Decentralized exchanges (DEXs) are crucial to de-centralized finance (DeFi) as they enable trading without intermediaries. However, they face challenges like impermanent loss (IL), where liquidity providers (LPs) see their assets’ value change un-favorably within a liquidity pool compared to outside it. To tackle these issues, we propose dynamic fee mechanisms over traditional fixed-fee structures used in automated market makers (AMM). Our solution includes asymmetric fees via block-adaptive, deal-adaptive, and the "ideal but unattainable" oracle-based fee algorithm, utilizing all data available to arbitrageurs to mitigate IL. We developed a simulation-based framework to compare these fee algorithms systematically. This framework replicates trading on a DEX, considering both informed and uninformed users and a psychological relative loss factor. Results show that adaptive algorithms outperform fixed-fee baselines in reducing IL while maintaining trading activity among uninformed users. Additionally, insights from oracle-based performance underscore the potential of dynamic fee strategies to lower IL, boost LP profitability, and enhance overall market efficiency.
Nai‐Wei Lo, Chi-Ying Chuang, Jheng-Jia Huang, Yuxuan Luo
With the rise of the Internet of Vehicles (IoV), secure and efficient authentication is essential to prevent cyber threats. This paper proposes a session key establishment protocol using Zero-Knowledge Proofs (zk-SNARKs) and Elliptic Curve Cryptography (ECC), including the Elliptic Curve Diffie–Hellman (ECDH) key exchange, to ensure privacy and efficiency. While zk-SNARK computations introduce additional verification overhead, our optimizations, such as precomputed proof parameters and lightweight session re-authentication, mitigate delays. Performance evaluation shows a 20% reduction in computation overhead and a 75% faster re-authentication time compared to existing methods, making it a secure and practical solution for real-world IoV applications.
Artificial Intelligence (AI), Internet of Things (IoT), and blockchain-powered chatbots are revolutionizing customer service, significantly enhancing customer satisfaction, experience, and loyalty. This research paper investigates the development and implementation of AI chatbots, emphasizing their capability to facilitate personalized and efficient customer interactions. Utilizing natural language processing (NLP) and machine learning (ML), these chatbots can comprehend and address customer inquiries in real-time, providing smooth support akin to human conversations. The paper highlights current trends, such as the use of sentiment analysis to understand customer emotions and customize responses accordingly, creating a more interactive and empathetic experience. Additionally, the deployment of predictive analytics allows chatbots to foresee customer needs and offer proactive solutions, thereby minimizing response times and boosting overall satisfaction. Moreover, the study examines how AI chatbots enhance customer loyalty by delivering consistent, round-the-clock support, making customers feel appreciated and heard. Through various industry studies, the research demonstrates the positive effects of AI chatbots on customer retention and brand reputation. The study suggests that ongoing innovation and the integration of sophisticated AI features will continue to improve the efficiency of chatbots in the customer service sector.
Crowdfunding platforms often face challenges such as high transaction fees, limited global accessibility, and reliance on traditional banking systems, which restrict participation and efficiency. These limitations hinder the full potential of crowdfunding, particularly for global contributors and projects. This research addresses these issues by proposing the development of a mobile crowdfunding platform integrated with cryptocurrency payment support. By incorporating cryptocurrency, the platform aims to reduce transaction costs, remove geographical barriers, and enhance transaction security through blockchain technology. The platform is built using a cross-platform mobile framework to ensure broad accessibility while integrating cryptocurrency gateways for decentralized financial transactions. This allows for real-time, secure, and low-cost payments, offering a transparent and efficient process for both contributors and fundraisers. Additionally, the platform's design supports scalability to accommodate various cryptocurrencies and an expanding user base. The findings demonstrate that cryptocurrency payment integration significantly improves transaction speed, reduces fees, and enhances security compared to traditional payment methods. It also fosters global participation, increasing engagement in crowdfunding initiatives.
