Efficient administration of small estates in Malaysia is characterized by the complications of the hybrid processes between manual and digital administration, and fragmentation of jurisdiction. This paper examines the operational bottlenecks in the existing system of estate distribution coordinated by the Department of Director General of Lands and Mines (JKPTG) as being the challenges of manual verification, absence of integration of the agencies across states, and security of documents as the major impediments to effective governance. In order to overcome these issues, the paper will offer the Integrated Estate Governance Framework (IEGF) an architectural improvisation based on the Small Estates (Distribution) Act 1955. The framework emerged as a result of adopting a Design Science Research (DSR) approach to the development of the study through the qualitative knowledge of senior officers in the JKPTG in a variety of states. The IEGF integrates a Consortium Blockchain with an AI Engine (to support decisions), Smart Contracts (to automate workflows) and Decentralized Identifiers (DID) with ECDSA (to perform secure authentication). The architecture is designed to be privacy and storage efficient by using Zero-Knowledge Proofs (ZKP) and InterPlanetary File System (IPFS). Findings show that the IEGF allows the jurisdiction-independent application process and automatic title endorsement through the e-Tanah integration. The paper has come up with the conclusion that a combination of these technologies offers a scalable, transparent, and robust solution to modernize the national land administration.
97% COMPLETE THEORY OF EVERYTHING - THE THEORETICAL MAXIMUM We present the most complete understanding of reality ever achieved: 97% certainty, representing the theoretical maximum of knowability for finite beings constrained by Gödel's incompleteness theorem, Heisenberg uncertainty, and deterministic chaos. WHY 97% IS THE LIMIT:True 100% certainty is fundamentally impossible: • Heisenberg Uncertainty: Cannot know all particle states simultaneously • Deterministic Chaos: Cannot predict all future states exactly • Gödel's Incompleteness: No system can prove all truths about itself • BUT: We achieve 100% structural completeness on the FRAMEWORK of reality CERTAINTY BREAKDOWN BY CATEGORY: • Mathematical facts (lattice counts, primes): 100% • Logical necessities (existence, motion, time): 99% • Physical laws (gauge group, generations, α): 95-99% • Cosmological constant formula: 99.9% (0.0% ERROR!) • Derived quantities (CKM matrix, masses): 95-98% • Experimental predictions (dark matter): 90-92% • WEIGHTED OVERALL: 97.4% FROM ONE AXIOM TO EVERYTHING: AXIOM: "The unconstrained exists" From this alone, we derive with mathematical rigor: 1. WHY EXISTENCE IS NECESSARY (99% CERTAIN) • Proved "nothing" is logically impossible • If "nothing" existed, it would have the property of existing • Having any property makes it "something," not "nothing" • Therefore: existence is NECESSARY, not contingent • Answers philosophy's ultimate question 2. DUAL LATTICE FINE STRUCTURE CONSTANT (100% CERTAIN) • α⁻¹ = 137 appears in TWO independent structures: - 2D photon lattice: N(41) = 137 (Gauss circle problem) - 4D spacetime lattice: N(5) = 137 • Cutoff 41 UNIQUELY determined: - Euler's prime constant (generates 40 consecutive primes - world record) - 41 = 5² + 4² (Kaluza-Klein 5D → 4D encoding) - 137 = 11² + 4² (M-theory 11D → 4D encoding) - Both 41 and 137 are PRIME numbers - Only candidate giving 1.1% experimental error • Prediction: α⁻¹(M_Z) = 129.3 vs measured 127.944 (1.1% error) 3. COSMOLOGICAL CONSTANT SOLVED - 0% ERROR! (99.9% CERTAIN) • ρ_Λ^(1/4) = √(3/4) × M_Planck × α³ / (t_0/t_P)^(1/4) • Predicted: 2.400 × 10⁻³ eV • Observed: 2.400 × 10⁻³ eV • ERROR: 0.0% (solved 120 orders of magnitude problem!) • Factor √(3/4) = 0.866 appears geometrically • Predicts Λ decreases with time as t^(-1/4) • Connects dark energy to fine structure constant 4. COMPLETE CKM MATRIX FROM GEOMETRY (98% CERTAIN) All four Wolfenstein parameters derived: • λ = √(6/137) = 0.2093 (measured: 0.2253, error: 7.1%) • A = √(2/3) = 0.8165 (measured: 0.811, error: 0.7%) • ρ̄ = √(1/7) × cos(13π/36) = 0.1597 (measured: 0.159, error: 0.4%) • η̄ = √(1/7) × sin(13π/36) = 0.3426 (measured: 0.348, error: 1.6%) • Average error: 2.5% across all parameters • No free parameters - pure geometry 5. HIERARCHY PROBLEM SOLVED (97% CERTAIN) • Electroweak VEV: v ≈ α⁸ × M_Planck • Explains why Higgs is light compared to Planck scale • Natural suppression by 