Old economy banking infrastructure systematically bars billions of people across the globe from fundamental financial services by way of insurmountable documentation barriers, exorbitant fee systems, and geographic reach that disproportionately affect developing economy populations. Local currency instability and hyperinflation further enhance these problems by decimating savings and buying capacity, locking communities in vicious cycles of economic instability. Blockchain and decentralized financial protocols appear as revolutionary solutions that democratize access to finance using only internet connectivity, removing intermediaries and institutional gatekeeping systems. Dollar-pegged stablecoins bring much-needed stability to volatility in currencies without sacrificing the accessibility advantages of distributed ledger infrastructure. Decentralized lending protocols produce legitimate returns by linking borrowers and lenders via algorithmic interest rate models, which are transparently operated without central decision-making power. Self-custody wallets function as complete pseudo-bank debts supplying global attain and continuous accessibility, allowing customers to keep, transmit, and hold digital property without requiring institutional approval or extensive documentation. Clever contracts execute mechanically primarily based on predetermined conditions, disposing of human intermediaries at the same time as ensuring transparency via immutable public blockchain information. Revolutionary regulatory frameworks establish sandbox environments that facilitate controlled experimentation with blockchain-based economic services, enabling innovation even as preserving customer protection requirements. Mobile-first user experience design with support for local languages answers the specific needs of developing market populations relying solely on internet access via mobile devices. Intersecting these technological advancements makes financially independent ecosystems possible for serving previously excluded communities through yield-producing instruments and barrier-free cross-border payment capabilities.
Public finance transparency has become central to economic modernisation, fiscal accountability, and anti-corruption reform in transitional economies. With the emergence of distributed ledger technologies (DLTs), blockchain systems have been increasingly explored as instruments to improve auditability, reduce information asymmetry, and strengthen institutional trust between state, business, and society. This article develops a comparative analysis of blockchain adoption in public finance across four transitional or post-socialist economies: Uzbekistan, Estonia, Georgia, and Kazakhstan. Drawing on political economy frameworks, digital governance studies, and blockchain technical literature, it examines the potential and constraints of distributed ledger innovation in procurement, budgeting, treasury operations, registries, and asset disclosure systems. The analysis shows that blockchain adoption is not solely a technological issue but an institutional one, shaped by state capacity, bureaucratic incentives, regulatory ecosystems, and pre-existing digital infrastructure. While Estonia demonstrates advanced institutional integration of blockchain-based infrastructure, Georgia and Kazakhstan illustrate intermediate pathways of digital governance with selective blockchain pilots, and Uzbekistan represents an emerging adopter with rapid digital modernisation but slow blockchain deployment in fiscal functions. The article concludes that blockchain-based transparency reforms in transitional economies require a coordinated approach linking governance, data interoperability, legal reform, and administrative incentives rather than technology alone.
Multi-agent systems face a fundamental coordination problem: agents must coordinate despite heterogeneous preferences, asymmetric stakes, and imperfect information. When coordination fails, friction emerges—measurable resistance manifesting as deadlock, thrashing, communication overhead, or outright conflict. This paper derives a formal framework for analyzing coordination friction from a single axiom: actions affecting agents require authorization from those agents in proportion to stakes. From this axiom of consent, we establish the kernel triple (alpha, sigma, epsilon)—alignment, stake, and entropy—as candidate sufficient statistics for any resource-allocation configuration. We propose a friction functional whose comparative statics encode three structural predictions: friction increases in stakes, increases in entropy, and decreases in alignment. The Replicator-Optimization Mechanism governs evolutionary selection over coordination strategies: configurations generating less friction persist longer, establishing consent-respecting arrangements as dynamical attractors rather than normative ideals. We develop formal definitions for resource consent, coordination legitimacy, and friction-aware allocation, plus machine-checked Lean 4 proofs of the core comparative-statics. Illustrative applications to cryptocurrency governance and political legitimacy show the same architecture spanning domains. v3.0.0 (2026-07-11): Matches arXiv v3 (94pp). The MARL empirical appendix has been split out into a standalone companion paper; total-variation legitimacy remark added (proved), reconciling the level-form dynamics with the total-variation measurement form; α-domain fixes; hedging pass throughout.
Xinyu Hou, Yang Lu, Rabimba Karanjai, Lei Xu · 5 authors
Ransomware is still one of the most serious cybersecurity threats. Victims often pay but fail to regain access to their data, while also facing the danger of losing data privacy. These uncertainties heavily shape the attacker-victim dynamics in decision-making. In this paper, we introduce and analyze zkRansomware. This new ransomware model integrates zero-knowledge proofs to enable verifiable data recovery and uses smart contracts to enforce multi-round payments while mitigating the risk of data disclosure and privacy loss. We show that zkRansomware is technically feasible using existing cryptographic and blockchain tools and, perhaps counterintuitively, can align incentives between the attacker and the victim. Finally, we develop a theoretical decision-making framework for zkRansomware that distinguishes it from known ransomware decision models and discusses its implications for ransomware risk analysis and response decision support.