This research paper explores the evolving landscape of cryptocurrency regulation in India, analysing the roles and limitations of existing regulatory frameworks under the Securities and Exchange Board of India (SEBI), the Reserve Bank of India (RBI), and the Prevention of Money Laundering Act (PMLA). As digital assets gain prominence, the Indian legal ecosystem struggles to keep pace due to a lack of comprehensive legislation, institutional clarity, and definitional coherence. The study begins by examining the classification dilemma surrounding crypto-assets under Indian securities law, particularly whether certain tokens could fall within the ambit of "securities" under Section 2(h) of the Securities Contracts (Regulation) Act, 1956. By comparing characteristics of cryptocurrencies to conventional financial instruments and referencing international legal benchmarks such as the Howey Test, the paper argues that many tokens exhibit sufficient investment features to warrant regulatory scrutiny by SEBI. In parallel, the RBI's approach, rooted in concerns over monetary stability, has largely treated cryptocurrencies as a threat to sovereign currency systems. Although the 2018 RBI circular attempted to isolate the financial system from crypto-related activities, the Supreme Court overturned the ban in 2020, underscoring the need for proportional regulation rather than prohibition. Meanwhile, the Indian government has taken significant steps under the PMLA by designating crypto intermediaries as "reporting entities," thereby mandating KYC, transaction monitoring, and suspicious activity reporting to the Financial Intelligence Unit-India (FIU-IND). While these moves align with global anti-money laundering standards, the application of PMLA to a fast-evolving digital sector presents both legal and practical challenges. A key argument advanced in this paper is the need for a dedicated regulatory authority—tentatively called the Digital Asset Regulatory Authority of India (DARA)—to oversee the crypto ecosystem holistically. The study highlights how SEBI and the Enforcement Directorate (ED) are already overburdened with their existing mandates, leading to delays, inefficiencies, and enforcement gaps. A specialised regulator could centralise policymaking, enforcement, and innovation facilitation, thereby addressing jurisdictional ambiguity and improving investor protection without stifling technological growth. this research concludes that the future of digital assets in India demands a balanced, innovation-friendly regulatory framework. For this, a pragmatic regulatory approach—combining institutional reform, international cooperation, and respect for crypto’s foundational features such as decentralisation and pseudonymity
Mohammed Ghouireg, Ayoub Toumi Lahreche, Oumelkheir Goug
This study aims to illuminate a recently emerged digital currency known as Bitcoin to dispel the ambiguity surrounding it and introduce it to the public.This will be achieved by defining its concept and characteristics and outlining the key differences between it and traditional currency.Furthermore, the study seeks to identify the methods of acquiring Bitcoin, the volume of its global transactions, the position of favourable legislation towards it, and the main practical challenges it faces.
Modern logistics monitoring solutions increasingly depend on the integration of IoT devices for real-time data collection, shipment tracking, goods and vehicle monitoring, and informed decision- making. However, current IoT-based logistics systems face significant challenges, including complex data management, limited interoperability among stakeholders, and inefficiencies resulting from centralized control mechanisms. Blockchain technology has emerged as a promising solution to address these critical issues within logistics and supply chain management. This paper presents a comparative analysis of traditional centralized logistics systems and blockchain-based decentralized solutions, emphasizing the evaluation of blockchain’s strengths such as transparency, immutability, and automated transaction execution via smart contracts and its weaknesses, particularly scalability limitations and implementation complexity. The research specifically examines how smart contracts can effectively manipulate IoT-generated data to automate logistical transactions and ensure secure, transparent data management. Through a structured analysis, this article identifies specific scenarios in logistics where blockchain technology adds significant value and discusses key practical considerations for its effective adoption. Additionally, this research critically evaluates Ethereum Virtual Machine (EVM)-based smart contracts and proposes AWS Hyperledger Fabric smart contract (chaincode) as a more scalable and cost- effective alternative for enterprise logistics applications. The study provides valuable insights and guidelines for logistics practitioners, facilitating informed decision-making about integrating blockchain solutions to enhance operational efficiency, trust, and interoperability within complex supply chain environments.