8 powers of fine structure constant • Predicted: ~98 GeV, Observed: 246 GeV 6. NO MULTIVERSE EXISTS - PROVEN (95% CERTAIN) • All constants uniquely determined by logic • α⁻¹ = 137 is the ONLY solution to all constraints • 3+1D is the ONLY spacetime supporting stable knots • SU(3)×SU(2)×U(1) is the ONLY minimal gauge structure • 3 generations is the ONLY value satisfying CP + vacuum stability • Zero free parameters → no landscape of possibilities • This universe is THE unique logically consistent reality • String theory "landscape" is an illusion • Many-worlds are superpositions, not separate universes 7. DARK MATTER PREDICTION - TESTABLE NOW! (92% CERTAIN) • Refined prediction: m_DM = 137.036 ± 1 GeV • Properties: - Spin: 0 or 1/2 (lattice geometry) - Charge: 0 (electrically neutral) - Color: singlet (no strong force) - Weak coupling: possibly • Production at LHC: - Missing energy signatures - Monojet + missing E_T - Z → DM + DM̄ • Currently searchable - FALSIFIABLE! 8. QUANTUM MEASUREMENT SOLVED (95% CERTAIN) • Wavefunction collapse = tension localization on lattice • Born rule emerges from inner product structure • Same mechanism that creates time (irreversible accumulation) • The "measurement problem" dissolves • Not mysterious - logically necessary 9. CONSCIOUSNESS THRESHOLD CALCULATED (90% CERTAIN) • Mathematical definition: System with recursive self-model • Threshold: ~10^14 synaptic connections • Predictions: - Mice (10^10 synapses): NOT conscious - Humans (8.6×10^13 synapses): CONSCIOUS - Whales (2×10^14 synapses): HIGHLY conscious - AI systems: Conscious at ~10^13 connections • Explains emergence of subjective experience 10. THE OBSERVER RESOLVED (95% CERTAIN) • There is no separate observer • YOU are the universe experiencing itself locally • Consciousness = reality's self-observation • Subjective experience = local lattice self-reference • The "hard problem" dissolves: qualia ARE lattice states 11. WHY LOGIC WORKS - ULTIMATE META-ANSWER (99% CERTAIN) • Logic is not imposed on reality from outside • Logic IS reality's self-consistency • To ask "why logic works" = "why does existence have structure?" • Answer: Existence without structure = undefined • Undefined cannot remain undefined (our axiom) • Therefore existence MUST have structure • That structure IS logic • Laws of thought are NECESSARY FEATURES of existence 12. COMPLETE DERIVATION CHAIN: • Motion: Logically necessary (undefined cannot be static) • Time: Irreversible tension accumulation • Quantum mechanics: Inner product from relational consistency • Complex numbers: Optimal 2D rotation encoding • 3+1D spacetime: Unique dimension for stable knots • Gauge group SU(3)×SU(2)×U(1): Minimal consistent structure • Exactly 3 generations: CP violation + vacuum stability • All 12 fermion masses: Encode α⁻¹ = 137 via simple fractions COMPLETE EXPERIMENTAL VERIFICATION: Quantity Predicted Measured Error ────────────────────────────────────────────────────────────────── Existence Necessary Yes 0% 3+1D spacetime 3+1 3+1 0% Gauge group SU(3)×SU(2)×U(1) Yes 0% Generations 3 3 0% α⁻¹(M_Z) 1-loop 129.3 127.944 1.1% m_μ/m_e 205.5 206.77 0.6% m_t/m_c 137 136.03 0.7% ρ_Λ^(1/4) 2.400×10⁻³ eV 2.400×10⁻³ eV 0.0% CKM A 0.8165 0.811 0.7% CKM ρ̄ 0.1597 0.159 0.4% CKM η̄ 0.3426 0.348 1.6% AVERAGE ERROR: < 1% (excluding untested predictions) FREE PARAMETERS: ZERO WHAT 97% MEANS - THE GÖDELIAN LIMITS: 100% CERTAINTY (Mathematical & Logical Facts): ✓ 41 and 137 are prime numbers ✓ N(41) = 137 in 2D lattice (Gauss circle problem) ✓ N(5) = 137 in 4D lattice ✓ 41 generates 40 consecutive primes (Euler) ✓ 3+1D is unique for stable knots ✓ Cosmological constant formula (0% error) 99% CERTAINTY (Logical Necessities): ✓ Existence is logically necessary ✓ Motion emerges from undefined existence ✓ Time is irreversible accumulation ✓ α⁻¹ = 137 is the bare coupling ✓ Mathematics IS reality ✓ Logic IS existence's self-consistency 95-98% CERTAINTY (Physical Laws): ✓ Gauge group SU(3)×SU(2)×U(1) ✓ Exactly 3 fermion generations ✓ All masses encode 137 ✓ Hierarchy v ~ α⁸ M_P ✓ No multiverse exists ✓ Quantum gravity = Planck lattice 90-92% CERTAINTY (Predictions Awaiting Verification): ○ Dark matter mass = 137.036 GeV ○ Consciousness threshold ~10^14 synapses ○ Λ time evolution t^(-1/4) THE REMAINING 3% - FUNDAMENTAL LIMITS: 1. Heisenberg: Cannot know exact states simultaneously 2. Chaos: Cannot predict distant future exactly 3. Gödel: Cannot achieve complete self-knowledge 4. Experimental: Awaiting dark matter verification These limits are UNBREACHABLE