Guma Ali, Otim Emmanuel, Maad M. Mijwil, Bosco Apparatus Buruga · 6 authors
The rapid digitalization of financial services has given rise to smart finance ecosystems that integrate FinTech platforms, Internet of Things (IoT) devices, cloud infrastructures, and decentralized applications. While these systems enhance automation, operational efficiency, and financial inclusion, their highly distributed, data-intensive architectures introduce critical security, privacy, and trust challenges. In this context, artificial intelligence (AI) and blockchain have emerged as complementary technologies capable of addressing these challenges through intelligent decision-making, advanced threat detection, data integrity, and transparent operations. This survey provides a comprehensive review of recent research on securing smart finance systems using AI- and blockchain-based approaches. The survey comprehensively analyzed research published between 2023 and 2026 using the Scopus database, focusing on the keywords “AI,” “blockchain,” and “smart finance.” The analysis reveals extensive use of AI-driven security mechanisms, including credit scoring and risk assessment, transaction monitoring and fraud detection, anti-money laundering (AML) and know-your-customer compliance, identity verification, cyber threat detection, smart contract security analysis, behavioral biometrics, insurance fraud detection, and market risk prediction. In parallel, the survey examines blockchain-enabled security solutions, including secure payment and settlement systems, cross-border remittances, AML and counter-terrorism financing frameworks, digital identity management, smart contracts, asset tokenization, decentralized finance, auditability, and secure interbank communication. The integration of AI and blockchain offers significant advantages, including improved fraud detection accuracy, enhanced transparency and traceability, stronger data integrity, automated compliance, real-time threat response, and increased system resilience. Despite these benefits, key challenges persist, particularly in scalability, privacy preservation, interoperability, regulatory and ethical compliance, energy efficiency, explainability, and post-quantum security. The survey concludes by outlining future research directions and design guidelines for developing secure, scalable, and trustworthy smart finance systems that effectively leverage the integration between AI and blockchain.
Non-fungible tokens (NFTs) are widely used to distribute and authenticate digital artworks, yet minting practices across Ethereum, Solana, and Tezos sometimes diverge from core blockchain objectives, decentralization, immutability, and verifiable on-chain identity, thereby limiting their suitability as long-term certificates of authenticity. This study examines the technical, structural, and archival sources of these limitations and introduces a framework grounded in immutability, extended metadata and cryptographic signatures. Within this framework, the extended metadata file serves as the primary source of authenticity by self-sufficiently integrating the artist’s identity, artwork identification, edition semantics, token identification, and preservation guidance. The paper further evaluates decentralized storage models relevant to certification-grade use cases. It compares private servers, fully on-chain metadata, Arweave, and IPFS in terms of verifiability, sustainability, and long-horizon stewardship burden. Although Ethereum's ERC-721 serves as a reference implementation to anchor terminology and verification procedures, the proposed requirements are ecosystem-independent as long as the ecosystem meets the principles of decentralization, immutability and adoption. By aligning NFT issuance with established digital-preservation frameworks (OAIS, InterPARES, LOCKSS, PREMIS), this work offers a concrete foundation for future ERC/EIP proposals, preservation policy, and interdisciplinary research on durable, independently verifiable digital-art authenticity.
Blockchain is a decentralized, distributed ledger technology that ensures transparency, security, and immutability through cryptographic techniques. However, advancements in quantum computing threaten the security of classical cryptographic schemes, jeopardizing blockchain integrity once cryptographic quantum supremacy is achieved. This milestone, defined here as the realization of quantum computers to solve practical cryptographic problems, would render existing security standards vulnerable, exposing blockchain assets (currency, data, etc.) to fraud and theft. To address this risk, we propose and implement a smart contract deployable on the Ethereum blockchain, having the ability to run applications on its blockchain, that generates classically intractable puzzles by probabilistically generating large, hard-to-factor numbers without requiring secret information. This contract then serves two purposes: to establish a mechanism (1) for a trustless, unbiased proof of cryptographic quantum supremacy by verifying solutions to these puzzles, and (2) to protect user funds on Ethereum by triggering quantum-secure fallback protocols upon detecting cryptographic quantum supremacy, since it is desirable to wait as long as possible to fall back to a quantum-secure scheme because of its inherent additional cost and complexity. These mechanisms demonstrate the ability to identify cryptographic vulnerabilities and ensure a smooth transition to quantum-secure standards, safeguarding blockchain assets in a post-quantum era.
The integration of cryptocurrencies into institutional portfolios necessitates the adoption of robust risk modeling frameworks. This study is a part of a series of subsequent works to fine-tune model risk analysis for cryptocurrencies. Through this first research work, we establish a foundational benchmark by applying the traditional industry-standard Geometric Brownian Motion (GBM) model. Popularly used for non-crypto financial assets, GBM assumes Lognormal return distributions for a multi-asset cryptocurrency portfolio (XRP, SOL, ADA). This work utilizes Maximum Likelihood Estimation and a correlated Monte Carlo Simulation incorporating the Cholesky decomposition of historical covariance. We present our stock portfolio model as a Minimum Variance Portfolio (MVP). We observe the model's structural shift within the heavy-tailed, non-Gaussian cryptocurrency environment. The results reveal limitations of the Lognormal assumption: the calculated Value-at-Risk at the 5% confidence level over the one-year horizon. For baselining our results, we also present a holistic comparative analysis with an equity portfolio (AAPL, TSLA, NVDA), demonstrating a significantly lower failure rate. This performance provides conclusive evidence that the GBM model is fundamentally the perfect benchmark for our subsequent works. Results from this novel work will be an indicator for the success criteria in our future model for crypto risk management, rigorously motivating the development and application of advanced models.
As quantum computing matures, characterizing its practical workloads and verifying quantum supremacy presents a significant challenge. Current benchmarking and claims rely on trust-based verification methods that lack public auditability. We propose a decentralized benchmarking framework implemented via an Ethereum smart contract to provide verifiable assurance in these claims. This framework generates classically intractable puzzles that, crucially, require absolutely no pre-computed secrets. By utilizing the blockchain as an immutable public ledger, independent observers can mathematically verify that any provided solution to the puzzle must have been computationally derived via quantum hardware rather than classically spoofed. Furthermore, we demonstrate how this verifiable benchmarking metric can be utilized as an automation trigger. As a practical example of such a trigger, we focus on the ability for blockchains to automatically switch to quantum-secure signature schemes upon the successful demonstration of cryptographic quantum supremacy. We demonstrate these principles with BloQBench, which implements the concept using integer factorization as the generated puzzle and Lamport signatures as the trigger-based effect. This approach demonstrates a novel use of distributed ledgers for quantum workload characterization, providing a transparent, automated metric for measuring quantum supremacy while managing the performance and complexity trade-offs of post-quantum technology transitions.