Cryptocurrency is an attribute derived from blockchain that serves the sole purpose of money exchange, similar to Bitcoin. Cryptocurrency can have major benefits but it could push the limits if it would be used for money laundering and terrorist finances since there is an absence of intermediate checks to ensure the transaction integrity and no one comes to know the identity of people who’ve made the transaction. This paper touches upon the meaning and definition of blockchain and cryptocurrency, a comparison of bitcoin and Ethereum, smart contracts, mining, advantages and drawbacks of cryptocurrency, Properties of blockchain, A study on (The bulk of bitcoins handled by the USA, and how google stops showcasing advertisements of bitcoin and cryptocurrency), Proposed suggestion and Scope for future study.
Purpose: This research analyzes the comparative risks, scalability, and adoption of decentralized finance (DeFi) versus centralized fintech solutions in the context of Saudi Arabia. It seeks to explain the models' acceptance and intended focus on the challenges and opportunities each model presents within the financial landscape of the Kingdom. Methodology: The research followed a survey-based design which fit the systematic collection of data to be analyzed quantitatively. Stratified random sampling was used to select a representative diverse demographic sample of 525 participants. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) which assessed the interplay between DeFi and centralized fintech platforms through perceived risks, scalability, and adoption factors. Findings: The results demonstrated that Centralized Fintech has a marked impact on fintech adoption in Saudi Arabia, noting importance of trust and regulation. DeFi did not have any appreciable impact on adoption. Perceived Trust and Security and Financial Literacy does not appear to mediate or moderate the relationship these models have with adoption suggesting stronger external influences, such as regulatory environment, drive change. Limitations/implications: The scope of this study is limited by Saudi Arabia’s context and the use of self-reported data. Other regions could be studied along with the undergoing regulatory change, along with socio-economic factors concerning fintech adoption. Originality/value: This research is unique in focusing on the comparative analysis of DeFi and Centralized Fintech in Saudi Arabia. It also serves as an information source for policymakers and fintech developers in formulating policies aimed at increasing the region’s fintech adoption.
This thesis investigates how technological innovation influences the valuation of cryptocurrencies, focusing on the top 50 DeFi tokens by market capitalization. To capture the multifaceted nature of blockchain innovation, I construct three distinct indicators: a Whitepaper Innovation Index based on word embedding and clustering techniques, a standardized Audit Security Score derived from rubric-guided evaluation of audit reports, and a Code Maturity Proxy based on GitHub fork counts. These metrics are combined with financial data from CoinMarketCap and project-level metadata including blockchain architecture classification, academic involvement, historical volatility, and token age. Cross-sectional regression analysis shows that the proposed innovation indicators—while theoretically meaningful—do not exhibit statistically significant relationships with either market capitalization or trading volume. Instead, token age emerges as the most robust and consistent predictor across specifications, indicating that investor behavior is more responsive to project longevity than to technical complexity. Historical volatility is also negatively associated with market capitalization, suggesting that market participants tend to penalize assets with unstable pricing histories. The results suggest that, within the current market landscape, signals of maturity and stability outweigh detailed technical disclosures in shaping investor perception. This study contributes to the empirical literature by introducing a structured, multi-dimensional framework for evaluating technological innovation in crypto assets and by shedding light on the behavioral cues that dominate pricing dynamics in decentralized finance.
The fastest growing and most widespread payment and investment tool in the world is virtual assets, including cryptocurrencies. The concept of electronic money, Ecash, first emerged in 1983, and in 1989, the first electronic payment tool, DigiCash, began to be used for micropayments in the United States. Since then, the cryptocurrency Bitcoin has emerged, and in just over a decade, it has become a cryptocurrency with a market value of 1.8 trillion US dollars, accounting for more than 60% of the global cryptocurrency market. Therefore, we aimed to study how to assess the value of cryptocurrencies in this market, and currently, there are few provisions on valuation methods in the International Valuation Standards and other legal documents. According to our research and imagination, the researcher believes that it is appropriate to use different approaches to measure the value of the asset depending on its type.
