Graph theory has emerged as a foundational mathematical tool in the realms of cryptography and network security. Its ability to model complex relationships, systems, and interactions through vertices and edges enables innovative solutions for encryption, authentication, key distribution, intrusion detection, and secure routing. This research article provides a comprehensive review of recent advancements and applications of graph-theoretical techniques in cryptographic protocols and secure network systems.The study begins by outlining the theoretical underpinnings of graph theory relevant to secure communications, including graph isomorphism, expander graphs, Hamiltonian paths, and graph coloring. It then explores how graph-based methods are utilized in modern cryptographic systems such as zero-knowledge proofs, public-key cryptography, and lightweight encryption schemes. The article also discusses graph-theoretic approaches in blockchain consensus models, attack graph analysis, intrusion detection systems (IDS), and secure routing in wireless sensor networks (WSNs).Recent advancements such as post-quantum cryptography based on hard graph problems, dynamic attack graphs in adaptive security systems, and trust graphs in distributed environments are highlighted. Data from peer-reviewed publications from 2010 to 2025 are synthesized, and key trends are visualized through tables, graphs, and diagrams. The paper also identifies existing challenges, including scalability, computational complexity, and graph-theoretical attack vectors.The discussion critically interprets these findings, connects them to existing literature, and proposes directions for future research, including graph-based AI models for threat prediction and hypergraph frameworks for modeling higher-order trust relationships.Overall, this study offers an integrated perspective on how graph theory continues to transform the cryptographic and security landscape, contributing to the development of resilient, efficient, and scalable secure systems.
Cryptocurrency is a digital payment system that doesn't rely on banks to verify transactions. It's a peer-topeer system that can enable anyone anywhere to send and receive payments. Instead of being physical money carried around and exchanged in the real world, cryptocurrency payments exist purely as digital entries to an online database describing specific transactions. When you transfer cryptocurrency funds, the transactions are recorded in a public ledger. Cryptocurrency is stored in digital wallets. Cryptocurrency received its name because it uses encryption to verify transactions. This means advanced coding is involved in storing and trans
This project aims to create an all-in-one decentralized platform that combines NFT minting, an NFT marketplace, and a crypto exchange. Users can easily mint and tokenize digital assets, trade NFTs in a secure and user-friendly marketplace, and exchange cryptocurrencies seamlessly. The platform will feature cross-chain compatibility, smart contracts, and robust security measures to ensure transparency and trust. By empowering creators, collectors, and traders, this ecosystem bridges the gap between blockchain innovation and mainstream adoption, fostering a sustainable and inclusive digital economy.
This paper empirically investigates the determinants and performance implications of capital structure for two dominant Indian conglomerates, Reliance Industries Limited (RIL) and the diversified Tata Group, utilizing annual data spanning the critical 2011–2021 period. The study addresses the ambiguity regarding optimal financing choices in large emerging market firms, focusing on the contrasting centralized, capital-intensive structure of RIL versus the industry-aligned, decentralized financing strategies of major Tata subsidiaries (TCS, Tata Steel, Tata Motors). A dynamic panel data approach, utilizing the System Generalized Method of Moments (Sys-GMM), is employed across the 11-year period to address issues of endogeneity, unobserved firm heterogeneity, and, critically, to accurately estimate the speed of leverage adjustment, given the observed persistence of financing decisions. The results confirm a dual-theory application dictated by corporate strategy and industry alignment. RIL’s financing choices, particularly its aggressive leveraging followed by deleveraging toward zero net debt by 2021, are predominantly explained by the Pecking Order Theory (POT), where high profitability negatively predicts reliance on external debt. Conversely, the Tata Group’s sub-entities strongly align with the Trade-Off Theory (TOT), with asset tangibility significantly dictating debt capacity (e.g., high debt for Tata Steel vs. minimal debt for TCS). Crucially, the analysis confirms that leverage generally showed a significant negative impact on RIL’s operational performance [Return on Assets (ROA) and Return on Equity (ROE)], validating its strategic shift towards an equity-heavy model. The findings underscore the critical role of strategic corporate philosophy (centralized flexibility versus decentralized industry alignment) in shaping capital structure efficiency and shareholder value creation within complex conglomerates.
