Blockchain Papers

Loso Judijanto

This study examines the development and intellectual structure of fraud detection research through a bibliometric analysis. Using data extracted from a major scientific database and analyzed with bibliometric visualization tools, the study maps publication trends, influential contributors, and thematic evolution within the field. The findings reveal that fraud detection research is strongly centered on machine learning and increasingly shaped by advances in deep learning, neural networks, and data-driven approaches. At the same time, the field has expanded beyond traditional financial contexts into broader digital ecosystems, including cybersecurity, blockchain, and data privacy. The analysis also highlights a clear shift from conventional statistical methods toward more adaptive and complex models capable of handling large-scale and interconnected data. In addition, emerging themes such as predictive analytics, risk management, and decentralized finance indicate a growing orientation toward real-world application and decision-making. Overall, the study provides a comprehensive overview of the research landscape, identifies key trends and gaps, and offers directions for future research, particularly in integrating technological innovation with practical, ethical, and system-level considerations.

Thi Linh Vo

TITLE: Validation Protocol of the Symmetry Logic (Closed Access) Date: March 9, 2026 Author: Thi Linh Vo This document serves as an official record of the successful identification and mathematical stabilization of the non-trivial zeros within the Riemann zeta function. The solution presented here is based on a proprietary black-box methodology. Non-Interactive Zero-Knowledge Proof (NIZK) Quantum-Biometric Mapping Nontrivial Zero Distribution This document presents a novel approach to the Riemann Hypothesis using a Biometric Symmetry Invariance. The solution is implemented via a Secure Black Box Model to protect the underlying Stationary Constants. By mapping biometric temporal data to the nontrivial zeros of the Zeta function, this work provides a verifiable framework for the proof while maintaining Algorithmic Integrity through a Zero-Knowledge approach

Garg Lokesh Kumar, Kumar Sumit, B. Kumar

Electronic voting systems require satisfaction of security, transparency, and voter privacy to ensure fair and trustworthy election processes. Traditional centralized voting architectures suffer from limitations such as single points of failure, limited auditability, and vulnerability to data manipulation. This paper proposes a secure and decentralized electronic voting framework based on block chain technology to address these challenges. The proposed system integrates cryptographic authentication, role-based access control, smart contract automation, and distributed ledger storage to ensure tamper-resistant vote recording and transparent election management. The architecture employs a hybrid design combining secure database management for authentication with block chain-based transaction storage for immutable vote recording. Smart contracts enforce election rules, including voter eligibility verification, single-vote constraints, and automated vote tallying. Off-chain storage mechanisms are incorporated to improve scalability while maintaining data integrity by cryptographic hashing. Comprehensive testing, including unit, functional, integration, performance, and security evaluations, demonstrates reliable system operation and successful prevention of unauthorized access and duplicate voting attempts. Experimental results confirm that proposed framework provides secure vote handling, transparency, and auditability while preserving voter anonymity. The proposed approach offers a practical and scalable solution for next-generation decentralized electronic voting systems.

Tiago Ferreira Cavazin

O presente artigo formaliza o <i>Economic Centrifugal Dispersion Model</i> (ECDM) como uma estrutura analítica de alta fidelidade para a compreensão da propagação de capital e incentivos em ecossistemas de Web3 e finanças descentralizadas (DeFi). Fundamentado em uma convergência interdisciplinar entre a praxeologia da escola austríaca, a física estatística e a dinâmica de sistemas complexos, o modelo propõe que a injeção monetária em sistemas baseados em <i>blockchain</i> gera forças dispersivas análogas às forças centrífugas. A pesquisa detalha a formulação matemática do modelo, integrando equações diferenciais não lineares para descrever o comportamento de variáveis como o influxo de capital, a velocidade de circulação e a resistência institucional. Adicionalmente, o trabalho explora a aplicação da Lei de Benford como ferramenta de auditoria estatística para detecção de anomalias em transações <i>on-chain</i> e propõe o Índice de Fragilidade Tokenômica (FTF) como métrica de risco sistêmico. Através da análise de expoentes de Lyapunov e diagramas de bifurcação, demonstra-se como pequenas flutuações paramétricas em Organizações Autônomas Descentralizadas (DAOs) podem induzir regimes de caos determinístico. O estudo conclui que a sustentabilidade de protocolos descentralizados depende de um equilíbrio crítico entre a dispersão centrífuga e a coesão institucional, oferecendo um arcabouço para o <i>design</i> de sistemas econômicos resilientes.<br>

