digital economy — not merely through the lens of technological determinism but also from the perspectives of artistic autonomy and social justice..
Bu çalışmada, kripto para piyasasında en yüksek işlem hacmine sahip varlıklar arasında yer alan Bitcoin, Ethereum ve Binance Coin’in günlük kapanış fiyatları incelenmiştir. Çalışmada ele alınan kripto para getirilerinin uzun hafıza özelliği gösterip göstermediğinin belirlenmesi ve uygun model tahmininin yapılması amaçlanmıştır. Getiri serilerinin uzun hafıza özelliğinin tespit edilmesi için literatürde sıklıkla ele alınan Hurst katsayısı, Geweke ve Porter-Hudak testi ve Yerel Whittle Tahmincisi kullanılmıştır. Ayrıca uzun hafızanın tespitine yönelik klasik testlerin yanı sıra, çok değişkenli yerel Whittle Skor tipi test ve Qu (2011) tarafından önerilen uzun hafıza testleri de yapılmıştır. Elde edilen bulgulara göre üç kripto para biriminin de uzun hafıza özelliği gösterdiği tespit edilmiştir. Ardından uzun hafızanın varlığı dikkate alınarak getiri ve koşullu varyansın modellenmesi için Otoregresif Kesirli Bütünleşik Hareketli Ortalama (ARFIMA) ve Kesirli Bütünleşik Genelleştirilmiş Otoregresif Koşullu Değişen Varyans (FIGARCH) modelleri tahmin edilmiştir. Tahmin edilen FIGARCH modellerinde kesirli fark parametresi 0
This study investigates the effectiveness of a hybrid forecasting model that combines Generalized Autoregressive Conditional Heteroskedasticity (GARCH) with Long Short-Term Memory (LSTM) neural networks, specifically applied to the cryptocurrency market, focusing on Bitcoin and Ethereum.The inherent volatility of cryptocurrencies presents substantial challenges for accurate price prediction, necessitating advanced methodologies that can adapt to fluctuating market conditions.We first utilize GARCH models to analyze and capture the time-varying volatility in the returns of Bitcoin and Ethereum, enabling a comprehensive understanding of the underlying market dynamics.Following this, we implement LSTM networks to exploit their capability to model complex, non-linear relationships in sequential data, enhancing the predictive power of the model.The performance of the GARCH-LSTM framework is rigorously evaluated using historical price data for Bitcoin and Ethereum, employing key metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to assess forecasting accuracy.The results demonstrate that the hybrid approach significantly outperforms traditional forecasting methods, providing more reliable predictions and insights into market trends.This study contributes to the growing body of literature on cryptocurrency forecasting by illustrating the potential of combining econometric techniques with advanced machine learning methods, offering valuable implications for traders and investors in the cryptocurrency ecosystem.However, the experimental results revealed that the LSTM model outperformed the other eight methods in terms of forecasting performance measures, the RMSPE validation is 0.112561, and the RMSE validation is 0.011456.
The integration of blockchain technology and Non-Fungible Tokens (NFTs) into Tanzanian art signifies a pivotal moment with transformative potential for artists, drawing on Everett Rogers' Diffusion of Innovations Theory. This discussion explores the implications of merging blockchain and NFTs, focusing on themes like technological decentralisation, cultural empowerment, and associated challenges. Blockchain empowers artists by facilitating direct engagement with a global audience and eliminating the need for intermediaries. It also creates unalterable ownership records, giving artists greater control over their work. NFTs contribute to digitally preserving and sharing Tanzanian cultural heritage, increasing visibility and influence for previously marginalised voices on the international stage. Despite these promising opportunities, integration faces obstacles such as limited technological access and complex legal frameworks, which hinder wider adoption. Addressing these issues requires collaboration to reduce digital inequalities, promote understanding of blockchain technology, and strengthen legal protections. Ultimately, combining blockchain and NFTs could transform the Tanzanian art scene by amplifying cultural voices and protecting heritage in an increasingly digital world. Success depends on effectively managing challenges and capitalising on emerging opportunities.