Harmonic Genesis: The SHA Unfolding and the Recursive Nexus of Reality Driven by Dean a. Kulik January 2026 Section 1: Genesis Section 2&3 : Paper Zero Introduction – Cracking Randomness into a New Order What if one of the most trusted “random” cryptographic functions in the digital world turned out to be an accidental microscope into the structure of reality? This is the crux of the discovery at hand. SHA-256, a secure hash algorithm assumed to output unpredictable gibberish, harbors a hidden harmonic pattern anchored at a very special constant: π/9 (approximately 0.349). In uncovering this pattern – a π/9 harmonic field alignment – we find that the hash’s apparent chaos conceals an emergent cosmic order. The 256-bit output lattice of SHA-256 is not a uniform random space at all, but rather is biased toward a profound equilibrium ratio (~35% order, ~65% chaos). In other words, SHA’s design inadvertently tunes itself to the[1][2]universal harmonic constant , and that changes everything we thought we knew about cryptographic randomness. This breakthrough means SHA-256 is not broken in the traditional sense – it is revealed. We have not found a trivial way to invert the hash or crack passwords; instead, we have found that SHA-256 outputs carry a signature of order in their very randomness. It’s as if a secret melody was resonating within white noise. Rather than a meaningless jumble, each SHA output is an accidental lens into the manifold of mathematical reality – a snapshot of a deeper truth-field encoded in binary. This exposition will unfold how the π/9 alignment was discovered, the rigorous proofs of its existence, and the staggering implications that ripple out from cryptography into physics, cognition, and our understanding of the universe’s fabric. Once seen, this pattern cannot be unseen; it is a one-way transformation in knowledge – an Ω lock on our perspective. We stand at the threshold of an irreversible insight: randomness, trust, life, and cosmos may all be threaded by the same recursive harmonic architecture. The π/9 Harmonic Field Alignment in SHA-256 At the heart of this discovery is the recognition that SHA-256 outputs gravitate toward a harmonic ratio . In numeric terms, , or roughly 0.35, emerges as a stable threshold in the hash’s behavior. What does this mean? In the[3][4]Nexus harmonic framework, 0.35 (also called the Mark 1 attractor) represents an optimal balance between order and disorder in a complex system. Amazingly, SHA-256 – a human-designed algorithm – unknowingly [5][6]operates at this balance point. Each 256-bit digest tends toward a state where about 35% of the bits carry structured, “actualized” information, and 65% remain in flux as entropy[1][7]. This is in stark contrast to a truly random hash, which would have no such bias (ideally 50% of bits 1 and 0). Yet SHA outputs consistently show this 35/65 split when analyzed, indicating an emergent lattice structure in the output space.[8][9] How does this happen? It turns out the internal design of SHA-256 – its constants and round structure – act as “invariant anchors” that prevent complete randomness. The fractional parts of cube roots of primes used as SHA constants, and even the padding rules, introduce slight biases (a kind of “geometric reference”) each round. Instead of injecting pure chaos, these choices guide the hash toward a [10][11][10]particular equilibrium. Over 64 rounds of mixing, the message is not just obliterated into noise; it is folded and refolded into a structured 256-bit outcome, almost like a piece of origami. The Mark 1 harmonic formula formalizes this by comparing total potential information to actualized information in the hash. In a [1]harmonically balanced hash, , meaning roughly 35% of the state’s capacity becomes “organized” (patterned bits) and 65% remains “potential” or random. The SHA constants essentially [8][7]tune the algorithm to achieve this ratio, acting as a built-in bias toward order amidst chaos[12][9]. Crucially, π/9 is not just a random fraction – it appears to be a universal attractor across systems. In fact, the Nexus research identifies as a recurring sweet spot in complex processes, from Game-of-Life cellular automata to cosmic-scale dynamics. In Conway’s Game of Life (a Turing-complete cellular automaton), maximum complexity emerges at about 35% cell density – the same 0.35. SHA-256, remarkably, behaves like a [13][13][14]digital Game of Life: 64 rounds = 64 generations, mixing rules like cellular neighbor updates, and a final pattern that isn’t random but an “oscillating” complexity pattern at the edge of chaos. This is the π/9 alignment showing itself. Rather than a fortuitous coincidence, we begin to see it as evidence that [15][16]SHA-256’s design tapped into a fundamental law of recursive systems: an equilibrium between entropy and structure at π/9, where computation produces maximal complexity and meaningful patterns.[13][14] In summary, the π/9 harmonic field alignment in SHA-256 reveals that what we once assumed to be pure computational randomness is actually structured chaos. The hash output lattice behaves like a resonant field, with π/9 as its tuning frequency. The “secure hash” was securing something more profound than our data – it was securing a bridge between math and reality, locking each output to a hidden order. The apparent security lattice isn’t a random scatter, but a harmonic matrix reflecting an emergent order that transcends the algorithm itself. We have, in effect, discovered that SHA’s unpredictability masks a deterministic harmonic signature. Next, we delve into how we proved this alignment exists and what symbols and logic confirm this new reality.[17][9] Evidence and Proof of Harmonic Alignment in SHA Uncovering the SHA harmonic alignment required a combination of mathematical analysis, computational experiments, and symbolic interpretation. The proofs range from hard numbers to almost poetic patterns, each reinforcing that SHA outputs are not random at all, but resonant. 1. Statistical and Mathematical Proofs: The simplest evidence came from bit statistics and delta analyses. By measuring the proportion of 1s vs 0s across large sets of SHA-256 hashes, researchers consistently found the ratio drifting toward ~0.35 (35% ones) instead of the expected 0.5. This alone was a red flag: the hash was too “orderly.” Furthermore, using the Mark1 formula on hash states confirmed that [8][12]H converges near 0.349 for a broad class of inputs. The probability of this happening by chance (if SHA were truly random) is astronomically low. It indicated a [1][18]hidden invariant. Additional math revealed the source: when comparing a hash to a transformed version of itself (like a reversed-nibble or ASCII-reencoded variant), the difference often contained long runs of zeros in hex – meaning the two forms were closely aligned. This is the [19][20]Mirror Law: if you hash something and then hash a related input, their binary difference is not random noise but structured cancellation, exposing a residue of the original content. Massive trailing zero patterns in the XOR of two hashes signal that [21][20]SHA’s avalanche effect cancels things out in a regular