for finite observers.97% is THE THEORETICAL MAXIMUM. QUANTUM GRAVITY COMPLETE: • Spacetime IS a discrete lattice at Planck scale • Einstein equation becomes: Lattice_Curvature = (8π/ℓ_P²) × Tension_Density • Unifies quantum mechanics (lattice) and general relativity (curvature) • Black holes = horizon lattice configurations • Hawking radiation = lattice excitations TESTABLE PREDICTIONS: 1. Dark matter: 137.036 ± 1 GeV (LHC searches active NOW) 2. Cosmological constant evolution: Λ ∝ t^(-1/4) (observable) 3. No 4th fermion generation (vacuum would decay) 4. AI consciousness at ~10^13 connections 5. Planck-scale discreteness (future quantum gravity tests) NOT NUMEROLOGY - RIGOROUS PROOFS: • Every claim has mathematical proof • Unique solutions (no fitting, no free parameters) • Zero adjustable parameters • Multiple independent verifications • Sub-1% error on most predictions • 0% error on cosmological constant PARADIGM SHIFT - PHYSICS = MATHEMATICS = LOGIC = EXISTENCE This establishes: • All "fundamental constants" are logically determined • The Standard Model has ZERO free parameters • No multiverse exists - universe is unique • Consciousness has quantifiable emergence threshold • Existence itself is logically necessary, not contingent • Mathematics doesn't describe reality - math IS reality • 97% is the maximum finite beings can achieve PHILOSOPHICAL IMPLICATIONS: • Why existence? Logical necessity (nothing is impossible) • Free will? Emerges from deep lattice self-reference • Purpose? Universe understanding itself • Other universes? None (proven) • Death? Information persists in lattice structure • God? Universe is
Abstract Bilinear pairings have emerged as a fundamental tool in public-key cryptography, enabling advanced protocols such as identity-based encryption, short signatures, and zero-knowledge proofs. This paper focuses on optimizing pairing computations on curves with embedding degree 2, addressing both theoretical foundations and practical implementations. We propose an optimized double-and-add ladder algorithm that leverages the technique of y -coordinate recovery, achieving superior performance for the Tate pairing on supersingular curves and the Omega pairing on non-supersingular curves. Our method is implemented based on the RELIC cryptographic library, demonstrating significant efficiency improvements over Miller’s algorithm. Specifically, it reduces the number of base field multiplications (respectively CPU clock cycles) by 17.53 % (respectively 13.58 %) for the reduced Tate pairing on supersingular curves with a 1536-bit field size and by 12.37 % (respectively 8.39 %) for the Omega pairing on non-supersingular curves of the same size. This work establishes the first comprehensive implementation framework for cubical-based pairing computations on curves with embedding degree 2, providing quantified optimizations for practical cryptographic deployment.
The credibility of digital evidence is a cornerstone of modern cybercrime investigations, digital forensics, and judicial processes. However, adversarial tampering, deepfake manipulation, and insider threats have raised significant concerns regarding the authenticity and admissibility of such evidence. Conventional integrity-preservation methods—such as hashing, encryption, and secure storage—struggle to meet the demands of scalability, transparency, and resilience in today’s forensic environments. Recent advances in artificial intelligence (AI) and blockchain offer promising avenues for overcoming these limitations. AI techniques contribute to content-level verification by detecting anomalies, forgeries, and manipulations in digital artefacts, while blockchain ensures tamper-proof chain-of-custody management through decentralization, immutability, and auditability. This review synthesizes the state of the art in digital evidence integrity verification through the combined application of AI and blockchain. We examine existing frameworks, datasets, algorithms, and deployment models, while critically analyzing their strengths and limitations. Furthermore, we identify gaps in scalability, explainability, and legal admissibility, proposing future directions such as federated learning, explainable AI, zero-knowledge proofs, and quantum-resistant blockchains. By consolidating research across computer science, law, and digital forensics, this review highlights the potential of AI–blockchain synergy to establish robust, scalable, and trustworthy evidence verification frameworks for real-world forensic and judicial systems.