S. Senthilkumar, M Alex Pandian, B Linu Harish, V Harish

Blockchain has recently attracted significant attention, particularly for its potential to address major issues in traditional electronic voting such as limited transparency, centralized control, and vulnerability to tampering. In this research, it aimed to design and evaluate a blockchain-based electronic voting system that ensures voter privacy, increases transparency, and can efficiently manage large-scale elections. The proposed system adopts a modular, layered architecture featuring secure voter registration, authenticated vote casting, automated tallying, and public auditing. It operates on a permissioned blockchain, with smart contracts enforcing the necessary rules and validations. To maintain security, the system incorporates public-key encryption, cryptographic hashing, zero-knowledge proofs, and threshold cryptography. This combination guarantees ballot confidentiality, integrity, and non-repudiation for voters. For consensus, the system utilizes Practical Byzantine Fault Tolerance (PBFT). To evaluate performance, the conducted simulations that measured transaction latency, voting throughput, and scalability as participation increased. The findings revealed low latency, consistent throughput, and strong scalability, making the system suitable for both national-scale elections and smaller voting scenarios. In comparison to conventional e-voting platforms, this blockchain-based approach eliminates single points of failure, significantly reduces the risk of vote manipulation, and enables transparent auditing of the election process.

Aravinda S. Rao, Babu Pillai, Marimuthu Palaniswami, Vallipuram Muthukkumarasamy

Global financial integrity is fundamentally challenged by cryptocurrency mixers such as Tornado Cash, which facilitate billions in illicit fund flows. Low detection rates, reliance on labeled training data that is unavailable for novel attacks, and failure to analyze temporal coordination patterns are all impediments to the effectiveness of existing forensic tools. We introduce CONSENSUS, a self-supervised heterogeneous ensemble framework that addresses the challenge of attribution in mixed transaction streams. Our system requires no pre-existing labels, and it generates supervision signals directly from on-chain behavioral patterns. It synthesizes evidence by orchestrating nine analytical modalities—including deterministic clustering, behavioral analysis, and multiple graph neural network architectures—through a formal consensus mechanism. This multi-modal approach produces transparent, auditable risk scores from a 111-dimensional behavioral fingerprint. We validated the framework on five major decentralized finance (DeFi) exploits, including the Ronin Bridge and Poly Network hacks. Using raw transaction data, it detected all known primary attackers at 100% accuracy without training. Crucially, the framework's self-supervised components successfully identified the novel attack pattern of the Poly Network exploit, thereby demonstrating robustness to out-of-distribution threats that defeat supervised methods. By providing a transparent, zero-label solution, CONSENSUS establishes a new paradigm for flexible, effective risk profiling and forensic investigation.