In the rapidly evolving landscape of cloud computing, ensuring secure user authentication and protection against cyber-attacks has become increasingly critical. This research proposes a novel security framework for cloud systems based on the Quantum Zero-Knowledge Proof (ZKP) technique, aiming to provide a privacy-preserving and quantum-resilient authentication mechanism. The core of the proposed model lies in leveraging photon polarization at specific quantum angles to implement secure and non-disclosive verification, effectively allowing users (provers) to prove their identity without revealing any sensitive credentials. The system's architecture integrates a Zero Knowledge Proof Engine (ZKE), which forms the backbone of the security protocol, enhancing resilience against Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks. The quantum properties of photons enable a high level of randomness and unpredictability, significantly improving the robustness of the system. A Python-based simulation environment has been developed to model the proposed engine and conduct experimental validations. Furthermore, a web-based application interface has been designed to facilitate seamless interaction between cloud users and the authentication system, demonstrating real-time threat detection and response. Experimental results, visualized through performance metrics and interface output, confirm the effectiveness and practicality of the proposed model. This approach not only enhances security but also offers a scalable and user-friendly solution for modern cloud environments, marking a significant step toward integrating quantum principles into mainstream cybersecurity infrastructures.
The evolving manufacturing landscape, characterized by increasing demands for customization, flexibility, and efficiency, requires adaptive systems that can respond in an autonomous and dynamic way. Bio-inspired Adaptive Manufacturing Systems, or Bio-AMS, provide a novel answer by integrating principles from nature that include self-organization, resilience, and adaptability. This paper covers the development and application of Bio-AMS, in which biological inspiration from organisms and ecosystems was applied to create systems that would adapt to varying production demands, disturbances, and resource constraints. In this manner, Bio-AMS enhances both the efficiency and scalability of systems with decentralized control, adaptive feedback, and MAS architectures. Simulations show that Bio-AMS outperforms conventional systems in terms of minimizing downtime and maximizing productivity. Case studies demonstrate their capability for autonomous adaptation to disruption and therefore operational resilience. Future work focuses on refining the algorithms, integrating advanced technologies like AI and IoT, and taking the applications to various industries.
This paper studies the \emph{unimodular isomorphism problem} (UIP) of convex lattice polytopes: given two convex lattice polytopes $P$ and $P'$, decide whether there exists a unimodular affine transformation mapping $P$ to $P'$. We show that UIP is graph isomorphism hard, while the polytope congruence problem and the combinatorial polytope isomorphism problem (Akutsu, 1998; Kaibel, Schwartz, 2003) were shown to be graph isomorphism complete, and both the lattice isomorphism problem ( $\mathrm{Sikiri\acute{c}}$, $\mathrm{Sch\ddot{u}rmann}$, Vallentin, 2009) and the projective/affine polytope isomorphism problem (Kaibel, Schwartz, 2003) were shown to be graph isomorphism hard. Furthermore, inspired by protocols for lattice (non-) isomorphism (Ducas, van Woerden, 2022; Haviv, Regev, 2014), we present a statistical zero-knowledge proof system for unimodular isomorphism of lattice polytopes. Finally, we propose an algorithm that given two lattice polytopes computes all unimodular affine transformations mapping one polytope to another and, in particular, decides UIP.
Non Fungible Tokens have changed digital ownership and how creators earn money. Between 2021 and 2024, the market value exceeded 40 billion. However, the fast growth of the NFT ecosystem has revealed serious issues in managing intellectual property rights. There is a lot of confusion about the difference between owning an NFT and owning the copyright for the underlying content. This research looks at the gap between traditional copyright laws and blockchain-based transactions. We use a mixed methods approach to analyze this disconnect. We create a new IP rights matrix that clearly shows how copyright law relates to NFT ownership structures. Additionally, we include a business model taxonomy that sorts new commercial applications by their IP risk and sustainability factors. By examining important legal cases, smart contracts, and interviews with stakeholders, we find key problems in enforcing laws across different regions, standardizing licenses, and assessing business opportunities.
The rapid digital transformation being currently experienced the developing economies such as Zimbabwe has underlined the inefficiencies and vulnerabilities in security of traditional Know Your Customer (KYC) processes. These KYC processes and procedures are predominantly manual, slow and are prone to data breaches. This paper proposes a privacy preserving authentication model for KYC optimization using Zero-Knowledge Proof (ZKP) cryptography. This model addresses critical challenges which include prolonged customer onboarding times, high operational costs and data compliance risks. By means of leveraging ZKP the model enables secure identity verification without exposing sensitive data which ensures compliance with Zimbabwe Data Protection Act. A mixed-methods approach was adopted, combining qualitative and quantitative techniques to design, develop and evaluate the model. Experimental results have demonstrate significant improvements in data privacy and onboarding efficiency which has seen reduced onboarding time from 3 days to under 10 minutes. The model scalability and adaptability potential makes it suitable for diverse sectors which covers education, healthcare, e-commerce and government services therefore positioning Zimbabwe as a leader in secure digital transformation.