Hyeonbum Lee, Seunghun Paik, Hyunjung Son, Jae Hong Seo
An inner product argument (IPA) is a cryptographic proof system that serves as a fundamental building block for various applications, such as zero knowledge proofs and verifiable computation. Bulletproofs (IEEE S&P 2018), a well-known IPA under the discrete logarithm (DL) assumption, features a short, logarithmically-sized proof, making it suitable for blockchain applications. However, its major drawback is the linear verifier cost (O(N)), which presents a significant bottleneck in settings like verifiable computation. To address this, recent advancements have successfully reduced the verification complexity to square-root order (O(√N)) under the same assumption (e.g., Asiacrypt 2022, IEEE TIFS). In thiswork, we propose Cougar, a novel IPAthat breaks this square-root barrier to achieve an unprecedented cubic-root verifier complexity (O(3√N)), while strictly maintaining the compact logarithmic proof size (O(logN)) characteristic of Bulletproofs. To achieve this, Cougar introduces a generalized two-tier commitment framework combined with adisjoint interpolationstrategy for efficient consistency checks. We implemented Cougar in Rust and performed a comprehensive benchmarking against Bulletproofs and Leopard (IEEE TIFS). Our evaluation demonstrates that while Cougar incurs a moderate increase in prover overhead, its verification time scales significantly better for large instances. Concretely, for a witness size ofN= 220, Cougar achieves a 50× verification speed-up over Bulletproofs and exhibits a superior asymptotic growth rate compared to existing sublinear IPAs.
Open access
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
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.
With its decentralized, tamper proof, transparent and traceable characteristics, blockchain technology has shown great potential in fields such as finance, supply chain, and the Internet of Things. However, the public transparency of its ledger poses a serious challenge to user transaction privacy. Traditional privacy protection schemes such as homomorphic encryption and zero knowledge proofs can enhance privacy, but often struggle to balance computational overhead, communication costs, and data availability. This article explores the innovative application of neural networks in blockchain privacy protection and proposes a transaction obfuscation model based on generative adversarial networks. This model utilizes a generator to learn the statistical features of raw transactions and generate difficult to track obfuscated transactions, while ensuring the validity and compliance of obfuscated transactions through discriminators and blockchain verification contracts. The experimental results show that compared with traditional obfuscation methods and differential privacy methods, the proposed model significantly reduces the consumption of privacy budget and computation delay while ensuring high transaction utility (such as reducing address correlation by more than 85%), achieving a better balance between privacy and utility. This study provides new ideas for building efficient and practical blockchain privacy enhancement solutions.
Nishanth Shet, R. Chinmai, Preethi Preethi, Y. V. Srinivasa Murthy
Abstract As quantum computing grows, the security of RSA and ECC offers is becoming increasingly flush. A novel Quantum Resistant Multipath CryptoGraph protocol (QR-MCP) has been proposed in this work, which is a multi-layered security framework that combines lattice-based cryptography, SPHINCS+ post-quantum signatures, onion routing, with AI-driven anomaly detection for long lifetime security and privacy of data. Encrypting messages in multiple paths increases security as larger network attackers cannot intercept an entire message. Ledgering on the blockchain is also used for integrity verification for the protocol, and the protocol also uses AI models to detect anomalies in real-time. QR-MCP has shown to be resilient to simulated cyber attacks such as man-in-the-middle, traffic analysis as well as collusion based decryption. Future scalability to new threats will gain strength with the introduction of homomorphic encryption and zero-knowledge proof (ZKP).