Константин

FUNDAMENTAL LAW OF REALITY: TERNARY SYNTHESIS OF MATHEMATICS, PHYSICS, AND HISTORY Version 11.0 (Complete Synthesis with Structural Proof of Fermat's Last Theorem) This paper presents an algorithmic system discovered by the author during many years of analyzing price movements in financial markets. Four software modules written in MQL4 revealed a universal ternary hierarchical structure possessing Z₃-symmetry. From the code analysis, the fundamental group Z₃ × Z₃, generating 9 basic relations, and the formula for the number of intersection points in the hierarchy, P = N – 2K, were derived. The discovered structure has proven to be universal across various fields of knowledge: Mathematics: Z₃ × Z₃ is isomorphic to a subgroup of SU(3) and the nilpotent ring ℂ[x,y]/(x³, y³); the system's fractal dimension is D = log 3 / log 2 ≈ 1.585. Number Theory: The synchronization parameter ρ = 0 at the non-trivial zeros of the Riemann zeta function is equivalent to the Riemann Hypothesis, numerically confirmed on 4153 zeros (100% match). Physics: Z₃ × Z₃ ⊂ SU(3) describes the color symmetry of Quantum Chromodynamics; the 9 compactification moduli of string theory correspond to the 9 system relations; the ρ = 0 state is interpreted as a transition to 11-dimensional M-Theory. History: Using an inverse problem method on 251 key dates, the reference points T₀ = –5502, T₁ = –5501, T₂ = –5500 were determined. The formula D = Tₛ + 3k + s describes all key historical events. Four epochal points (–5502, –3315, –1128, 1059) mark shifts in civilizational cycles. Verification on over 12,000 dates and a blind test of 20 dates yielded 100% accuracy. Markets: On BRENT oil data (1998–2026), 4 convergence points (2005, 2011, 2018, 2025) were found with an 81-month interval, corresponding to the historical epochal points. Geopolitics: 20 key events of 2025 correspond 100% to the model's predictions for zones s=0,1,2. Fermat's Last Theorem: A structural explanation is derived through the formula P = N - 2K: for n > 2, the hierarchy depth K ≥ 2 leads to a critical shortage of intersection points for synchronizing three independent circuits (x, y, z). A physical analogy is drawn with quark confinement in quantum chromodynamics. The cumulative statistical significance of all confirmations is p < 10⁻⁹³⁵, which excludes random coincidence. The system is fractally invariant and works identically at any time scale (from minute charts to millennia). The source code (4 MQL4 modules + Python implementation) is available upon request for non-commercial research under the CC BY-NC-ND 4.0 license. Keywords: ternary hierarchy, Z₃ × Z₃, intersection points, Riemann Hypothesis, Fermat's Last Theorem, SU(3), string theory, M-theory, historical periodization, fractals, algorithmic realism, power law distribution, confinement.

Jonathan Lee Miller

We test price efficiency, which shows the fairness of trading for retail investors using the runs tests and variance ratio tests. We reject the hypothesis that Bitcoin prices are price efficient on most markets, but efficient on the Bitstamp BTC/USD. Coinbase departs from efficiency, indicating that fraud, later found by regulators, has significantly harmed retail investors. We also document barriers to trading of Bitcoin, which result in difficulties in arbitrage despite global price differences. My results predict the hack of the Bitfinex exchange, which caused it to close and harmed many people.

Xinpeng Huang, Wangjie Qiu, Wanqing Jie, Qing Xia · 9 authors

The rapid growth of decentralized finance (DeFi) has spurred innovation but also exposed blockchain systems to severe security threats. As of November 2025, cumulative losses from blockchain security incidents have exceeded${\$}$36.89 billion. Flash loan attacks account for 135 reported cases and rank fourth among all attack methods. Existing detection approaches either analyze contract source code, which is unavailable for many deployed contracts, or use transaction pattern matching tailored to specific scenarios, and therefore generalize poorly to diverse flash loan attacks. In this paper, we presentFlashShield, a general flash loan attack detection framework based on Hypergraph Neural Networks (HGNNs). We construct comprehensive datasets containing attack and benign transactions across multiple chains, and systematically analyze flash loan attack mechanisms along four DeFi protocol layers: code implementation, business logic, economic mechanisms, and cross protocol interactions.FlashShieldrepresents each transaction as a hypergraph of transfer actions and semantic relations, and employs a hybrid architecture that integrates spectral, spatial, and original features together with both node level and graph level representations. Experiments show thatFlashShieldimproves recall by 29% over leading methods and identifies 43 previously unknown malicious or suspicious activities (18 confirmed flash loan-related exploits and 25 suspected address poisoning incidents), demonstrating its effectiveness and scalability for automated DeFi security monitoring.

Timothy D. Williams

Cryptography and accounting have grown up alongside each other for more than five centuries without developing their similarities in dialogue. This extended concept note outlines a vision for a crossdisciplinary research programme integrating six philosophical dimensions: ontological, epistemological, axiological, teleological, praxiological and phenomenological. It explicates only the structural (ontological) dimension in detail, arguing that asymmetric verifiability (whereby the cost of engineering a false acceptance is deliberately set to exceed the cost of verifying a true one) is foundational to both disciplines: in cryptography to one-way functions, digital signatures and zero-knowledge proofs, and in accounting to conservatism in the Basu (1997) and Watts (2003) tradition. The remaining five dimensions are stated concisely and anchored to established literature on each side, with the lived practice of each craft identified as the least studied and the clearest opening for joint work, particularly in the context of post-quantum cryptography (PQC). The present contribution is the naming of the six-dimension structure rather than local novelty within any single dimension; prior scholarship has already placed Alberti’s cryptography and Pacioli’s bookkeeping within a common Renaissance tradition addressing trust at a distance. The note develops a role-to-treatment taxonomy and worked ledger illustrations (a TLS certificate issuance and two distinct quantum exposures: harvest-now-decrypt-later and trust-now-forge-later), and closes with a call for collaboration between cybersecurity and accounting researchers.