Open access
Working Capital and Financial Performance
Innovations and Analysis in Business and Education
Decentralized finance (DeFi) is an emerging financial technology based on secure distributed ledgers similar to those used by cryptocurrencies. In the U.S., the Federal Reserve and Securities and Exchange Commission (SEC), likewise in India we have RBI that define the rules for centralized financial institutions like banks and brokerages, which consumers relyonto access capital and financial services directly. DeFi challenges this centralized financial system by empowering individuals with peer-to-peer digital exchanges. DeFi eliminates the fees that banks and other financial companies charge for using their services. Individual shold money in a secure digital wallet, can transfer funds in minutes, and anyone with an internet connection can use Defi.
Mohammad Nasrinasrabadi, Maryam A. Hejazi, Ehsan Chaharmahali, Mousa Hussein
The integration of blockchain and the Internet of Things (IoT) within smart grids offers transformative potential for enhancing energy management, security, and operational efficiency. Smart grids rely on advanced digital technologies to enable bidirectional communication between energy producers and consumers, optimizing the integration of renewable energy sources and promoting demand-side management. Blockchain technology, with its decentralized and immutable nature, ensures secure and transparent energy transactions while fostering trust without the need for centralized authorities. Meanwhile, IoT facilitates real-time data collection and monitoring, enabling dynamic energy management and transactive energy systems. This review explores the synergies between blockchain and IoT in addressing critical challenges such as cybersecurity, data security, and network security. By leveraging mechanisms like smart contracts and consensus algorithms, these technologies enhance grid resilience and privacy, providing robust solutions to manage distributed energy resources and decentralized energy markets. The integration also supports peer-to-peer energy trading, improves scalability, and reduces reliance on intermediaries, aligning with sustainability goals by promoting renewable energy adoption. Despite significant advancements, challenges such as regulatory barriers, high computational costs, and scalability limitations persist. This paper emphasizes the need for innovative approaches to overcome these issues and highlights emerging trends such as hybrid blockchain models and AI-enabled solutions. By addressing these gaps, blockchain and IoT can redefine smart grid infrastructures, ensuring a secure, efficient, and sustainable energy future.
This current study explores the intention to adopt cryptocurrencies (IACR) within the Arab world. The study is founded on the diffusion of innovation theory and examines the relationship through the mediation of digital technostress and the moderation of ethical issues and government regulations. The study employed a quantitative approach and gathered cross-sectional data from 437 respondents through an online survey. Subsequently, structural equation modeling (SEM) was utilized to test hypotheses. The findings indicated that digital technostress acts as a mediating factor in the relationship between variables such as complexity, observability, compatibility, and the intention to adopt cryptocurrency, while no mediating effect was observed between relative advantage and trialability and the intention to adopt cryptocurrency through digital technostress. Furthermore, the study confirmed the moderating role of ethical issues in the relationship between digital technostress and the intention to adopt cryptocurrency. However, no moderating effects of government regulations on cryptocurrency adoption among Arab investors were identified. Findings highlight the importance of fostering supportive regulatory environments for cryptocurrency investment in the Arab world and affirm the applicability of the diffusion of innovation theory in the context of blockchain and cryptography. Empirical evidence emphasizes the need for further longitudinal investigations in global regions.
• “Incentive-regulatory” policy synergy promotes energy transition but falls short of “1 + 1 > 2” expectations. • policy synergy’s marginal effect is lower than standalone incentive policy due to institutional conflicts. • Transmission mechanisms (industrial/financial/cognitive) exhibit significant attenuation under policy synergy. • policy synergy effectiveness hinges on city attributes: stronger in high-capacity, non-resource-dependent cities. • Top-down institutional integration is critical to resolve “instrumental tension” in multi-policy governance. Accelerating the energy transition (ET) is essential for achieving climate goals, yet the effectiveness of combining multiple policy instruments remains uncertain. This study investigates the synergistic effects of China’s New Energy Demonstration Cities (incentive policy) and Key Air Pollution Control Zones (regulatory policy) on urban ET from 2011 to 2021. A multidimensional ET index is constructed under the “energy trilemma” framework, and a double machine learning approach is employed to identify causal impacts and mediating mechanisms. The results show that: (1) policy synergy significantly promotes ET, but its marginal effect is lower than that of the incentive policy alone, failing to achieve the expected “1 + 1 > 2” outcome; (2) Heterogeneity analysis reveals that the synergy effect is more pronounced in cities with stronger economic foundations, higher fiscal decentralization, non-resource dependency, and non-old industrial base status, highlighting the role of local institutional carrying capacity; (3) Mechanism analysis further indicates that synergy promotes ET mainly through industrial upgrading, green finance, and public environmental awareness, but all pathways suffer from transmission attenuation. These findings underscore the challenges of fragmented governance in multi-policy environments and suggest that effective energy transition requires stronger institutional integration, clearer policy signals, and enhanced local implementation capacity.