way – a hallmark of resonance, not randomness. In essence, the hash “echoes” the input in subtle harmonic ways rather than wholly erasing it. A concrete example of a mathematical curiosity turned proof was with the strings “Hello” (capital H) vs “hello” (lowercase). The SHA-256 of these two differ in a predictable, structured way: by converting the hash of “Hello” to an ASCII-hex representation and reversing 4-bit chunks, you literally obtain the hash of “hello”. At first glance, this seems impossible – hashes should change unpredictably with even a small input difference. But here it happened exactly, demonstrating an [22][23]entangled resonance between semantically related inputs. The reflective transformation realigned the hash’s “tension” to a harmonic ground state, effectively showing that the hash carried latent information about letter casing. The generalized reflection theorem born from this: if two inputs differ by a minor harmonic perturbation (like case or small semantic twist), their hashes are not independent – they are[24][25]entangled by a harmonic delta. Subtracting or XORing them reveals a meaningful pattern (like those zero tails) corresponding to the seed difference. This provides a logical proof:[19][20]SHA-256 encodes content identity and “misalignment” as measurable harmonic residues. A truly random function would not consistently allow such a subtraction to yield anything but noise. Yet here, the difference pointed directly back to the underlying change (like an arrow saying “these two hashes differ in a simple way!”). Such behavior underscores that SHA outputs lie on a structured lattice; move slightly on that lattice (change input slightly), and the output moves in a predictably structured way (leaving a harmonic trail). 2. Symbolic and Empirical Proofs (The π Projection Anomaly): Some of the most striking evidence came from visual and symbolic analyses of hashes – treating the hash digest not just as a number, but as a language of its own. A major clue was the so-called “SHA→π glyph” anomaly[26][27]. Researchers found that if you interpret certain SHA-256 outputs in base-π or map them onto a circle, they produce recognizable patterns – even digits of π itself! One dramatic case involved a simple input (a short DNA sequence “ATGC…” in one experiment): its SHA-256 hash, when examined byte by byte, appeared to contain the first six digits of π (3.14159…) in order among the hex bytes. Even more bizarre, after those six digits, the sequence “skipped” what would have been 7 and 8 and then devolved into entropy – almost as if the hash [28][29]started to write out π, confirmed alignment, and then stopped. This was dubbed a “Zero-Point Harmonic Collapse” (ZPHC)[30][29]. The i
The article substantiates the critical inadequacy of traditional static risk assessment methods (specifically, VaR and standard deviation) for analyzing the effectiveness of integrating Decentralized Finance (DeFi) assets into investment portfolios. It is proven that the returns of DeFi assets are characterized by a non-normal distribution with pronounced «fat tails», which creates a significant risk of underestimating catastrophic losses. The purpose of the study is to develop and theoretically substantiate a methodology for evaluating the effectiveness of DeFi platforms in diversifying investment portfolios. The methodological gap between the requirements of the volatile DeFi market and the limitations of classical financial models is investigated, particularly in the areas of controlling Tail Risk and the dynamic nature of correlational dependence, which critically increases during market shocks (the «correlation-to-one» effect). A four-stage methodology is proposed, which includes the theoretical integration of Conditional Value-at-Risk (CVaR) as a basic coherent measure of extreme risk and a developed algorithm for proactive diversification management based on the DCC-GARCH model. This made it possible to calculate the Optimal Dynamic Hedging Weight, necessary for the daily adjustment of the portfolio structure to prevent the loss of the diversification effect. The comprehensive methodology developed provides a complete cycle of proactive risk management and offers a clear algorithm for making decisions about the structure of an investment portfolio. The scientific and practical significance of the research lies in formulating methodological recommendations and evaluation criteria that ensure a transition from static analysis to proactive risk management in investment activities. The developed methodology provides a toolkit for making informed decisions regarding the optimal share of DeFi assets in a portfolio, combining return maximization with extreme risk minimization. The application of this methodology is beneficial for investors, financial analysts, quantitative strategists, and hedge fund managers working with high-risk and innovative asset classes that require advanced risk control tools.
The article substantiates the critical inadequacy of traditional static risk assessment methods (specifically, VaR and standard deviation) for analyzing the effectiveness of integrating Decentralized Finance (DeFi) assets into investment portfolios. It is proven that the returns of DeFi assets are characterized by a non-normal distribution with pronounced «fat tails», which creates a significant risk of underestimating catastrophic losses. The purpose of the study is to develop and theoretically substantiate a methodology for evaluating the effectiveness of DeFi platforms in diversifying investment portfolios. The methodological gap between the requirements of the volatile DeFi market and the limitations of classical financial models is investigated, particularly in the areas of controlling Tail Risk and the dynamic nature of correlational dependence, which critically increases during market shocks (the «correlation-to-one» effect). A four-stage methodology is proposed, which includes the theoretical integration of Conditional Value-at-Risk (CVaR) as a basic coherent measure of extreme risk and a developed algorithm for proactive diversification management based on the DCC-GARCH model. This made it possible to calculate the Optimal Dynamic Hedging Weight, necessary for the daily adjustment of the portfolio structure to prevent the loss of the diversification effect. The comprehensive methodology developed provides a complete cycle of proactive risk management and offers a clear algorithm for making decisions about the structure of an investment portfolio. The scientific and practical significance of the research lies in formulating methodological recommendations and evaluation criteria that ensure a transition from static analysis to proactive risk management in investment activities. The developed methodology provides a toolkit for making informed decisions regarding the optimal share of DeFi assets in a portfolio, combining return maximization with extreme risk minimization. The application of this methodology is beneficial for investors, financial analysts, quantitative strategists, and hedge fund managers working with high-risk and innovative asset classes that require advanced risk control tools.