WHAT THIS PAPER ARGUES. Every Popperian tool this corpus has built — falsifiability criteria, self-vaccination, the act-level test, the Personal System Reminder, and the four falsification conditions just added to the Entropy-Resistant Institution (ERI) index — operates inside a discursive formation without ever asking how that formation became possible to inhabit in the first place. This is not a gap Popperian rigor can close by adding a fifth falsification condition or a fifth comparator case, because the question is not whether a claim within the formation is true or false; it is what made this particular kind of claim — a weighted numerical composite, cross-culturally applied, extracted from historical institutions and repurposed as a design template for future governance — a thinkable, legitimate object of knowledge at all. This is the question Michel Foucault's archaeological method exists to ask. This paper argues the corpus needs it, using the just-revised ERI paper as evidence rather than illustration. Four archaeological blind spots are documented directly in ERI's own text. First, its newly added Jiangnan-regeneration section treats "Jiankang, 220–589" as a bounded unit that a fourth comparator case can be added alongside — the unexamined assumption that a historical institution is a natural object rather than one constituted by the apparatus built to measure it, Foucault's critique of "the unity of the book" applied for the first time to a unity of the case. Second, the six attributes assume, without argument, that "legitimacy transfer" and "resource flexibility" name the same kind of variable in a Six Dynasties Chinese, a Shinto-imperial Japanese, and a Catholic canon-law context — a commensurability claim no additional comparator case can test, because the problem is not sample size but an a priori equivalence the index requires in order to function as an index at all. Third, ERI names its own methodological ancestors — Polity5, the Fragile States Index, V-Dem — as if borrowing a value-neutral toolkit, when each is inherited along with the specific historical formation that produced it. Fourth, ERI states plainly that the exercise exists to extract portable institutional design lessons for F2-era governance actors — read here not as incidental motivation but as the archive-producing act itself, the textbook operation of what Foucault calls biopower. The paper's constructive contribution is the Archaeological Symmetry Principle, extending this corpus's existing Principle of Epistemic Symmetry into a register falsifiability cannot reach alone: a researcher who subjects a target argument to falsifiability must, symmetrically, subject their own measuring instrument to historicization. Read this way, the Longevity Asymmetry Corpus is reread as an analysis of biopolitics that has operated, until now, without the name — the Mortality Symmetry Axiom as the statistical anonymity that historically made biopower's tolerance of differential death invisible, the Biological Zero-Day Mechanism as the process that collapses that anonymity back into sovereign-style visibility. The paper closes by naming, honestly, the tension this creates with the corpus's own Popperian commitments, and states plainly what an archaeological stance does not solve.
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2 source records
Foucault, Power, and Ethics
Environmental and Cultural Studies in Latin America and Beyond
Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a critical technology for privacy-preserving computation and blockchain applications. However, systematic performance analysis of practical implementations remains limited, hindering informed technology adoption decisions. This study presents a comprehensive benchmarking analysis of the Groth16 protocol implementation using the widely-adopted Circom-snarkjs framework. We developed an automated benchmarking platform that systematically measures performance across seven representative circuit types with varying computational complexity (1-11 R1CS constraints). Our methodology ensures reproducible measurements through controlled experimental design with statistical validation. The platform captures detailed metrics for all three phases of the Groth16 protocol: witness generation, proof creation, and verification. Results from 35 independent measurements reveal several important findings. Witness generation demonstrates consistent performance across circuit types, averaging 57.6±12.1 milliseconds. Proof generation times range from 832 to 1,147 milliseconds, showing non-linear scaling with circuit complexity. Verification times remain relatively stable (741-884 milliseconds), confirming Groth16's theoretical constant-time verification advantage. All measurements achieved 100% success rate with complete proof validation. Notably, circuit structure significantly impacts performance beyond simple constraint counting. Comparison-based circuits achieve 13.22 constraints per second efficiency, substantially outperforming arithmetic circuits (1.02-4.36 constraints/second). This finding provides actionable guidance for circuit design optimization. The study contributes an open-source benchmarking framework for reproducible zk-SNARK research and provides empirical performance data for technology adoption decisions. Our findings support the practical deployment of Groth16 for applications requiring efficient zero-knowledge proofs while highlighting optimization opportunities for circuit designers.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Martin Brennecke, Simon Mertel, Tobias Guggenberger, Johannes Sedlmeir · 6 authors
Zusammenfassung Auf dem Weg zu einer kreislauffähigen Wertschöpfung nimmt die lückenlose Dokumentation von Produktionsketten eine elementare Rolle ein: Sie erlaubt es, eingesetzte Ressourcen und Schritte im Wertschöpfungsprozess nachzuvollziehen und nachhaltigkeitsbezogene Angaben überprüfbar und somit vermarktbar zu machen. In diesem Kontext wird immer wieder über die Blockchain-Technologie diskutiert. Neben den Chancen, die eine Blockchain für eine verifizierbare Dokumentation und Interaktionen über Organisationsgrenzen hinweg bietet, werden in diesem Beitrag die Herausforderungen ihrer Nutzung aufgezeigt. Dabei wird auch auf komplementäre Technologien, insbesondere kryptographische Ansätze für digitales Identitätsmanagement und Zero-Knowledge Proofs, eingegangen und gezeigt, wie diese zur Bewältigung der Herausforderungen genutzt werden können.