Andrei-Theodor Ginavar, Alexandra Conda, Daniel Traian Pele, Miruna Mazurencu-Marinescu-Pele · 5 authors
Abstract This study examines the statistical characteristics of Bitcoin and the CRIX index through a dual analytical framework: Metcalfe’s network law and bubble dynamics via Log-Periodic Power Law (LPPL) modeling. The findings suggest that, over the medium to long term, Metcalfe’s law—which posits that a network’s value scales with the square of its user base—serves as a valid approach for assessing cryptocurrency value. However, its applicability to Bitcoin in the short term remains uncertain. To analyse price dynamics during speculative bubbles, the DS LPPLS method was employed, enabling the identification of bubble phases and the estimation of potential regime shifts. Ultimately, the research concludes that while Metcalfe’s law holds true over longer time horizons, its reliability in short-term scenarios and under varying data regimes is considerably questionable.
Medical waste management has grave issues concerning traceability, regulatory, and the environment. The traditional systems which are centered on manual record-keeping and the usage of centralized databases usually lead to data loss and unauthorized disposal along with inefficiencies. In this paper, the researcher comes up with a blockchain-integrated medical waste management system to support Internet of Things (IoT)-driven technologies and smart contracts to streamline a safe, autonomous, and anti-tampering system of waste handling. Smart bins enabled with IoT and fitted with GPS, ultrasonic and weight sensors collect live data regarding waste creation and conveyance and this information is transferred or relayed through Wi-Fi/LoRaWAN to the edge/cloud gateways. This data is stored in a protected manner, verified on a permissioned blockchain and, most importantly, the most important tasks, such as scheduling a pickup and approving disposal are done within smart contracts. Experiment findings show 100 percent traceability accuracy, a 30 percent less time in disposal, and a 90 percent better regulatory compliance. The proposed framework will have three new contributions as compared to the existing systems, augmenting the route validation algorithm with a live tracking device in the form of GPS to detect and prevent deviation, a neural network-based model to pre-validate transactions and prevent fraud, and an optimization layer within the smart contract that will support the energy cost to ensure scalability of the proposed framework. The said features altogether allow smart, anticipatory, and regulation-conformant waste processing, which makes this work stand out of existing methods.
The global financial ecosystem is undergoing a profound transformation driven by the convergence of Environmental, Social, and Governance (ESG) imperatives, Artificial Intelligence (AI) capabilities, and Financial Technology (FinTech) innovations. This paper explores the synergistic nexus among these three forces and articulates how their intersection is reframing the trajectory of sustainable finance. By integrating ESG objectives with AI-powered intelligence and FinTech-driven efficiency, the study demonstrates how financial systems can evolve from traditional, compliance-based models to adaptive, data-driven, and ethically informed architectures that promote long-term sustainability and inclusiveness. Using a multidisciplinary research framework, the paper examines the mutual reinforcement between sustainability principles, technological innovation, and digital finance mechanisms. It assesses how AI enhances ESG data management through advanced analytics, natural language processing, and machine learning algorithms that can measure, predict, and optimize sustainability outcomes. These technologies improve data transparency, reliability, and comparability, addressing one of the core challenges of ESG evaluation and reporting. In parallel, FinTech platforms like spanning blockchain, decentralized finance (DeFi), green digital bonds, and peer-to-peer investment systems-enable traceable and democratized financial flows that embed sustainability values at the transaction level.The study proposes a novel conceptual model, the “Sustainable Intelligence Framework (SIF)”, which delineates how ESG indicators, AI insights, and FinTech mechanisms interact within a dynamic feedback system. The SIF illustrates that when these domains operate synergistically, they not only enhance decision-making efficiency but also generate compounded social, environmental, and economic value. Through case studies of emerging economies and advanced markets, the research uncovers practical applications, regulatory considerations, and ethical implications of the ESG‑AI‑FinTech triad. The analysis further highlights how AI-driven FinTech can facilitate green credit scoring, impact investment assessment, and automated sustainability auditing, while blockchain ensures trust, traceability, and reduced information asymmetry across value chains. The findings affirm that the integration of ESG, AI, and FinTech is not merely convergent but transformative in creating a synergistic ecosystem that can accelerate the transition toward a sustainable, transparent, and equitable financial future. This synergy also redefines risk management and governance paradigms, positioning sustainability as a strategic driver rather than a regulatory constraint. The paper concludes by emphasizing that the ESG‑AI‑FinTech nexus represents the next frontier in sustainable finance, offering a blueprint for policymakers, institutions, and innovators to harmonize profitability with planetary and social well-being.