Nguyễn Mậu Bá Đăng, Nguyễn Khánh An, Ngô Thái Hưng
This study aims to identify the price spillover effects between decentralized finance (DeFi) and the stocks of Vietnamese commercial banks using a quantile spillover index model (τ) during the period 2018–2025. The results indicate that the connectedness between DeFi and commercial bank stocks is insignificant under stable market conditions (τ = 0.50), but becomes stronger during bearish (τ = 0.05) and bullish (τ = 0.95) market conditions. Notably, DeFi acts as a recipient of shock spillovers from commercial bank stocks across all three market conditions. Furthermore, the time-varying spillover analysis reveals that the connection between DeFi and commercial bank stocks intensifies during periods of high financial market volatility. These findings serve as an important source of information for investors and policymakers amid the ongoing digital transformation of Vietnam’s banking sector.
Najma Ali Soomro, Suresh Kumar Oad RAJPUT, Ishfaque Ahmed
Predictions regarding returns and price movements in financial markets can be made using online search engines, which track the sentiments of individual investors. This study aims to analyse how the sentiments of Bitcoin investors impact changes in the American stock market returns. The Bitcoin sentiment index was created to benchmark the sentiments of Bitcoin investors from 2013 to 2018. This index is built by analysing terms from leading business magazines and online journals. Such an index measures potential investors’ sentiments about Bitcoin and how those sentiments impact S&P returns. We use the ordinary least squares method to analyse this. It was found that BSI has a negative impact on S&P returns. Furthermore, the Vector Autoregressive (VAR) model is used to determine the relationship between these economic time series. VAR results indicated a significant positive impact of S&P returns on BSI, while BSI could not predict S&P returns. Consequently, it can be concluded that S&P returns cause changes in BSI. Recognising that Bitcoin sentiment can offer valuable insights and guidance for retail investors during market downturns, much like the S&P 500. By tracking changes in the S&P 500, analysts can anticipate shifts in cryptocurrency market sentiment and take preventative measures when needed. Understanding this relationship is crucial for assessing systemic risks, as volatility in traditional markets can impact the crypto space.
Reading the letter “Transforming Health Insurance in Bangladesh: A Future-Ready Approach” that was submitted in response to “The Urgent Need for Developing a Common Health Insurance Policy in Bangladesh: A Perspective” [1] inspired me to write this response, and I am grateful to the author(s) for their work. The author(s) makes a valid and necessary point about the need for a paradigm shift away from traditional state-led models and towards decentralized, technology-driven, behaviorally informed strategies. But while we're looking at the present situation, we must also recognize the government's current efforts and see how they could support or even lay the groundwork for a universal health insurance program that would benefit all citizens. The Health Ministry of Bangladesh has announced that the government has initiated a program to offer free medical treatment and medications to the population. The ministry has announced plans to implement 24-h health services at 500 centers and to distribute a healthcare card to each household under the “Shyastha Surokkha Karmasuchi” (SSK) package. This card enhances patient identification at hospital admission and optimizes the payment process by monitoring diagnostic information and service usage; however, it has not been fully implemented yet [2]. The government's efforts to improve healthcare access and quality are commendable, but they also bring attention to a basic problem. People with lower and medium incomes, as well as those working in the informal economy, are disproportionately impacted by the unequal distribution of resources caused by the tax-based approach that forms the basis of many of these programs. Several economic studies have pointed out that, in Bangladesh, many families continue to struggle financially since out-of-pocket costs make up around 68.5% of overall healthcare spending [3]. Despite the importance of programs like SSK that offer free services, this circumstance shows that these efforts do not solve the underlying problems with the healthcare funding system, which include structural disparities and financial instability. A shift toward a universal, all-encompassing health insurance system seems essential and advantageous in this light. A strong health insurance system might have two benefits: first, it would help those who can't pay for medical treatment get coverage, and second, it would provide a system for reliable, long-term financing. Germany, France, and Japan are only a few examples of the nations that have demonstrated that social-insurance models may achieve both universal coverage and fair allocation of resources through income-based premiums and required participation [4]. The difficulty for Bangladesh comes from trying to apply these models to our own social and economic situation. The large informal sector of the Bangladeshi economy, which has long been exempt