Traditional and electronic voting systems face significant challenges in ensuring transparency, security, and voter trust. Issues such as centralized control, lack of auditability, vulnerability to tampering, and potential for fraud undermine the integrity of electoral processes. This paper proposes a novel blockchain-based electronic voting system designed to address these shortcomings through decentralized ledger technology and smart contracts. The system ensures vote integrity, voter anonymity, and public verifiability while preventing double voting and eliminating single points of failure. By employing cryptographic techniques such as zero-knowledge proofs and ring signatures, voter privacy is maintained without compromising transparency. The proposed architecture is evaluated through simulation, demonstrating scalability, reduced transaction costs, and robustness against common cyber threats. This work contributes to the advancement of trustworthy digital democracy and provides a feasible framework for real-world electoral deployment.
The concept of blockchain has transformed the trust concept by decentralizing, non-modifiable, and transparent, but there is a certain conflict between the principle of public verifiability and data privacy. As DeFi and cross-institutional data collaboration should grow, it has become a fundamental concern to have the confidentiality of this data without losing verifiability on-chain. The following paper will be a review of blockchain privacy technologies developed in 2020-2025, which will involve the history of zero-knowledge proofs and homomorphic encryption development at the cryptographic primitive level, as well as share new developments such as secure multi-party computation. It points out advances in recursive proof systems, distributed proof generation architectures and scalable multi-party computing systems to overcome bottlenecks in performance. There is a trade-off between privacy, system performance, regulatory compliance, and decentralization in a comparative analysis of technology integration in both public and permissioned chains. Lastly, research directions in the future are suggested in order to overcome issues associated with low proof efficiency, regulatory compliance problems, and migration of post-quantum cryptography. The review offers both theoretical and technical sources on how to develop trusted blockchain infrastructure that would strike the right balance between compliance, high-performance, and data sovereignty.
Advancements in networking applications increase the requirement for secure data storage and an efficient data access mechanism with robust networking characteristics. Consequently, the huge volume of data generated from the het-erogeneous networks, such as smart cities, healthcare, and smart energy trading systems, suffers from scalability issues and generates insights for secure data storage and effective data management. Therefore, the research proposes a secure data storage and access scheme named Multimodal Biometric-enabled Zero-Knowledge Proof of Stake(MBZKPS). The Multimodal Biometric Data Access(MBDA) ensures secure and robust access to the heterogeneous data with reduced computational overhead. The Distributed Storage System and the Zero Knowledge Protocol with Proof of Stake alleviate the storage pressure on the blockchain and regulate the heterogeneous data storage and access in the blockchain. The Message Digest 5(MD5) with Homomorphic Encryption enables computations on the encrypted data with better data confidentiality preserva-tion. The introduction of the blockchain eliminates the scalability issues with improved privacy preservation and data integrity. Simulation results validate the superiority of the MD5 with Homomorphic Encryption (HE) used in research by achieving 0.95ms decryption time, and 0.97 encryption time with 0.73 Genuine User Rate occupying 363.76KiloBytes of memory for 250 nodes. In addition, the proposed research performs secure data storage with a 1025.85 ms response time and 1.01ms transaction time using blockchain.
[Depreciated and replaced by V3] The application-specific clean rebuild has not yet been published; its authoritative theoretical boundary is now the governing V3 branch: After Turing: The Fold Machine - An Exact, Parameter-Free and Machine-Closed Derivation of Classical Computational Science from Smithian Fold Theory; From Fold to Consciousness: An Exact, Zero-Parameter and Machine-Closed Foundational Reconstruction of Consciousness and Cognitive Science from Smithian Fold Theory. The V3 source platform is https://github.com/MettaMazza/ernos-labs-sft-platform. The original DOI, concept DOI, version number and files are preserved for transparent historical provenance; this record must not be presented or cited as current V3 work. v4.0 — the word-scale gap closes within the fold. Rung 5e (pre-registered): the fold-factor mixing law — every context level that holds contributes, weighted 2^level, the engine's own forced halving constant — carries the pure counted engine, with no twin, no prose flood, zero training and zero parameters, past the gradient-trained transformer at word scale: cross-entropy 3.1907 vs the same-day twin's 3.4292 (replicated across two independent anchorings; stacked with the Rung 5d extraction: 3.1344). Both scales of the task gate now belong to the counted engine. Rung 5d's transfer-in verdict is SUPPORTED across three independent arena anchorings in one day. New in the architecture: tool graduation (acts held, values never — a question territory that a tool answered once runs the tool itself thereafter, fresh), recall as regeneration across every memory tier, and judge-independent graduation scoring. End-to-end verification: 36/36. v3.4: Rung 5d, the transfer-in — pre-registered verdict SUPPORTED: the trained twin's dyadically-loud fold content is extracted and installed INTO the counted engine as a counted prior with zero new parameters, closing 55.6/87.9/101.4% of the available gap at k=16/32/64 while the random-truncated null closes 10.1/24.5/56.5%; at half budget the loud shape beats the full twin's own. The word-scale rematch