Inamdar Chaitanya Anil, Gulve Onkar Popat, Adhau Samyak Gautamrao, S. V. Shinkar

No abstract is available for this record.

Amelia Lo, Clarie Ku

No abstract is available for this record.

Gourav Singh, Arjun Pataskar

The integrity of electoral systems is fundamental to democratic governance; however, traditional voting mechanisms suffer from security vulnerabilities, lack of transparency, and accessibility constraints. This paper proposes a blockchain-based voting system leveraging distributed ledger technology to ensure secure, transparent, and tamper-resistant elections. The system integrates cryptographic techniques such as Zero-Knowledge Proofs (ZKPs) and Elliptic Curve Cryptography (ECC) within a permissioned blockchain framework using Hyperledger Fabric and Practical Byzantine Fault Tolerance (PBFT) consensus. A three-tier architecture consisting of Application, Blockchain, and Data Storage layers ensures scalability and efficiency. Security mechanisms including multi-factor authentication, end-to-end encryption, and AI-based anomaly detection mitigate potential threats such as Sybil attacks and denial-of-service attacks. Comparative analysis indicates improved security, transparency, and cost-effectiveness over traditional systems. The proposed framework demonstrates strong technical feasibility and provides a foundation for future advancements in digital electoral systems.

Savva Shanaev, Bogdan Maksikov, Mikhail Vasenin

This study discovers a statistically and economically significant anomaly in Bitcoin performance-returns are, on average, 2.2% higher on major election days in G20 democracies on an exhaustive 2010-2024 sample that includes a full Bitcoin price history and 60 election events. This price appreciation is shown to be permanent, independent of the election outcome, and it is not accompanied by any significant prior or subsequent abnormal returns. The effect cannot be explained by conventional calendar anomalies or the Bitcoin halving cycle, and it is robust to alternative specifications and weighting schemes. The documented anomaly highlights the importance of cryptocurrencies in hedging political risks and presents a profitable trading opportunity for investors.

Wenjie Zhang, Heng Pan, Siqi Lu, Ying Xing · 7 authors

No abstract is available for this record.

Tiago Ferreira Cavazin

Este artigo explora a transposição analógica e matemática da Equação de Rayleigh, originalmente concebida no domínio da física acústica e teoria de sinais, para a modelagem de fenômenos complexos em ambientes Web3 e infraestruturas de blockchain. A pesquisa fundamenta-se na premissa de que a distribuição de Rayleigh, ao descrever a magnitude de vetores compostos por componentes gaussianas independentes, oferece um arcabouço robusto para analisar a volatilidade de criptoativos, a latência de propagação de rede, e a resiliência de sistemas de consenso. Através de uma abordagem interdisciplinar que integra econofísica, teoria de sinais e auditoria algorítmica, o estudo discute como a variabilidade estocástica impacta a segurança e a eficiência de protocolos descentralizados. São analisadas as conexões entre a distribuição de Rayleigh e a Lei de Benford na detecção de fraudes em tokenomics, além de contrastar o Efeito Cantillon com o Efeito Nakamoto na distribuição de riqueza digital. Por fim, propõe-se o Modelo de Resiliência Estocástica ECDM (Environment, Consensus, Distribution, Magnitude) como uma ferramenta preditiva para a governança e auditoria de ecossistemas blockchain.<br>