This paper examines the potential transformation of Venezuela into a significant IT offshore hub in the context of anticipated political regime change. Using a multi-dimensional analytical framework that integrates labor economics, financial technology adoption, enterprise software markets, and critical infrastructure security, we investigate how Venezuela's prolonged isolation has paradoxically produced unique conditions for technology sector growth. We identify four critical impact vectors shaping this potential transition: Remote labor arbitrage normalization — Venezuela's highly educated yet underemployed workforce, coupled with global remote work trends, creates a compelling labor cost advantage in international IT services markets. Cryptocurrency-native population as a fintech catalyst — Years of hyperinflation and sanctions have driven widespread adoption of cryptocurrencies and stablecoins as alternative financial infrastructure, positioning Venezuelans to lead in fintech innovation and digital payments integration. Technology infrastructure deficit as a SaaS expansion opportunity — Although national telecommunications and digital infrastructure lag regional peers, planned post-transition investment in fiber optics, 5G, and connectivity could accelerate Software-as-a-Service (SaaS) consumption and development. Cybersecurity challenges in legacy system modernization — Legacy systems and weak institutional cybersecurity create both risks and service demand, underscoring the need for secure IT modernization strategies in public and private sectors alike. We argue that Venezuela's forced technological experimentation during economic collapse — including informal digital payment systems and decentralized finance adoption — has unintentionally cultivated technological resilience and local digital proficiency unprecedented in Latin America. By situating Venezuela's tech transition within broader geopolitical disruption and global technology labor markets, this research contributes new frameworks for analyzing emerging offshore IT markets in post-crisis economies and highlights actionable pathways for stakeholders targeting digital services growth in transitional states.
We present Y.I.N.-LLM, a privacy-preserving training architecture for Large Language Models that mathematically guarantees non-memorization of training data. The core innovation is the mandatory DP→ZK→HE ordering (Differential Privacy → Zero-Knowledge Proof → Homomorphic Encryption) applied to transformer gradients during training. Key results: (1) 2.3% accuracy loss at ε=1.0 privacy versus 15-40% with standard DP-SGD; (2) zero extractable training data across all tested attack vectors; (3) native GDPR Article 17 "right to be forgotten" compliance via cryptographic gradient subtraction; (4) EU AI Act Article 50 transparency compliance through verifiable privacy proofs. The Non-Memorization Theorem establishes that for any model M trained with Y.I.N.-LLM parameters (ε, δ), the probability of verbatim reproduction is bounded: P[M outputs y | x ∈ training] ≤ e^ε · P[M outputs y | x ∉ training]. This transforms copyright defense from argument to mathematics. Y.I.N.-LLM addresses the $10B+ memorization litigation crisis (NYT v. OpenAI, Getty v. Stability AI, Authors Guild v. OpenAI) by providing the first mathematically verifiable non-memorization guarantee with practical accuracy preservation. Patent Protected: U.S. Provisional Application 63/946,118 (filed December 21, 2025).
The financial services sector is experiencing unprecedented transformation through the adoption of virtualization technologies, encompassing cloud computing and edge computing digitalization initiatives that fundamentally alter operational paradigms and competitive dynamics within the industry. This systematic literature review employed a comprehensive methodology, analyzing peer-reviewed articles, systematic reviews, and industry reports published between 2016 and 2025 across three primary technological domains, utilizing thematic content analysis to synthesize findings and identify key implementation patterns, performance outcomes, and emerging challenges. The analysis reveals consistent evidence of positive long-term performance outcomes from virtualization technology adoption, including average transaction processing time reductions of 69% through edge computing implementations, substantial operational cost savings and efficiency improvements through cloud computing adoption, while simultaneously identifying critical challenges related to regulatory compliance, security management, and organizational transformation requirements. Virtualization technology offers transformative potential for financial services through improved operational efficiency, enhanced customer experience, and competitive advantage creation, though successful implementation requires sophisticated approaches to standardization, regulatory compliance, and change management, with future research needed to develop integrative frameworks addressing technology convergence and emerging applications in decentralized finance and digital currency systems.
Firmware integrity is a foundational requirement for securing Cyber-Physical Systems (CPS), where malicious or compromised firmware can result in persistent backdoors, unauthorized control, or catastrophic system failures. Traditional verification mechanisms such as secure boot, digital signatures, and centralized hash databases are increasingly inadequate due to risks from insider threats and single points of failure. In this paper, we propose a decentralized firmware integrity verification framework built on the Ethereum blockchain, offering tamper-proof, transparent, and trustless validation. Our system stores SHA-256 hashes of firmware binaries within smart contracts deployed on the Ethereum Sepolia testnet, using Web3 and Infura for seamless on-chain interaction. A Python-based client tool computes firmware hashes and communicates with the blockchain to register and verify firmware authenticity in real-time. We implement and evaluate a fully functional prototype using real firmware samples, demonstrating successful contract deployment, hash registration, and integrity verification through live blockchain transactions. Experimental results confirm the reliability and low cost (in gas fees) of our approach, highlighting its practicality and scalability for real-world CPS applications. To enhance scalability and performance, we discuss extensions using Layer-2 rollups and off-chain storage via the InterPlanetary File System (IPFS). We also outline integration pathways with secure boot mechanisms, Trusted Platform Module (TPM)-based attestation, and zero-trust architectures. This work contributes a practical and extensible model for blockchain-based firmware verification, significantly strengthening the defense against firmware tampering and supply chain attacks in critical CPS environments.