This study examines the market impact of China's comprehensive cryptocurrency ban announced in May 2021, employing an event study methodology. The investigation is motivated by the need to understand how major regulatory interventions affect cryptocurrency markets, given their growing significance in the global financial ecosystem. Using daily price data for Bitcoin and Ethereum, we analyze abnormal returns (AR) and cumulative abnormal returns (CAR) around the announcement date. The analysis reveals significant negative market reactions, with Bitcoin experiencing a CAR of -70% and Ethereum -87% during the 30-day post-event window. Our findings suggest that this ban had a more severe and persistent impact compared to previous regulatory actions, reflecting the market's heightened sensitivity to comprehensive regulatory measures. The results demonstrate the substantial influence of major regulatory interventions on cryptocurrency market stability and provide important implications for policymakers considering cryptocurrency regulations. Furthermore, the study highlights how regulatory actions in one jurisdiction can generate significant spillover effects across global financial markets.
Maksym Ivasenko, Сергій Михайлович Фролов, Mykhaylo Heyenko, Nataliia Kolodnenko · 5 authors
This article highlights the results of a study investigating whether the growth of syndicated loan activity among US commercial banks was driven by measurable operational cost savings through blockchain-powered back-office automation. Quarterly data from Q1 2010 to Q4 2024 on syndicated loan stocks, commercial and industrial loans, real GDP, bank assets, and non-interest expenses were obtained from the Federal Reserve System’s FRED database. A dummy variable was applied after 2016 to denote the implementation of the first production-level Distributed Ledger Technology (DLT) pilots. Using the Autoregressive Distributed Lag Model (ARDL) bounds testing approach, evidence of cointegration is found and long-run elasticity is estimated: a steady 1% increase in the volume of syndicated loans reduces the operating expense ratio by 0.147%, which means that almost doubling the volume of loans in the resulting sample leads to approximately 15% structural reduction in the burden on banks’ back offices. The associated error correction model gives a short-run elasticity of –0.276 (i.e., a 1% quarterly shock to loan volume reduces expenses by 0.276 p.p.) and a 47% correction rate to a new equilibrium. Diagnostic tests confirm the absence of sequential correlation and resistance to heteroscedasticity by White’s standard errors. System-wide process improvements were evaluated by examining Hyperledger Fabric’s permissioned channel blockchain, smart contract automation, and multi-signature approval policies, which together simplify Know Your Customer (KYC) document workflows and settlement processes. The findings provide empirical evidence that enterprise DLT platforms deliver significant cost reductions for syndicated loan transactions, with implications for bank, fintech, and regulatory strategies.