Blockchain technology is becoming an important tool for secure financial transactions. It supports decentralized finance (DeFi) services and new ways of auditing. This paper gives an overview of how blockchain is used in financial modeling, focusing on DeFi and auditing. We explain the basic technology behind popular blockchain systems, like public platforms such as Ethereum (with smart contracts and oracle networks), and private systems like Hyperledger Fabric. We also look at advanced methods like zero-knowledge proofs. We show how these tools help build financial models in DeFi by allowing peer-to-peer services without needing trust, and in auditing by making data more transparent and secure. We compare different blockchains in terms of speed, cost, and how well they scale. Security issues (like smart contract bugs or attacks on consensus) and practical problems (like trusting oracles and following laws) are also discussed. The review article looks at challenges in using blockchain and some of the latest solutions, such as Ethereum’s move to proof-of-stake, sharding for better scalability, and using zero-knowledge proofs for privacy. We also suggest future research topics, like connecting different blockchains, checking smart contracts with formal methods, creating better rules and laws, and training skilled workers. The goal is to help researchers and professionals understand the current situation and future of blockchain in finance and auditing.
This article explores the potential of Decentralized Autonomous Organizations (DAOs) to contribute to the digital transformation of society through the lens of ethics, social structure, and emerging economic paradigms. The focus is on the synergy between DAO structures and artificial intelligence (AI), and the ways in which such convergence may support new redistributive mechanisms such as Universal Basic Income (UBI) and Inclusive Capitalism. By combining conceptual analysis, relevant case studies, and data derived from existing research, the article evaluates whether DAO-AI systems can provide scalable, ethical, and decentralized alternatives to traditional organizational and economic models.
In this paper, we consider how the introduction of blockchain technology into the healthcare system can address the many challenges the healthcare industry is facing. After outlining the evolution of blockchain technology since 2015, we focus on two representative blockchains, Ethereum and Cardano. We scrutinize their similarities and differences in light of their potential applications in the healthcare industry.
The rapid advancement of blockchain technology presents new opportunities and challenges for the Islamic financial system, particularly in ensuring compliance with Shariah principles. As Islamic finance continues to grow, there is a pressing need to explore how digital innovations such as smart contracts can be integrated without violating core religious tenets. This study explores the potential application of smart contracts in Islamic finance, focusing on how blockchain technology can support transactions that comply with Shariah principles. Using a qualitative approach with triangulation methods, the research combines systematic literature review, in-depth interviews, and comparative analysis between smart contract frameworks and classical Shariah contracts such as murabaha, mudarabah, and ijarah. The study examines how smart contracts can enhance transparency, reduce operational costs, and minimize human error while ensuring adherence to Islamic legal and ethical standards. The findings indicate that blockchain-based smart contracts can effectively automate Islamic financial transactions when designed with proper attention to the prohibition of riba (interest) and gharar (uncertainty). The research highlights the need for close collaboration between Shariah scholars and technology developers to ensure compliance. This study suggests that smart contracts hold significant promise for increasing efficiency, trust, and transparency in the Islamic financial ecosystem
Stablecoins represent a rapidly growing segment of the cryptocurrency market, aiming to overcome the high volatility of cryptocurrencies. Their primary goal is maintaining a stable value, usually pegged to fiat currencies (e.g., the US dollar), which facilitates their use in international payments, as assets within decentralized finance (DeFi), and as protection against inflation. This article explores blockchain technology, the development of stablecoins, methods of ensuring stability, and the reasons for their popularity among users. Special emphasis is placed on regulation at both the EU and US levels, evaluating the compliance of the most widely used stablecoins within legal frameworks. This research investigates advantages and risks, including their use in criminal activities, legal ambiguities, and potential instability. Quantitative and qualitative methods were utilized, including analysis of market capitalization, stability assurance mechanisms, and regulatory policies. Findings reveal that investors trust stablecoins backed by fiat currency reserves (particularly USD) the most, with Tether (USDT) holding the largest market share, despite its lack of full legislative compliance. The article highlights the key challenges and opportunities stablecoins present to individuals and financial markets.