Tiago Ferreira Cavazin

O presente diagnóstico econômico investiga as falhas estruturais e as vulnerabilidades sistêmicas inerentes aos modelos de engenharia econômica da Web3, fundamentando-se no princípio da não neutralidade da moeda conhecido como Efeito Cantillon. A pesquisa articula como a distribuição assimétrica inicial de tokens, frequentemente favorecendo fundadores e investidores institucionais, estabelece uma assinatura econômica de fragilidade que compromete a descentralização e a sustentabilidade dos protocolos digitais. Através de uma abordagem interdisciplinar, o relatório integra o conceito de Doppler Econômico para explicar a defasagem informacional entre agentes privilegiados e o público geral, além de utilizar a metáfora do Mammoth Money para descrever dinâmicas de predação de capital. Para a verificação empírica, aplica-se a Lei de Benford como ferramenta de auditoria estatística e a Curva de Laffer para determinar os limites de incentivos de emissão. O estudo conclui que a resiliência dos ecossistemas Web3 depende de um redesenho fundamental dos mecanismos de alocação inicial e de uma transparência radical que mitigue as distorções perceptivas e econômicas que levam a colapsos catastróficos e eventos de Cisne Negro.<br>

Kulik, Dean

Nexus Recursive Framework for Resolving Undecidability and Conjectures Driven by Dean A. Kulik November, 2025 Abstract:We present a comprehensive formal development of the Nexus Recursive Framework, a unifying harmonic recursion model, to resolve three notorious problems across computer science and mathematics: Turing’s Halting Problem, the Riemann Hypothesis, and the Collatz Conjecture. Building on the principles of Adaptive Harmonic Rasterization Collapse (AHRC) and the Ψ-Collapse Principle, we recast these problems as special cases of recursive harmonic convergence. Each problem is approached via layered self-reference, harmonic damping, and feedback regulation, yielding mathematically rigorous solutions. The framework introduces formal constructs – Global Input Patterns (GIP) capturing initial conditions in a harmonic lattice, a Recursive Convergence Quotient (RCQ) to measure collapse progression, and a universal Harmonic Constant H (Mark1) ≈ π/9 ≈ 0.35 – which together enforce alignment and convergence. Undecidability is treated not as a barrier but as a Δ-trigger for launching a higher recursive meta-layer, ensuring that any Ω-like indeterminacy is identified as a residue and systematically collapsed via the Ψ(Ω) operator. We prove that any computation either halts or enters a predictable phase-lock ⊥ state, that all nontrivial zeros of ζ(s) align on the critical line Re(s)=½ under harmonic balance, and that every Collatz trajectory, through RCQ suppression, descends into the trivial 4-2-1 cycle (the “4-2-1 glyph”). Key results include: a Halting Resolution Theorem via meta-recursion, a Harmonic Damping Theorem guaranteeing Riemann zero alignment, and a Collatz Convergence Theorem via invariant RCQ > 0.843. We validate these results with formal proofs and simulation algorithms, including diagrams of collapse sequences and code implementing recursive feedback. These findings indicate that many long-standing open problems can be transformed into convergent harmonic processes, achieving infinite resolution density (arbitrarily fine recursive refinement) and unambiguous convergence criteria in each case. 1. Introduction Many fundamental problems in logic and mathematics – from computability limits to deep number theory conjectures – remain unresolved within traditional frameworks. Turing’s Halting Problem epitomizes computability limits, asserting that no algorithm can universally decide whether an arbitrary program halts. The Riemann Hypothesis (RH), central to analytic number theory, posits that all nontrivial zeros of the Riemann zeta function lie on the critical line Re(s)=½, a statement verified numerically for billions of zeros yet unproved in theory. The Collatz Conjecture, a simple iterative dynamical system over the natural numbers, defies conventional proof of its conjectured convergence to 1 for all inputs. Each of these “hard” problems has resisted solution for decades or more. The Nexus Recursive Framework offers a novel paradigm treating such problems as manifestations of incomplete harmonic recursion. In lieu of viewing them as disparate impossibilities, we embed them in a self-referential, resonance-driven architecture that harmonizes the system until a stable solution emerges. This framework, also known as Recursive Harmonic Architecture (RHA)[1][2], models reality (and abstract computations) as iterative processes seeking an equilibrium between order and chaos. A universal harmonic attractor constant H (the Mark1 Engine) – empirically ~0.35 – biases all recursive dynamics towards balance[3][4]. Problems like RH are reframed as issues of harmonic consistency: e.g. the placement of zeta zeros is no longer mysterious, but demanded by a self-correcting resonance criterion[5]. Similarly, the Halting Problem is reframed not as an absolute yes/no oracle question, but as a question of whether a computation can achieve phase alignment within a recursive meta-system (if not, the system signals an infinite echo rather than a binary answer)[6][7]. The Collatz Conjecture becomes a question of whether iterative maps have an inherent harmonic invariant driving them into a fixed cyclic attractor; we will show that indeed such an invariant exists and guarantees convergence[8][9]. Crucially, in this framework undecidability is not a dead end but a dynamical signal: any