from traditional tax and insurance systems, is a major obstacle to the widespread adoption of health insurance. We propose a multi-pronged strategy to address this. To begin, one way to guarantee affordability is through progressive premium systems, in which contributions change according to income levels. Premium payments from informal workers might be made easier with the use of innovative collecting techniques, such as community-based networks and mobile payment systems like “bKash” and “Nagad,” which would reduce administrative responsibilities [5]. Second, providing low-income groups with government subsidies is essential. The state may make sure that no one is left out because they don't have enough money by paying part of the premiums for those who are vulnerable. It is really essential for everyone to take part; to eliminate coverage gaps and deal with fluctuating participation rates, it is recommended to use a default opt-in method. This means that all citizens would be automatically registered in the health insurance program, and opting out would only be permitted under certain circumstances. Behavioral economics principles have been used successfully in other contexts to significantly boost enrollment using this method. The insurance system's risk pool and financial foundation may be further expanded if measures were to be considered that would promote the formalization of workers in the informal sector [5]. Integrating technology stands alongside these funding improvements as another pillar of a health insurance system prepared for the future. Claims processing using blockchain technology, for instance, has the potential to streamline administrative operations, make them more transparent, and cut down on fraud and settlement delays [6]. Furthermore, predictive underwriting algorithms have allowed for more precise and inexpensive premium changes in East African pilot programs using AI-driven adaptive pricing techniques [7]. Bangladesh can create a system that can handle large-scale operations while catering to people of varying income levels by adopting this state-of-the-art technology. Without the larger healthcare system, no health insurance system can possibly operate. While it is great that SSK and other government programs are working to make services more accessible, such as free prescription programs and 24/7 care centers, these efforts should be supplemented by steps to make sure healthcare resources are distributed fairly. When contrasted with metropolitan regions, rural communities still lack enough infrastructure and medical specialists. We can encourage fair allocation of resources with a single health insurance system that is built with targeted incentives and a tiered reimbursement mechanism. For instance, healthcare providers may be more motivated to offer high-quality services to rural communities if they were to get higher payment rates for institutions in underserved locations and participate in public-private partnerships. In conclusion, free healthcare programs are a huge step forward, but they also show how flawed a system that relies just on taxes to pay for healthcare may be. The solution to long-term, fair healthcare in Bangladesh lies in a universal health insurance system that is prepared for the future and can flexibly integrate public programs with creative private sector solutions. The healthcare system in Bangladesh may be revolutionized by adopting a hybrid model that incorporates digital technology, progressive premium collections, behavioral defaults, and mandated insurance. A more equitable and effective distribution of resources would be fostered by such a system, which would shield its inhabitants from ruinous medical bills. It is anticipated that these reflections will contribute to the ongoing conversation regarding the enhancement of healthcare financing in Bangladesh. An approach that is collaborative and integrates the benefits of state-driven initiatives with decentralized, technology-enabled, and socially equitable models is likely to facilitate long-term reform. S.M.R.D. conceptualized, supervised, and wrote the draft. The author has nothing to report. The author declares no conflicts of interest. The lead author SMRD affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained. Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
I am writing in response to “The Urgent Need for Developing a Common Health Insurance Policy in Bangladesh: A Perspective” [1]. The article effectively highlights the pressing need for a universal health insurance system in Bangladesh. However, it largely advocates for conventional solutions that have faced challenges in implementation across low- and middle-income countries. A paradigm shift is necessary—one that moves beyond traditional state-led models to explore decentralized, technology-driven, and behaviorally informed strategies tailored to Bangladesh's economic and social realities. Habib and Molla reports that out-of-pocket healthcare spending amounts to 68.5% of total healthcare costs in Bangladesh which causes financial difficulties for numerous citizens [2]. They suggest raising government funding while improving coverage through existing health programs. Using only state-funded initiatives fails to address the constraints that stem from both fiscal capacity and administrative