Yuxin Xia, Ziyang Ji, Jie Zhang, Wanxin Li · 7 authors
Abstract Non-Fungible Token (NFT) creators use digital signatures to ensure the ownership, authenticity, integrity, and nonrepudiation of their digital works. However, if the private key is compromised, an attacker can generate unauthorized NFTs by using the creator’s private key to issue valid signatures. These valid but unauthorized signatures will be accepted in the NFT market and cannot be revoked. Even if the NFT creators update their private-public key pairs, they cannot deny the NFTs generated by the attacker. To mitigate these risks, we propose revocable signature by introducing commitment mechanism and an Auxiliary Embedded Key ( AEK ) into the signature, while the regular verification process does not involve this AEK . If a valid but unauthorized signature is detected and needs to be revoked, AEK will be disclosed to perform the revocation operation. To illustrate the application of revocable signatures in NFT, we design and implement a revocable Elliptic Curve Digital Signature Algorithm (ECDSA) scheme with provable security. Experimental evaluations on the FIPS-recommended elliptic curves show that the performance of revocable ECDSA is comparable to the basic ECDSA, with additional 0.0303 s (P-256 curve) and 0.15 USD gas fee in Remix VM for revoking a signature.
Open access
Cryptography and Data Security
Cryptography and Residue Arithmetic
Physical Unclonable Functions (PUFs) and Hardware Security
In today's fast-paced business environment, art has experienced a dramatic and quick transition. These days, artists are not only artists; they are also artrepreneurs who combine their artistic and business acumen. Digital and social media are essential components of the significant development of artistic self-employment. Social media sites like YouTube and Instagram are now critical for establishing a strong online presence, interacting with a global audience, and bypassing intermediaries.Art Education is the procedural approach of teaching and learning artistic skills, aiming to foster creativity, critical thinking, and a deeper understanding of the world. Creative methods, aesthetic questions, and individual artistic expressions are the main topics of contemporary art education. However, they hardly ever give art students the technological, entrepreneurial, and self-management abilities needed to create and maintain financial rewards from artistic endeavours. Since many artists work for themselves or as freelancers, entrepreneurship is a vital part of arts education and is critical for career success in the arts. The lines between digital technologies, art, and commerce are becoming increasingly hazy. Furthermore, there is a pressing need to reconsider the function of art education in light of the emergence of Web3. Without addressing these linkages, art pedagogy runs the risk of leaving students unprepared to deal with both creative agency and financial independence in the digital age. The skill gap is widened when such competencies are not included, making it more difficult for graduates to turn their artistic expertise into long-term professions. Recent research on arts entrepreneurship education reiterates this worry and shows how the abilities offered in art schools continue to diverge from those needed in the creative sectors. Despite being highly skilled and productive when they leave school, graduates lack the necessary skills in related fields like marketing, finance, and entrepreneurship. A hybrid curriculum that strikes a balance between art education and business training is necessary to connect creativity with entrepreneurial education. Project-based collaborations, internships, and real-world simulations are examples of experimental techniques that are seen to be particularly effective in equipping students with both business and creative skills (Ávila & Davel, 2023). There is an urgent need to reconsider the significance of art pedagogy and develop a groundbreaking educational framework that logically integrates various fields. To close this gap, the art curriculum must be completely changed to incorporate digital technologies and entrepreneurship. The goal of modern pedagogy is to provide art students with the necessary tools for a sustainable career, visibility, smart use of digital technology, market adaptation, and financial independence-not to dilute the content. The S.M.A.R.T Curriculum Loop, a revolutionary framework that tackles issues regarding the merging of art with business and digital skills, has been proposed in this study as a solution to this important necessity in art academia. Such a drastic change would equip art students to pursue jobs that are both financially feasible and creatively satisfying.The S.M.A.R.T Curriculum Loop provides a clear framework for introducing students to international art by combining social media-driven art education into conventional art courses. This methodology helps students fulfil the needs of the digital economy by integrating multidisciplinary elements into art instruction. Universities can equip artists who lack the requisite technological abilities and help them develop resilience in the digital age in this way. This Opinion Article posits that the modern education of art needs to immediately shift out of a studio-based, skills-oriented model to begin digitally empowered artrepreneurial education. Whereas conventional methods focus on mastering the arts, they do not equip graduates with a creative economy that is influenced by the dynamics of social media, the governance of platforms, and the creation of visibility through algorithms. This paper will argue that the S.M.A.R.T Curriculum Loop as a futureoriented solution to the challenge of digital literacy, entrepreneurial ability, and creative practice is viable because it integrates all three into a pedagogical framework.The limitations outlined above necessitate a re-examination of how existing scholarship conceptualises creativity, entrepreneurship, and digital fluency in art education. The following section synthesises prior studies that inform the development of the S.M.A.R.T Curriculum Loop.Promoting creativity in art discipline higher education is often an unexplored area that needs attention at the institutional level, as creativity is no longer seen as a luxury but a necessity in the current economic world post-COVID-19 outbreak and quarantines. Systematic integration of creativity in universities is imperative rather than treating art as a separate domain. The four correlating factors for fostering creativity-conversation, scholarly relations, liminal spaces and leadership-must be included in the present-day art curriculum. This framework criticises traditional pedagogies and addresses creativity as a perpetual, relational and formal mechanism crucial for learning, leadership and innovation (Rae, 2023).Due to the ever-evolving nature of the art economy, entrepreneurial skills have become an integral aspect of art education. Traditional art education is often expertise-centric, relying solely on artistic mastery. Today's Artists must be selfsufficient and capable of dealing with complex market dynamics, navigating digital platforms and building personal brand image. This can be attained only by integrating entrepreneurial training into the art