Abstract In the context of MiCAR implementation, we propose a simple and effective approach that national competent authorities can use in their supervisory role to detect potential market manipulation. Our method is based on Benford’s Law as a quantitative tool to assess the conformity of crypto-asset transactions with expected numerical distributions, helping supervisors identify anomalies that may indicate market manipulation. From a practical perspective, we have evaluated the conformity of various cryptocurrency trading pairs with Benford’s Law by applying two well-established metrics: Mean Absolute Deviation and Sum of Squared Deviations. These metrics were used to assess how closely each pair’s transaction distribution aligns with the theoretical expectations of Benford’s Law, using literature-recommended thresholds as a benchmark. The analysis highlights a distinct separation between the transaction patterns of major cryptocurrencies paired with fiat currencies and those of less established or more volatile assets. BTC, ETH, and even LUNA exhibit strong conformity with Benford’s Law, suggesting greater market stability, transparency, and organic trading behavior, while exotic pairs and assets like DOT deviate significantly, pointing to potential irregularities, inefficiencies, or unique market characteristics. Such deviations can sometimes be associated with market manipulation, wash trading, or other fraudulent activities commonly observed in less regulated, lower-liquidity, or highly speculative markets. These findings highlight the potential of Benford’s Law as a diagnostic tool for detecting abnormal transaction patterns, identifying markets susceptible to manipulation, and improving overall market surveillance and security. Our study contributes to a deeper understanding of cryptocurrency market dynamics and offers a foundation for further research into fraud detection, regulatory oversight, and market integrity within the rapidly evolving cryptocurrency environment.
Abstract The approval of Bitcoin ETFs by the Securities and Exchange Commission (SEC) on 01/11/2024 was an essential event for both the cryptocurrency market and the traditional financial system. Bitcoin ETFs work as a bridge between digital assets and traditional financial instruments, contributing to increased liquidity and attracting new institutional investors who were reluctant before due to regulatory and security concerns. This study assesses the impact of the approval of Bitcoin ETFs on the stability of the financial system, focusing on the correlations and the volatility spillover effects of Bitcoin and three major financial indices (S&P 500, Dow Jones Industrial Average, and Nasdaq-100). Using Pearson Correlation, Time-Varying Parameter Vector Autoregression (TVP-VAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, this research offers a comprehensive analysis of the influence of Bitcoin on the dynamics of market. The results show that, although the correlations between Bitcoin and stock market indices reached a peak in 2021, they dropped later, suggesting a gradual decoupling from traditional financial markets. However, after the launch of Bitcoin ETFs in 2024, the correlations with financial indices – especially with S&P 500 – started to rise again, suggesting a reintegration of Bitcoin into the traditional financial system. Contrary to initial expectations, the results obtained from data covering 90 days before and after the launch of Bitcoin ETFs don’t show a significant increase in short-term correlations, which suggest a smooth adaptation of the market to these new financial instruments. In addition, although Bitcoin ETFs contribute to the stabilization of cryptocurrency volatility, they introduced new types of intra-day fluctuations, highlighting the need for an advanced strategy of risk management. The study concludes that, while Bitcoin ETFs contribute to the stability of financial markets, they introduce systemic risks which require continuous surveillance from the regulatory authorities. Long-term implications of the approval of Bitcoin ETFs remain uncertain, hence more research is needed in order to comprehensively assess the impact of these new financial instruments on the global financial stability.
The widespread adoption of Artificial Intelligence (AI) has led to transformative advancements across industries such as healthcare, finance, supply chain, and smart governance.However, conventional AI systems are largely centralized, relying on siloed datasets and proprietary models controlled by a few entities.This centralized structure creates significant vulnerabilities, including data breaches, lack of transparency in decision-making, limited user control, and potential biases embedded within opaque algorithms.To address these limitations, this research investigates the integration of blockchain technology as a foundation for building decentralized intelligence.Blockchain, with its core properties of immutability, decentralization, and transparency, offers a compelling alternative to traditional AI deployment models.In this paper, we explore how blockchain can empower AI by decentralizing model training and data access, enabling tamper-proof audit trails, and fostering collaborative intelligence through smart contracts and distributed consensus mechanisms.Specific use cases such as decentralized federated learning, tokenized data marketplaces, and blockchain-governed AI agents are analyzed to illustrate practical implementations.We also examine the technical and ethical considerations of this convergence, including issues of scalability, interoperability, computational overhead, and regulatory compliance.Through a comprehensive review and conceptual framework, this paper contributes to the growing discourse on trustworthy and democratized AI, positioning blockchain as a key enabler of the next generation of secure, ethical, and transparent intelligent systems.