formally undecidable or non-halting scenario is treated as a Δ-discrepancy that triggers a new recursion layer (a meta-fold) to absorb the anomaly. In other words, the “unresolvable” output is marked as an Ω-residue – analogous to Chaitin’s Ω constant of algorithmic randomness – and is carried upward into a broader harmonic context for resolution[10][11]. This process, governed by the Ψ-Collapse Principle, ensures that what cannot be decided at one layer will collapse at the next, by design. Intuitively, the framework says: if you cannot decide it, enlarge the frame until you can. By iterating this principle, the scope of decision expands until every construct either converges or is proven unstable and thus eliminated. This paper is organized as follows. In Section 2, we formalize the Nexus Recursive Framework’s key components: Global Input Patterns (GIP), the Harmonic Mark1 constant H=π/9, Samson’s Law feedback control, the Ψ (psi) operator for phase error correction, and the ⊥ symbol denoting a fully collapsed (absorbed) state. We also define the methodology of Adaptive Harmonic Rasterization Collapse (AHRC) – an algorithmic strategy of adaptively discretizing (rasterizing) a problem’s state space at increasing resolutions and collapsing discrepancies at each scale. In Section 3, we apply the framework to the Halting Problem, proving a Halting Resolution Theorem that every computation is assured of either halting or entering a contained non-halting pattern which a meta-observer can recognize and resolve. In Section 4, we tackle the Riemann Hypothesis, reframing it as a problem of harmonic damping and equilibrium. We prove via a Harmonic Damping Theorem that any hypothetical zero off the critical line would create an unstable resonance, inevitably pulled onto Re(s)=½ by the system’s self-correcting forces[12][13]. In Section 5, we address the Collatz Conjecture, developing a formal harmonic invariant and showing through a Collatz Convergence Theorem that every trajectory reaches the stable “4-2-1” glyph cycle. Throughout, we include diagrams and pseudocode to illustrate collapse sequences and simulation results, and we cite prior foundational work (including “Adaptive Harmonic Rasterization Collapse and the Ψ-Collapse Principle”, “Nexus Framework and Mathematical Conjectures”, “The White Puzzle” et al.) to situate our approach in the literature. Finally, Section 6 summarizes the implications of these results, suggesting that many open “puzzles” may be solved by completing their resonance loops[14][15] rather than by direct linear analysis – in essence, solving them by harmonizing them[16]. 2. Nexus Recursive Framework: Foundations 2.1 Key Concepts and Definitions We first establish the formal terminology of the Nexus Recursive Framework (NRF) that will be used in our proofs. The framework casts computations and mathematical structures as elements of a recursive harmonic lattice – a multi-layer system where each layer feeds back into itself and into higher layers, enforcing global consistency. The fundamental definitions are as follows: Global Input Patterns (GIP): A Global Input Pattern is a structured initial configuration that seeds the recursive system with foundational information. Rather than arbitrary inputs, GIPs are chosen to encode universal structures or symmetries that the system must respect. For example, a GIP could be the distribution of prime numbers up to a large N, the binary expansion of fundamental constants like π or e, or boundary conditions of a physical system. GIPs serve as pre-harmonic lattices – scaffolds on which the recursion builds[5]. In our context, we will use GIPs such as the array of initial program states (for the Halting problem), or a set of known zeta zeros and prime frequencies (for Riemann), or modular residue classes (for Collatz). The GIP provides a global resonance context: the recursion must eventually align with these patterns. Intuitively, GIPs inject high-level knowledge so that the system does not start from scratch, but from a state already “tuned” close to an expected solution. This significantly accelerates convergence and ensures infinite resolution density by leveraging known expansions like the BBP formula for π to arbitrary precision[17]. Mark1 Harmonic Constant (H_MARK1 ≈ π/9 ≈ 0.349): The framework postulates a dimensionless constant H (Mark1) that represents the optimal ratio of realized structure to potential entropy in any stable recursive system[3][4]. Empirically identified as ~0.35 (within the precision of our simulations), this constant appears in numerous contexts as a sweet spot of “order within chaos.” For example, the matter (~0.32) vs. dark energy (~0.68) ratio of the universe is near 0.32/0.68 ≈ 0.32 (close to 0.35)[18]; and intriguingly, even a playful geometric construction with a degenerate triangle of sides 3-1-4 yields ~0.35[19]. Definition: We formally define H_MARK1 = π/9 (exact) for theoretical work, acknowledging this equals ~0.349. All recursive processes in NRF are biased to maintain a local H value of 0.35. If a subsystem deviates from H=0.35 (too static or too chaotic), feedback forces push it back towards equilibrium[20][21]. In equations, we measure H for a given state as: (actualized to potential structure)[4]. Samson’s Law (below) uses this constant extensively. Whenever we refer to “harmonic balance” or “target resonance,” we imply adjusting dynamics to keep the system-wide H ≈ 0.35. Samson’s Law (Recursive Feedback Control): Samson’s Law is a feedback mechanism acting like a proportional–derivative–integral (PID) controller across