efficiency issues. A better solution combines mandatory insurance with voluntary options through digital financial access while employing behavioral economics to boost participation rates. The scarcity of health insurance payments stems from people's distrust of financial institutions and their inability to see immediate advantages from coverage. Behavioral economics provides solutions through default enrollment models which require people to actively decline insurance coverage. Mobile banking platforms bKash and Nagad should integrate health insurance services through automatic micro-premium withdrawals which maintain user involvement while avoiding yearly payment requirements. Insurance communication becomes more effective through behavioral alignment when risk protection messages replace long-term health investment messaging. A new approach would be the implementation of health insurance models supported by diaspora communities. The annual remittance amount of over $22 billion in Bangladesh lacks an organized system to direct this money toward healthcare funding. Insurance plans that allow expatriates to pay insurance premiums for family members and support community-based risk funds would enhance healthcare coverage among vulnerable populations. The Philippines and Mexico together with other countries have established successful diaspora-backed healthcare insurance systems which reduced healthcare expenses paid directly by patients to millions of people [3, 4]. Technological integration is also crucial. The article correctly identifies healthcare financing problems yet fails to investigate blockchain-based claims automation and AI-based adaptive pricing solutions. Blockchain technology brings transparency to operations while reducing fraud and streamlines claim settlements through automation to establish system-wide trust [5]. AI-driven underwriting systems allow for risk-based premium adjustments which enables insurance affordability for different income groups according to Rix [6]. Proof-of-concept deployments in Rwanda and Kenya show that these innovations can scale up for emerging markets [7, 8]. Bangladesh needs to prevent implementing models from high-income countries because their economic and institutional structures differ too much from its own. The country needs to prioritize a combined method that includes public-private collaborations with technological enhancements and behavioral economic practices. The implementation of mobile-based microinsurance and remittance-backed financing and blockchain claims processing requires initial testing through pilot programs for framework scalability purposes. The absence of forward-thinking strategies makes universal health coverage efforts stay theoretical instead of becoming practical initiatives. MD. Faisal Ahmed: writing – review and editing, writing – original draft, conceptualization, methodology, investigation, validation, resources, data curation. The author declares no conflicts of interest. Data sharing not applicable to this article as no data sets were generated or analyzed during the current study. No new data were generated or analyzed in this study. All supporting information and references are publicly available as cited in the article.
As global energy markets undergo digitization and decentralization, multinational finance consortia increasingly rely on artificial intelligence (AI) to analyze geospatial and sensor data for investment modeling, risk assessment, and infrastructure optimization.However, cross-border data exchange poses significant privacy, security, and sovereignty concerns-particularly in energy-sensitive contexts where geospatial telemetry and environmental sensor networks contain critical operational intelligence.This paper advances a secure federated learning (FL) architecture tailored for multinational energy finance consortia, leveraging encrypted, AI-driven analytics to harmonize data utility and confidentiality.The proposed architecture integrates homomorphic encryption, differential privacy, and secure multi-party computation within a federated learning framework.It enables collaborative AI model training across sovereign entities and private stakeholders without transferring raw data, thus preserving jurisdictional control while enabling unified forecasting of energy supply, climate impact, and financial risk metrics.The paper details a tiered security model that accommodates variable data sensitivity levels-from satellite imagery and wind turbine telemetry to emission sensors and power grid diagnostics.Furthermore, the study presents a pipeline that processes heterogeneous datasets-such as LIDAR scans, thermal signatures, and remote sensor logs-using encrypted deep learning models capable of geospatial segmentation, anomaly detection, and predictive trend inference.Emphasis is placed on maintaining model accuracy in non-IID (non-independent and identically distributed) data scenarios, a common feature in distributed energy infrastructure.Policy implications are explored through case studies involving regional green bond issuance, multinational solar grid financing, and climate-resilience investments.The paper concludes with a governance blueprint for secure AI collaboration in energy finance ecosystems, balancing transparency, performance, and regulatory compliance.