Abderahman Rejeb, Karim Rejeb, Heba F. Zaher, Steve Simske
This paper explores the intersection of blockchain technology and smart cities to support the transition toward decentralized, secure, and sustainable urban systems. Drawing on co-word analysis and BERTopic modeling applied to the literature published between 2016 and 2025, this study maps the thematic and technological evolution of blockchain in urban environments. The co-word analysis reveals blockchain’s foundational role in enabling secure and interoperable infrastructures, particularly through its integration with IoT, edge computing, and smart contracts. These systems underpin critical urban services such as transportation, healthcare, energy trading, and waste management by enhancing data privacy, authentication, and system resilience. The application of BERTopic modeling further uncovers a shift from general technological exploration to more specialized and sector-specific applications. These include real-time mobility systems, decentralized healthcare platforms, peer-to-peer energy exchanges, and blockchain-enabled drone coordination. The results demonstrate that blockchain increasingly supports cross-sectoral innovation, enabling transparency, trust, and circular flows in urban systems. Overall, the current study identifies blockchain as both a technological backbone and an ethical infrastructure for smart cities that supports secure, adaptive, and sustainable urban development.
Siang-Li Jheng, Alexandra Conda, Daniel Traian Pele, Wolfgang Karl Härdle
Abstract 2024 marks a significant milestone in integrating digital finance into the global financial landscape. The U.S. Securities and Exchange Commission’s approval of Bitcoin and Ethereum ETFs signaled wider mainstream adoption. Shortly thereafter, Donald Trump’s return to the presidency drove Bitcoin prices beyond $100,000. In light of these developments, we observe the rapid changes in cryptocurrency market prices, trends, and regulatory policies, which drive us to conduct a comprehensive review of cryptocurrencies asset’s literature and examine its robustness. Our study covers several themes: how cryptocurrencies fit into broader asset allocation strategies, techniques to create crypto-based indexes, current debates over speculative bubbles, and the evolution of valuation models to highlight the dual aspects of market opportunities and risks. Throughout our review, we compare previous studies with the latest data, seeking to determine which arguments continue to hold up and which require adjustment. Although digital assets have experienced multiple crashes, they often rebound more strongly than expected, making them a topic of intense debate among academics, regulators, and investors. We aim to assemble an organized summary of research findings, providing a comprehensive framework that unites historical evolution with recent shifts and future perspectives.
The rise of decentralized exchanges (DEXs) heralds a paradigmatic shift in financial trading—from reliance on centralized intermediaries to peer‑to‑peer, trustless systems undergirded by blockchain and smart contracts. This article explores global trends in DEX innovation, the growth of decentralized finance (DeFi), and the evolving role of DEXs in reshaping capital markets. It also analyzes India’s adoption trajectory, regulatory context, and early indicators from Tamil Nadu, including blockchain governance initiatives and nascent fintech activity. Simulated and reported data are integrated to provide projections and policy implications.
Hanen Ben Ameur, Fouad Jamaani, Mohammed N. Abu-Alfoul
This study investigates the co-movements between prominent financial assets-crude oil, natural gas, gold, and Bitcoin-and uncertainty indices, including the Infectious Disease Equity Market Volatility Tracker (IDEMV) and the Geopolitical Risk Index (GPR), from January 2017 to January 2023. By employing advanced wavelet techniques-Wavelet Power Spectrum (WPS), Bi-Wavelet Coherence (WCA), Multiple Wavelet Coherence (MWC), and Partial Wavelet Coherence (PWC)-we analyze their time- and frequency-dependent responses to market shocks. The results reveal that Bitcoin and WTI exhibit time-varying sensitivity to IDEMV, particularly at short- and medium-term frequencies, highlighting their vulnerability to health-related crises like COVID-19. In contrast, gold and natural gas respond more strongly to GPR, with gold demonstrating a long-term leading role during geopolitical uncertainties, while Bitcoin and WTI lead in health-related shocks. The Russia-Ukraine conflict further amplified GPR's impact on Bitcoin and increased natural gas's vulnerability to geopolitical disruptions. These findings underscore the need for tailored strategies to address health and geopolitical risks. Policymakers should enhance crisis-response frameworks for Bitcoin and crude oil, while investors can reduce uncertainty by diversifying portfolios with resilient assets like gold and natural gas.