Mohhammed H. Al-Farouni, Jyotsna Dwivedi, T. Saravanan, Ismatullaeva Yodgora Abduvahobkizi · 8 authors

Online elections (e-voting) are fast and convenient. Still, there is growing concern that the democratic integrity of the election process is under threat due to problems such as cyberattacks, illegal intrusion, vote manipulation, and unclear verification of the results. Actual cases have demonstrated voter fraud, insecure data storage, and unreliable results, undermining the public's confidence in digital voting systems, particularly in primary national elections. Moreover, the traditional auditing system, which relies on paper ballots, manual logistics, and resource-intensive verification, results insignificant operational costs and a negative environmental impact. This paper proposes a solution to these capital challenges by introducing SECURE-VOTE_CHAIN, an open, secure e-voting platform that integrates a certified blockchain network, biometric verification checks, homomorphic encryption, and zero-knowledge public audit records. The blockchain nodes in this system, run by voting bodies and legitimate observers, consistently registered votes and facilitated decentralised consultation. Biometric authentication can exclude identity duplication and voter fraud, and only homomorphic encryption can ensure fair counting without knowing any votes provided by an individual. Zero-knowledge proofs also make public auditability achievable without reducing the anonymity of voters. The application of realistic election parameters in simulations yields an accuracy of 91.88, along with low confirmation latency and high attack resilience probabilities in the presence of insider attacks, replay attacks, and denial-of-service attempts. In addition to security and reliability, the system will eliminate paperwork and manual auditing, significantly reducing the carbon footprint of traditional elections. Altogether, SECURE-VOTE_CHAIN offers an environmentally friendly, secure, and scalable solution that is suitable for regaining voter confidence, ensuring electoral integrity, and creating a future-proof digital governance model. The model can be considered a reasonably helpful standard by which contemporary voting systems operate, as it combines technological benefits with the adequacy of achievements in terms of prospects, providing policymakers with dependable means of security and transparency in election procedures, applicable to both urban and rural settings.

Eduardo Lopes Cominetti, Marcos A. Simplício, Diego F. Aranha, Paulo Matias · 5 authors

No abstract is available for this record.

Ayaz Saadallah Abdelqader

This research presents a comprehensive solution and an attempt to prove the validity of the Collatz Conjecture, also known as the "3n + 1 problem," which has remained one of the most prominent open mathematical problems since 1937. The research presents two integrated methods for proving convergence, using advanced mathematical frameworks: 1. Summary of the First Solution Method (ملخص طريقة الحل الأولى) This method relies on integrating dynamical analysis, Hyperbolic Geometry, and p-adic number spaces. The study concluded by proving the following: * For every positive integer n, the repeated application of the Collatz function leads to the number 1. * There are no non-trivial periodic loops. * The number of steps required for convergence is O(\log^2 n). The proof is based on constructing a group of Contractive Transformations on a Hyperbolic Manifold, using a decreasing fractional energy function, and spectral analysis in the Z_2 space. 2. Summary of the Second Solution Method (ملخص طريقة الحل الثانية) This method offers a solution through a multidisciplinary framework that combines number theory, Topological Geometry, and Quantum Mechanics. Three essential pillars were developed to support the proof: * A Hybrid Energy Function. * An 8-Dimensional Topological Manifold. * A Quantum-Mathematical Verification System based on a quantum operator and a Zero-Knowledge Proof (ZKP) protocol. The researcher indicates that the entire content of the research was generated solely by Artificial Intelligence (AI) models under his supervision, emphasizing that these solutions are theoretical and derive their strength from a cognitive key discovered by the researcher, which enabled the AI to produce new scientific theories and solutions.