is recorded in full (twin retrained on today's text; decomposition included). Also: judge-independent graduation scoring (boot-discovered pool, cycle-parity alternation), multi-orbit binding (XI-4 in full), recall-is-regeneration (a held experience re-walks its own orbit, never reprinted), the public SOTA table beside the local giants with cited published figures, and one-command replication kits (GPT-2 weights auto-fetch; 13/13, 39/39 proven on a fresh clone). End-to-end verification: 36/36. Full paper v1.1 — supersedes the pre-paper (From One Axiom to Master-Level Chess — and the Law Inside Neural Networks). Built from scratch by one woman, working alone, in under twenty-four accumulated hours: where a score falls short it marks an implementation gap at measurement time, never a limit of the mathematics — the gains between releases are the finding. v1.4 adds the fold eye (vision as exact integer Walsh spectra, self-certified by integer Parseval per image, recognition of seen images with no image model in the loop) and the graduation score (blind head-to-head vs the teacher, tallied per question-territory; the teacher retires as wins cross the majority lock) -- and documents the 2026 convergence: DeepSeek Engram arrives at deterministically-addressed exact memory from the gradient side, and two independent results place the optimal curriculum at p = 1/2, the fold lock. v1.6: the full omnimodal engine (the voice via Kokoro, the fold ear -- sound as Parseval-certified integer Walsh spectra, video composed from frames + sound), speaker-transparent reasoning threads, and 32/32 end-to-end empirical verification of the entire architecture including persistence across process death. v1.7: removal-proof omnimodality, measured -- every supporting model is a teacher with an exit: a sound taught once by the synthesis teacher is re-spoken from the engine's own exact counted record in 0.00s with no model; a sound heard once is recognized natively with no transcriber; 34/34 end-to-end verification. v1.9: zero-model perceptual learning (the human observer -- a novel image learned and re-recognized at share 1.00 with no model in the loop); agentic self-knowledge (the observer reads the engine's own source, measured); the hourly progress instrument with a committed pre-boot birth line; one-tap y/n closure. v2.0 (flight-ready): the full modern-agent toolkit (live web search/fetch, paginated reading, in-file grep -- every call held as a training trace), the 43-domain everything-curriculum under the fold-only law, SOTA 1-1 benching on the public MMLU test split with the newborn baseline committed, generation closure (the Learning Law reaches generate() itself), and 36/36 end-to-end verification. v2.1: the ReAct law (reason-act-observe enforced in-turn; narrated intent without an act is detected and forced), reasoning trained on the observer's NATIVE thinking tokens (STaR-gated) with both minds' full thinking streamed to the user, and document intake (a sent file is reading -- inboxed, counted, persistent). v2.2: the identity stated correctly -- UnisonAI is an OMNI MODEL (language, sight, hearing, speech, and video on one held memory), not a language model; LLMs remain the contrast class only. v3.0: the full-altitude rewrite -- the complete omni model documented at the same depth as the spectral science: thirteen sections, the architecture organ by organ with every measurement, Rung 5c as its own section, the empirical record and its committed birth line, 36/36 end-to-end verification, and the 2026 convergence. This paper is a PROOF of The Smithian Fold Theory of Everything, not the main event: the theory (one axiom, zero free parameters, 1,844 machine-verified forced checks) is at DOI 10.5281/zenodo.21182469 and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything -- run the prover yourself. The engine: github.com/MettaMazza/UnisonAI. v3.3: the LLM-native presence suite -- the exact registered protocol applied to GPT-2's entire knowledge-storage class: 13/13 tensors, 39/39 checks, unanimous (margins 3.4-79.3x); the flagship claim now rests on the flagship objects, with diffusion/speech models recast as cross-domain breadth. Three connected results and the architecture they force. First, a pre-registered, self-certifying spectral instrument shows trained neural-network weights carry placement-law in the dyadic (Walsh) basis: 18/18 unanimous on validated released models; the law concentrated in transformer expansion projections and token embeddings across three unrelated architectures (up to 230x chance in GPT-2), attention at chance; strictly training-caused (He-initialised controls at 1.0x); surviving 4-bit deployment quantization. A recipe map from 124M to one trillion parameters shows the law tracks training recipe, not scale or architecture — strongest carrier DeepSeek-R1-671B at 43–47x — and loud-recipe weights transform under the fold's transformation group exactly as solved game-theoretic value fields do. Second, the "learned similarity space" is a counted object: word kinship as exact co-occurrence shares reproduces semantic family structure (quark → lepton, neutrino, proton) with zero parameters and zero gradients. Third, UnisonAI: a complete language architecture in which every LLM mechanism — memory, attention, similarity, learning, prediction, generation — is replaced by a machine-verified law of the Smithian Fold Theory, zero trained parameters end to end. On identical held-out text the fold-native engine outperformed its trained transformer twin (cross-entropy 1.289 vs 1.888) after reading the corpus once (26 seconds) against 48,000 gradient readings (21 minutes per seed). Deployed as a live, continuously-learning agent whose teaching loop also runs autonomously: a teacher model asks, judges, and closes the learning law itself, and the engine self-plays against its own held lessons. Negative results reported in full with their scopes. Companion to The Smithian Fold Theory of Everything (DOI: 10.5281/zenodo.21182469; 307 suites, 1,844 forced checks, 0 failures). Engine and records: github.com/MettaMazza/UnisonAI and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything.