Y. Suganya, Ch. Sudha Sree, S. Kayalvili, D. Joel Jebadurai · 8 authors
Despite its rapid expansion in the last ten years, the cryptocurrency market remains highly volatile and unpredictable, creating difficulties for both investors and market participants. Using artificial intelligence (AI) and machine learning techniques, this project seeks to build a predictive model for cryptocurrency prices, which will focus on Bitcoin, Ethereum, and Cardano to solve market challenges. The project aims to develop an end-to-end solution covering all stages of data management, which begins with setting up a real-time data ETL pipeline to collect information from the Binance and Yahoo Finance APIs. The system places data into a structured database that holds historical price information as well as technical indicators. Historical data serves as the basis for training and testing machine learning models to forecast price trends, which enhances cryptocurrency trading and investment decisions.
DeFi or Decentralized Finance aims to automate and decentralize any form of traditional finance workflow done by a centralized institution. In this regard, cross border payments and transactions in SAP ERPs can be automated and secured using DeFi protocols. Thus, this study aims to design a payment interface that would fit into SAP ERP frameworks capable of meeting the low-cost, automated, and secure requirements for cross-border payment transactions. Traditionally, payments were made via SWIFT and SEPA. The proposed model intends to replace these with DeFi transactions handled through smart contracts, oracles, and payment middleware. Focusing on results, transaction latency, smart contract auditability, saved costs, and compliance assessments were measured for Ethereum, BNB Smart Chain, and Polygon. Real SAP Business Environment pilots showed over 60% decrease in processing cost while settlement speed increased by up to 90%. The model is designed to handle enterprise risk and compliance by incorporating robust KYC/AML governance, validation, and logging controls. A roadmap for the incorporation of DeFi into enterprise ERPs at a large scale for finance automation will serve as the study’s conclusion.
Blockchain technology presents transformative opportunities for secure personal data sharing, particularly in healthcare, finance, and identity management. However, its widespread adoption is constrained by challenges such as limited scalability, privacy concerns, and conflicts with regulatory frameworks like the General Data Protection Regulation (GDPR). This study introduces a novel hybrid framework that integrates the InterPlanetary File System (IPFS) for off-chain storage with Zero-Knowledge Proofs (ZKPs) to enhance privacy, ensure regulatory compliance, and reduce on-chain storage demands. Employing a Design Science Research (DSR) methodology, the framework was developed and validated using Ethereum and Hyperledger Fabric, guided by insights from a systematic review of 180 studies from 2018 to 2023. Empirical evaluations revealed a 75% reduction in blockchain storage, 98% GDPR compliance, and zk-SNARK proof verification times below one second. The framework also enables GDPR-compliant erasure by removing encrypted off-chain data while preserving on-chain auditability. Despite challenges such as IPFS latency and trusted setup complexities, the solution offers a scalable and privacy-preserving architecture applicable to real-world domains, especially in privacy-critical environments like healthcare and finance by resolving blockchain’s GDPR compliance paradox.
Decentralized Finance (DeFi) is a blockchain-based financial system that utilizes smart contracts to increase efficiency and transparency, while overcoming the limitations of conventional financial systems. In Indonesia, there is still little research on blockchain, especially on the DeFi, so investors have very little information. The lack of previous research on the DeFi in Indonesia creates a knowledge gap, given that the local DeFi market has unique characteristics influenced by investor preferences, evolving regulations, and specific levels of technology adoption. Cryptocurrency prices, including the DeFi, are influenced by public information that reflects market efficiency. For example, on October 10, 2020, the price of Yearn Finance (YFI) increased 36% following the rise in Bitcoin prices, demonstrating the link between information, transaction volume, and fluctuations in the DeFi market value. This research aims to identify the factors that influence the DeFi price changes, focusing on the influence of price liquidity and market efficiency. Using a quantitative approach, 65 DeFi coins were selected through purposive sampling, and analysis was carried out using multiple regression using EViews 13. The research results show that partially, price liquidity and market efficiency do not have a significant effect on the DeFi price changes. However, simultaneously, these two variables have a significant effect, with a contribution to price changes of 54.521%. The insignificance of the influence of market efficiency on the DeFi prices suggests that regulations focused on improving efficiency may not be enough to control price volatility or promote price stability in the DeFi ecosystem.
FastSet is a distributed protocol for decentralized finance and settlement, which is inspired from both actors and blockchains. Account holders cooperate by making claims, which can include payments, holding and transferring assets, accessing and updating shared data, medical records, digital identity, and mathematical theorems, among others. The claims are signed by their owners and are broadcast to a decentralized network of validators, which validate and settle them. Validators replicate the global state of the accounts and need not communicate with each other. In sharp contrast to blockchains, strong consistency is purposely given up as a requirement. Yet, many if not most of the blockchain benefits are preserved, while capitalizing on actor's massive parallelism. The protocol is proved to be correct, despite its massively parallel nature.