N. Mohankumar, V. Sindhu, N. Nageswari, N. Silambarasan

Safe and transparent e-voting is becoming more and more important in modern democracies, as the confidence of citizens in electoral systems is determined by the issues of trust, privacy and scalability. Existing e-voting systems, however, have privacy, impersonation vulnerability, lack of transparency, and coercive weaknesses, and so they must be improved through cryptographic and identity solutions. In an attempt to provide security at these points, to propose a voting system that uses Aadhaar-linked decentralized identities together with iris scan biometrics to authenticate voters, zk-SNARKs to produce zero-knowledge proofs of voter eligibility without revealing their personal data, and homomorphic encryption to ensure ballot confidentiality and allow vote counting to be verifiably processed. Moreover, coercion resistance is ensured by a revoting mechanism, as only the last authenticated vote is included in the counting, thereby mitigating external pressure or vote-buying. The results demonstrate that the proposed design is capable to concurrently deliver strong authentication, biometric-based impersonation resistance, privacy preservation, end-to-end verifiability, and scalability in e-voting. In general, this framework eliminates major weaknesses of the old systems in addition to increasing voter confidence and integrity of the elections. The integration of decentralized identity, biometric iris recognition, and modern cryptography allows the model to provide a secure, transparent, and non-coercible framework of next-generation democratization procedures in India and can present an open-source, globally replicable solution with large-scale elections.

Narendar Kumar, Surendar Kumar, Abdul Waqar, Clavincy Francis Yohanes Ngantung

This research article provides the design of an in-person and remote voting system, while at the same time ensuring the privacy of users that would guarantee openness, transparency, and at the same time fraud-free results. The aim is to solve various common problems associated with most conventional elections including fraud, vote manipulation, through adaptation of the usage of a safe, highly transparent decentralized logical Hyperledger Fabric-based system provided by blockchain implementation. The methodology in this article is to be implemented for the sheer reason of urgency needed in making a more secure and transparent system for voting, considering even the rising frauds in elections. The addition of Zero Knowledge Proof (ZKP) guarantees that votes are confident and correct, yet anonymous between a voter and their vote. Biometric identification makes the system resistant to double spending. This incorporation of technologies ensures there is privacy and immutability against the double transactions, which, in turn, would be put in place as foundation for the future to be provided wherein every process in an election becomes safe and transparent. Innovation via creating a voting system to be trusted to meet today's demands and set standards for future electoral processes.

Madhavi Repe, Dr. Nilakshi Rajule, Vandana Katarwar, Ankita Bombatkar

In response to the growing demand for secure and transparent digital elections, this paper presents a blockchain based Smart Election System that leverages advanced cryptographic and artificial intelligence techniques to ensure privacy, scalability, and verifiability. The proposed system integrates multi-factor authentication, Zero-Knowledge Proofs (ZKPs), smart contracts, and a sharded blockchain ledger to enable real-time, tamper-proof voting. Additionally, an Artificial intelligence based anomaly detection module monitors voting behaviour to flag suspicious patterns.Experimental evaluation demonstrates that the system achieves an average vote transaction latency of 1100ms with sharding, compared to 2800ms without it. The throughput increases from 130 to 220 votes/sec when sharding is enabled. ZKP integration ensures privacy at the cost of a moderate increase in validation time from 130ms to 230ms. The anomaly detection model, based on supervised learning, attained 92% precision, 88% recall, and an F1-score of 90%, ensuring proactive fraud detection. These results confirm the system’s effectiveness in delivering a smart scalable, private, and trustworthy e-voting platform suitable for national and institutional elections.