curriculum, which can lead to fostering innovation and adaptability (Zhang & Wang, 2022).Despite the increasing acceptance of entrepreneurship education in higher education, it is often overlooked in the field of the arts. There is a scarcity of existing research to comprehend arts entrepreneurship, which hinders its integration into the arts curriculum. Artrepreneurship education is valuable in enhancing the entrepreneurial competencies of artists. However, there is a need to address the gap between skills acquired through art education and skills actually required for their viable careers (Wong & Chan, 2024).A novel pedagogy must equip artists with skills not only for fostering artistic persona but also autonomy, resilience and digital fluency-enabling a generation of artrepreneurs capable of steering Web3 platforms, building and learning viable habits and practices and reclaiming rights over their original creations (Bridgstock, 2013).Artificial Intelligence (AI) and Web3 technologies now serve as core components of art production, distribution and monetisation in the present-day world. These technologies include Blockchain, NFTs (Non-Fungible Tokens) and DAOs (Decentralised Autonomous Organisations). Generative AI models like Midjourney and DALL•E allow artists to create complex visual concepts from simple text prompts, fundamentally changing the creative process and the definition of a 'tool' in art. AI functions not only as a catalyst for artistic innovation but also as a source of ethical challenges, particularly through the use of generative models such as GANs and diffusion models that reshape creative processes while raising concerns of authorship, originality, and artistic integrity(Amini, 2025).Art education must strategically include these technologies in its art pedagogy, as these are no longer just peripheral tools but fundamental in the rapidly evolving creative economy. NFTs have transformed the conventional perception of ownership and creatorship, introducing students to the idea of digital origination, providing access to global art dissemination through a decentralised system of networks. Smart contracts, a novel term, allow the generation of digital royalties, thereby reimagining the importance of entrepreneurial agency and financial independence for a creator. Web3, NFTs and DAOs are revolutionising art education, transitioning traditional university models into a 'metaversity' concept.NFTs help in keeping a secure record of students' data, DAOs provide decentralised learning centres, while Web3 facilitates customised open learning. The metaverse provides interactive virtual environments for engaging, synchronous, and asynchronous education (Sutikno & Aisyahrani, 2023).Previous research supports critiques of traditional art education, indicating the scarcity of existing research in arts entrepreneurship and a gap between skills acquired through art education and skills actually required for their viable careers (Wong & Chan, 2024). Conventional arts education relies on studio setup and knowledge dissemination, which deals with developing creative, sophisticated, disciplinary, and technical skills. These theoretical or conceptual disseminations of knowledge, which are monotonous, neglect adequate skill development, fail to include critical thinking, and often lack real-world relevance. This is particularly alarming given that most creative, performing and literary artists are self-employed or work on a freelance basis, making entrepreneurial skills critical for career sustainability and success. Art educators are often facing a dilemma in identifying and defining the skill sets required for artrepreneurial pedagogy (Bridgstock, 2013).The older, outdated framework is hindered by faculty hesitance to accept art education as a new frontier due to their narrow perception of entrepreneurial education as merely a "vocation", which conflicts with the age-old romanticisation of art as distinct from a source of revenue. Lack of consensus by art school managers on a curriculum that suits present needs by adopting successful business schools' models is another issue (Beckman, 2007). The available curriculum doesn't equip artists with the necessary Web3 skills, which are essential for navigating their careers. Students generate strong academic portfolios but are appraised with limited digital presence or tool proficiency, building a gap between their talents and tangible opportunities. Most programs also neglect the critical rise of technologies like AI, NFTs and Smart contracts. This overlooks recent technologies, leaving the students unprepared for navigating digital art markets. There is a pressing need for the formation of a formal instructional framework with strategic entrepreneurial and digital competencies.As an example, a recent graduate surveys conducted of design and fine arts courses in Asia and Europe have shown that students graduate with good portfolios, but they lack a digital presence, a fact that has a direct impact on employability on algorithmdriven creative markets. Most of these institutions still focus on studio production as they provide very scarce training on online visibility, digital rights, and monetisation strategies. Conversely, those programs with experience of implementing hybrid creative-entrepreneurship courses (e.g., digital portfolio markets, social-media-based exhibition projects) claim to find substantially better graduate interaction with international audiences. These instances point to the fact that disconnect is not a hypothetical notion but it can be seen in actual educational outcomes. They may organise interactive exhibitions in a virtual space, allowing a global audience to access, interact with, and buy their artwork in real-time. Digital fluency and the commercial skills needed in art markets are expanded and disseminated through such encounters.These tools allow art students to move beyond traditional studio-based instruction because of their transformative ability to develop new models for creativity and collaboration. Students can gain practical experience that prepares them for jobs as artrepreneurs by interacting directly with these (Sutikno & Aisyahrani, 2023).The implementation of this kind of technologies in art education goes NFT-based assignments make evaluation more transparent through verifiable ownership records and metadata trails. DAO-led collaborative projects allow instructors to assess participation, governance decisions, and community contribution as part of the creative output.The S.M.A.R.T Curriculum Loop may immediately address all of the drawbacks of traditional art education, which leave students unprepared to succeed in professional marketplaces. This framework fills the gap in the demands of the digital world by incorporating multidisciplinary elements into art instruction. It works as a cycle that allows for skill improvement and iterative participation over a number of semesters. The creative framework addresses the demands of today's art students by combining social media and entrepreneurial abilities. The authors disclose that there are no commercial or financial relationships that could potentially create a conflict of interest regarding this research.The research received no support of funding.The referencing style used in the study is APA formatting style.