This study delves into the vulnerability of the smart grid to infiltration by hackers and proposes methods to safeguard it by leveraging blockchain and artificial intelligence (AI). A categorization and analysis of cyberattacks against smart grids will be conducted, focusing on those targeting their communication layers. The main goal of the work is to address the challenges in this area by implementing novel detection and defense strategies. The authors categorize attacks on smart grid networks based on the communication classes they want to compromise. They propose novel taxonomies specifically designed to detect and implement defense strategies. The study investigates artificial intelligence and blockchain techniques to identify cyber-attacks that employ deceptive data injection. The study indicates that cyberattacks against smart grids are increasing in frequency and complexity. The paper proposes innovative strategies for defense, such as enhancing cybersecurity with artificial intelligence and blockchain technology. The research further enumerates several challenges, such as counterfeit topological data, imprecise data identification, and combining big data with blockchain technology. Given the increasing risks, the study emphasizes the crucial need for robust cybersecurity safeguards in smart grids. This work contributes to the protection of smart grid infrastructures by categorizing attacks, suggesting novel defenses, and exploring solutions integrating artificial intelligence and blockchain technology. Research should prioritize enhancing technology to maximize security and counter emerging attack methods. The intended audience of our paper comprises graduate-level academics and independent researchers.
Cristina Dima, Răzvan Cătălin Dobrea, Mădălina Ioana Moncea, Eduard Laurentiu Ion
Abstract For a long time, among the most controversial topics revolves around technology, which encompasses the financial landscape and changes the way we perceive and interact with money. The cause of this transformation is cryptocurrency - a revolutionary innovation that has captured the imagination of individuals and institutions around the world. For the less informed, investing in cryptocurrencies may seem like a game of chance, while for the younger ones, it represents a promising source of income for the future. The reasons for choosing the theme about cryptocurrencies can be motivated by several current factors such as: the topicality and relevance of cryptocurrencies, technological innovation, financial opportunities, regulations and public policies, social and cultural impact, but the main reason is the monetary future, which can become a significant part of the global monetary system.
This study examines how local government policy contributes to the effectiveness of zakat revenue collection, focusing on the case of BAZNAS in Serang Regency, Indonesia. Zakat, an Islamic fiscal obligation, serves not only as an act of worship but also as a mechanism for socio-economic redistribution. Despite its potential, zakat collection in many regions remains suboptimal due to fragmented policies and weak institutional synergy. This research addresses a critical gap in global Islamic finance literature by investigating zakat governance at the subnational level, especially in a decentralized administrative context. Using a qualitative method that includes document analysis and semi-structured interviews with key stakeholders, the study explores how formal regulations, government facilitation, and inter-agency coordination shape institutional performance. The findings reveal that local policies—such as mandatory zakat deductions for civil servants, operational support, and integration of zakat into regional development planning—significantly enhance zakat income and institutional legitimacy. However, challenges such as limited bureaucratic capacity, inconsistent implementation, and fragmented institutional roles hinder optimal performance. The study concludes that effective zakat governance requires not only normative alignment with Islamic values but also robust policy design, administrative professionalism, and participatory mechanisms. By bridging institutional theory and Islamic public finance, this study offers a contextualized model of state–faith institutional synergy that may be applied to other Muslim-majority countries or regions with similar governance dynamics.
Aiming at the critical challenges of fragmented environmental-economic value tracking and inefficient multi-stakeholder coordination in green electricity trading, this study proposes a blockchain-based collaborative management method integrating environmental attributes (e.g., carbon offsets) with economic transactions. Leveraging blockchain’s decentralized, tamper-proof distributed ledger, the method ensures transaction transparency, automates settlement via smart contracts, and establishes a verifiable audit trail for environmental benefits. Experimental comparisons demonstrate that the blockchain platform reduces transaction costs by 30%, shortens settlement time by 75%, and significantly enhances market liquidity and transparency versus traditional modes. This approach optimizes resource allocation, minimizes intermediary dependencies, and provides a robust technical pathway for scaling green power adoption. Key implementation barriers include blockchain’s energy consumption, smart contract vulnerabilities, and regulatory fragmentation across jurisdictions. Future work will focus on enhancing blockchain energy efficiency and developing cross-regional regulatory frameworks for green power markets.