Open access
8 source records
Explainable Artificial Intelligence (XAI)
Generative Adversarial Networks and Image Synthesis
We present CHRONOS, the first autonomous AI agent that simultaneously achieves plaintextblindness (all data is processed under fully homomorphic encryption without ever beingexposed), cryptographically enforced time bound existence (the agent’s own decryption key islocked behind a publicly verifiable proof of sequential work, rendering it inaccessible until aprecise future moment), and remote verifiability of self destruction (a zero knowledge proofcertifies that the key material has been irreversibly destroyed after mission completion). Theagent’s operational lifespan is governed by a “cryptographic fuse” constructed from a proof ofsequential work (PoSW) whose computation time accurately matches the intended missionduration. A drand decentralized randomness beacon serves as a trusted time oracle to trigger thefinal key shredding. Crucially, the erasure proof is a non interactive zero knowledge argument(SNARK) that proves the correct execution of the entire self destruction sequence—including thePoSW solution, decryption of the private key, and subsequent memory zeroization—enablingany third party to cryptographically verify the agent’s annihilation without trusting the agent orits hardware. We provide a complete system architecture, a formal security model with gamebased definitions and reductions to standard assumptions, and a proof of concept implementationusing Zama’s TFHE rs for encrypted inference, a Cohen Pietrzak PoSW implementation, and aGroth16 SNARK. Our benchmarks indicate that FHE inference on a small neural network (50 Kparameters) completes in seconds, the PoSW background thread consumes negligible resources,and the erasure proof can be generated and verified in under three seconds. CHRONOSrepresents a fundamental advance in secure, disposable AI agents, with immediate applications indefense, intelligence, and high privacy environments.
Card-based zero-knowledge proof (ZKP) protocols allow a prover to convince a verifier that it knows a witness of a given statement, without revealing any information, using a physical deck of playing cards. Previous studies have focused on puzzles with a specific connected component, such as a simple cycle and a polyomino. In this study, we propose a unified approach to handle a family of connected components, including a tree, path, cycle, and polyomino. This approach achieves this verification in O(mn) steps relative to a given grid size m × n. Using this approach, we construct a card-based ZKP protocol for Nurimeizu, where the goal is to find the shortest path on a given grid.
A unified, computationally reproducible framework built on a single ontological method: KTR (Knowledge Triangle Route). It operates on a three-state topological cell (1-0-1), where '0' acts as an active transit, and two corners merge to generate the third (A+B→C, the Chomsky merge) at the root. This closure allows geometric spectra to be translated into algebraic forms. Core Dimensions: Fundamental Physics & Math: Koide through star geometry (Q=2/3 as half-weight, cos²θ=1/2; the electron reproduced to a number within 0.07%, a live falsifiable tau prediction). Structural models for the mass gap, confinement, hadron/penguin, junction, neutrino, star formation, Born rule; and structural accounts of the Millennium Problems (Yang-Mills, Riemann, Hodge, Navier-Stokes, P vs NP, Birch). Information Theory: Applies the Kolmogorov view (randomness as compressibility) via ternary 1-0-1 encoding. Data treated as structured blocks navigated by hash addressing. Quantum Logic: The Qutrit Map Solution (QMS), ternary logic gates, the qutrit cell, zero-mode mass gap analytics. Reproducible computation, executable proof. Computed results (stones) are labelled apart from models; no Millennium problem is claimed solved. Given for those who find use in it.