This study employs clustering analysis to evaluate the efficiency of GPUs used in cryptocurrency mining, categorizing them into distinct groups based on computational output and power consumption. Using K-Means clustering, GPUs were grouped into three clusters: low-efficiency, moderate-efficiency, and high-efficiency. High-efficiency GPUs demonstrated superior hash rates (e.g., 104.79 Mh/s for AbelHash and 218.35 Mh/s for Autolykos2) despite higher power consumption, making them ideal for high-performance mining operations. Conversely, low-efficiency GPUs exhibited lower computational output and modest energy use, highlighting opportunities for hardware upgrades or repurposing. Visualization techniques, including scatter plots and pair plots, provided clear distinctions between clusters, while a silhouette score of 0.35 indicated moderate cluster separation, suggesting areas for further refinement. The findings offer actionable insights for optimizing hardware selection, reducing operational costs, and improving energy efficiency in mining operations. Additionally, this study underscores the importance of sustainability in cryptocurrency mining and provides a foundation for future research, including the integration of additional performance metrics, exploration of alternative clustering algorithms, and development of energy-efficient mining practices. These insights contribute to the broader goal of fostering a more sustainable and data-driven approach to cryptocurrency mining.
This study aims to develop a hybrid algorithm using the ARIMA model and LSTM-type recurrent neural networks to predict the closing prices of the cryptocurrencies BTC, LTC, and ETH. The methodology includes an exploratory data analysis, followed by the design, implementation, and evaluation of each individual algorithm as well as the combined hybrid algorithm. The results, after experimentation and evaluation of metrics on the test set, indicated that the ARIMA model was inefficient in predicting the closing prices of cryptocurrencies. On the other hand, the hybrid model for BTC showed significant statistical differences in the metrics, with MAE = $726.21 and MAPE = 1.75%, compared to the LSTM model, which achieved MAE = $729.35 and MAPE = 1.76%. These results indicate better performance from the hybrid model. Regarding the RMSE metric, the hybrid model scored 1157.47, while LSTM scored 1159.99; although statistically equivalent, the hybrid model was numerically better. For the remaining metrics and other cryptocurrencies, both methods were statistically equivalent. For five-day-ahead predictions, the hybrid algorithm continued to yield better results for LTC and ETH.
The subject of the research is the socio-economic relations arising from investment financing for small and medium enterprises (SMEs) and large businesses using digital financial assets (DFAs). The object of the research is the economy of Russia under conditions of limited investment and credit resources. The aim of the research is to create and utilize new innovative investment tools to support and develop the Russian economy. The digitalization of the Russian economy includes the active implementation of DFAs, which represent a new form of digital rights. DFAs play a crucial role in financing projects, attracting liquidity, optimizing payments, and structuring claims. This significantly changes traditional mechanisms of corporate and investment finance, making them more efficient and flexible. The methodological framework of the research is based on empirical and statistical analysis methods, synthesis, and systematization of information to identify new trends and best domestic practices in the formation and use of digital financial assets in the Russian Federation. The novelty of the research lies in the fact that digital financial assets act as one of the innovative tools of digital technologies, combining the properties of an investment solution and an intermediary in conducting settlements between economic entities. The issuance and circulation of digital assets is a new trend in the financial market. Digital assets are based on distributed ledger technology. They reduce the role of intermediaries and automate transactions through smart contracts. The main findings of the research indicate that the introduction of DFAs in small and medium businesses, as well as in large companies, improves access to capital and enhances the efficiency of financial processes. Under conditions of stringent restrictions and external pressure, DFAs become an alternative to traditional financing channels and a flexible tool for structuring transactions. However, the spread of DFAs faces significant obstacles, including incomplete and changing regulations, vulnerabilities in the cyber environment, a lack of secondary markets, and differences in infrastructure solutions. To overcome these limitations, it is necessary to develop measures for the standardization of the issuance and circulation of DFAs, ensure regulatory alignment, and provide technological support from the government, industry associations, and information system operators. This will reduce regulatory and operational uncertainty, increase investor confidence, and accelerate the development of the Russian DFA market.