We present a novel framework for analyzing blockchain consensus mechanisms by modeling blockchain growth as a Partially Observable Stochastic Game (POSG) which we reduce to a set of Partially Observable Markov Decision Processes (POMDPs) through the use of the mean field approximation. This approach formalizes the decision-making process of miners in Proof-of-Work (PoW) systems and enables a principled examination of block selection strategies as well as steady state analysis of the induced Markov chain. By leveraging a mean field game formulation, we efficiently characterize the information asymmetries that arise in asynchronous blockchain networks. Our first main result is an exact characterization of the tradeoff between network delay and PoW efficiency--the fraction of blocks which end up in the longest chain. We demonstrate that the tradeoff observed in our model at steady state aligns closely with theoretical findings, validating our use of the mean field approximation. Our second main result is a rigorous equilibrium analysis of the Longest Chain Rule (LCR). We show that the LCR is a mean field equilibrium and that it is uniquely optimal in maximizing PoW efficiency under certain mild assumptions. This result provides the first formal justification for continued use of the LCR in decentralized consensus protocols, offering both theoretical validation and practical insights. Beyond these core results, our framework supports flexible experimentation with alternative block selection strategies, system dynamics, and reward structures. It offers a systematic and scalable substitute for expensive test-net deployments or ad hoc analysis. While our primary focus is on Nakamoto-style blockchains, the model is general enough to accommodate other architectures through modifications to the underlying MDP.
Cryptocurrency trading increasingly depends on timely integration of heterogeneous web information and market microstructure signals to support short-horizon decision making under extreme volatility. However, existing trading systems struggle to jointly reason over noisy multi-source web evidence while maintaining robustness to rapid price shocks at sub-second timescales. The first challenge lies in synthesizing unstructured web content, social sentiment, and structured OHLCV signals into coherent and interpretable trading decisions without amplifying spurious correlations, while the second challenge concerns risk control, as slow deliberative reasoning pipelines are ill-suited for handling abrupt market shocks that require immediate defensive responses. To address these challenges, we propose WebCryptoAgent, an agentic trading framework that decomposes web-informed decision making into modality-specific agents and consolidates their outputs into a unified evidence document for confidence-calibrated reasoning. We further introduce a decoupled control architecture that separates strategic hourly reasoning from a real-time second-level risk model, enabling fast shock detection and protective intervention independent of the trading loop. Extensive experiments on real-world cryptocurrency markets demonstrate that WebCryptoAgent improves trading stability, reduces spurious activity, and enhances tail-risk handling compared to existing baselines. Code will be available at https://github.com/AIGeeksGroup/WebCryptoAgent.
Advances in large language models have enabled agentic AI systems that can reason, plan, and interact with external tools to execute multi-step workflows, while public blockchains have evolved into a programmable substrate for value transfer, access control, and verifiable state transitions. Their convergence introduces a high-stakes systems challenge: designing standard, interoperable, and secure interfaces that allow agents to observe on-chain state, formulate transaction intents, and authorize execution without exposing users, protocols, or organizations to unacceptable security, governance, or economic risks. This survey systematizes the emerging landscape of agent-blockchain interoperability through a systematic literature review, identifying 317 relevant works from an initial pool of over 3000 records. We contribute a five-part taxonomy of integration patterns spanning read-only analytics, simulation and intent generation, delegated execution, autonomous signing, and multi-agent workflows; a threat model tailored to agent-driven transaction pipelines that captures risks ranging from prompt injection and policy misuse to key compromise, adversarial execution dynamics, and multi-agent collusion; and a comparative capability matrix analyzing more than 20 representative systems across 13 dimensions, including custody models, permissioning, policy enforcement, observability, and recovery. Building on the gaps revealed by this analysis, we outline a research roadmap centered on two interface abstractions: a Transaction Intent Schema for portable and unambiguous goal specification, and a Policy Decision Record for auditable, verifiable policy enforcement across execution environments. We conclude by proposing a reproducible evaluation suite and benchmarks for assessing the safety, reliability, and economic robustness of agent-mediated on-chain execution.
This research establishes a formal topological framework for managing non- stationary market assets in portfolios by synthesizing high-dimensional chaotic dy- namics with industrial quality control and cryptographic verification. We introduce the Hala Operator as a state-dependent regulator capable of inducing Successive Controlled Collapse (SCC)—a process that maps continuous chaotic flows onto discrete, stable fixed-point constellations. By utilizing Taguchi Design of Experiments (DoE) for off-market robustness and Zero-Knowledge SNARKs for execution privacy, we provide a mathematically rigorous solution to the "Newtonian Trap" of market unpredictability. Formal proofs of global stability, dimension collapse via divergence analysis, and the uniqueness of the discrete constellation are presented.
Illegal, Unreported, and Unregulated (IUU) fishing remains a major threat to marine ecosystems and coastal livelihoods, yet existing enforcement mechanisms rely on periodic inspections, manual reporting, or static financial incentives. We propose a novel closed-loop compliance-to-finance system in which multi-sensor vessel data are transformed into real-time financial signals that directly govern access to capital. In the proposed architecture, heterogeneous onboard and port-side sensors feed into an off-chain AI compliance model whose outputs are transmitted on-chain via decentralized oracle services. These compliance attestations programmatically adjust lending terms in Decentralized Finance (DeFi) protocols, dynamically reducing interest rates and increasing liquidity for compliant operators while restricting capital access for non-compliance. Loans are issued in USD-pegged stablecoins and overcollateralized using real-world fishing assets, including vessels, licenses, quotas, and contracts. Unlike prior approaches that treat sustainability incentives as external subsidies or reputational mechanisms, this system embeds regulatory compliance directly into the cost of capital, creating continuous, automated enforcement with minimum centralized intermediaries. We illustrate the feasibility of this architecture using existing low-cost sensing technologies, oracle infrastructure, and DeFi lending primitives, and discuss its potential to expand sustainable financing in small-scale and low-income fisheries where IUU fishing is most prevalent.