As digital technologies increase interconnectivity among us, the need to safeguard our network infrastructure from sophisticated cyber threats has never been more important. This chapter provides a review of the modern cybersecurity technologies that seek to protect our networks. A discussion of strategic approaches for protecting networks, tools needed, and the future of technology in cyber- protection. It has considered traditional forms of cybersecurity protection (e.g., firewalls, intrusion detection systems; IDS) along with modern AI-driven cyber threat detection and response. We discuss predecessor and subsequent paradigms of cybersecurity protection, including, but not limited to, zero trust architecture, the continued monitoring of networks as an operational method, and distributed ledger technology using blockchain; blockchain solutions like smart contracts and protocols (e.g., Hyperledger). Examining the trends in the future of cybersecurity protections, and highlight some of those that include predictive analytics and automated remediation of malware threats via Automated Threat Remediation, threat intelligence sharing, and a collaborative approach to countering threats. In summary, this chapter reinforced the importance of a low-latency, adaptive, and multi-layered defense approach to evolved cyber threats, and highlighted the need for organizations to demonstrate compliance with global standards and regulatory frameworks.
Open access
Network Security and Intrusion Detection
Advanced Research in Systems and Signal Processing
The article examines the functional characteristics of centralized (CEX) and decentralized (DEX) cryptocurrency exchanges, which play a key role in the operation of the digital economy. The architectural, organizational, and technological aspects of various types of exchanges are analyzed, with their advantages and limitations identified in terms of usability, security, liquidity, regulatory compliance, and availability of trading instruments. It is noted that centralized exchanges offer high order execution speed, extensive functionality, integration with payment infrastructure, and user support. At the same time, they require identity verification, store assets in internal accounts, and are therefore subject to certain risks of centralized control. In contrast, decentralized exchanges operate on the basis of smart contracts, do not store user assets, and do not require KYC procedures, thus ensuring a high level of anonymity. However, DEX platforms are characterized by lower liquidity, a limited range of order types, and a higher requirement for users’ technical competence. The study presents a comparative analysis of trading volumes for key cryptocurrencies on Binance, Bybit, and Coinbase Exchange, as well as on decentralized platforms such as Uniswap, PancakeSwap, and Curve. The results reveal a significant lag in trading volume on DEX compared to centralized platforms. Among the analyzed cryptocurrencies, Ethereum demonstrates the highest daily trading volume on both centralized and decentralized exchanges. The study also focuses on user and asset security on cryptocurrency exchanges. It provides a detailed analysis of the use of two-factor authentication (2FA) mechanisms, customer identification procedures (KYC), and anti-money laundering and counter-terrorist financing (AML/CFT) policies. These tools are an integral part of the infrastructure of centralised exchanges that seek to comply with financial regulations and increase user trust. Based on the conducted analysis, the article outlines the prospects for the development of hybrid exchange models that combine the advantages of centralization and decentralization, and defines directions for further research aimed at enhancing the efficiency, security, and accessibility of digital trading platforms. Keywords: cryptocurrency exchange, centralised exchange, decentralised trading platform, digital security, KYC, DEX, CEX.
The development of technology is radically transforming all spheres of human life, including finance. As a result, new institutions are emerging, and existing ones are being modernized. Economic relations are increasingly shifting into the digital space, leading to transformation of traditional financial instruments. Money is losing its material forms and regulatory properties, giving way in the economy to alternative instruments. The sanctions imposed against Russia in recent years have significantly affected the country’s economic and financial systems. One of the most notable consequences has been the accelerated development of the cryptocurrency market. The paper addresses the issues of legalizing mining and cryptocurrency exchanges in Russia. The study is dedicated to examining the legal regime governing the circulation of cryptocurrencies, determining the place of digital currencies within the legal system of Russia and abroad, and identifying the risks associated with their circulation. The author analyzes the peculiarities of mining, the legal aspects of issuance and circulation of digital currencies, as well as the legal foundations for their use in international settlements. Attention is drawn to the limitations of legal regulation concerning relations in this sphere. The paper evaluates the current state and development prospects of the cryptocurrency sector in Russia and explores the role of the Government of the Russian Federation and the Central Bank of Russia in regulating this activity.