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8,484 results · page 57 of 354
Jophiel Arevalo Enriquez, Babu Pillai, Aravinda S. Rao, Vallipuram Muthukkumarasamy
No abstract is available for this record.
Omar Cheikhrouhou
No abstract is available for this record.
X. Liu, Anyang Qi, Lanying Liang, Lu Peng · 10 authors
No abstract is available for this record.
Shilpa Mahajan, Garima Sharma, Ambika Thakur, Laxmi Upadhyay · 6 authors
No abstract is available for this record.
Shumin Zhang, Shumin Zhang, Wenming Wang, Weidan Shi · 6 authors
No abstract is available for this record.
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).
Thi Bich Hue Tran, Thien Nhat Quang Le, Tra Huong Thi Le, Long Quoc Nguyen · 5 authors
No abstract is available for this record.
HUYNH GIA BAO
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.
Oleksandr Kuznetsov, Yulia Khavikova, Valerii Bushkov, Dmytro Shchytov · 5 authors
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.
Mehdi Beriane, Muhammed Ali Bingöl
No abstract is available for this record.
Matthew Rosendin
No abstract is available for this record.
Liang Xue, Xiaodong Lin, Xuemin Sherman Shen
No abstract is available for this record.
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.
Mrs.Dhanalakshmi.J, Gokul Pandi.P, Gurumoorthi.P, Ragul Pranav.A
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.
Liang Xue, Xiaodong Lin, Xuemin Sherman Shen
No abstract is available for this record.
Darío Valarezo-Castañeda, Aitor Gómez-Goiri, Cristina Regueiro
No abstract is available for this record.
Yujia Xian
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.
Madalina Bolboceanu, Jonathan Bootle, Vadim Lyubashevsky, Antonio Merino-Gallardo · 5 authors
No abstract is available for this record.
Gunjan H. Deshmukh, Mahesh R. Sanghavi
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.
Kunal Kumar Mandal, Abhoy Chand Mondal
No abstract is available for this record.
Aitor Gómez-Goiri, David García-Estévez, José-Tomás San-José Lombera, Iván Gutiérrez-Agüero
No abstract is available for this record.
Jiazheng Lin, Yingying Wang
ABSTRACT The increasing complexity and interdependence of global supply chains necessitate innovative solutions to enhance collaboration while safeguarding data privacy. This paper presents a lightweight multi‐blockchain framework designed to address the challenges of privacy‐preserving collaboration in Internet of Things (IoT)‐driven supply chains. By integrating multiple blockchain networks, the proposed framework ensures data confidentiality, integrity, and traceability across various stakeholders. The system employs advanced cryptographic techniques, including zero‐knowledge proofs and differential privacy, to protect sensitive information during data exchange and processing. Additionally, the framework incorporates lightweight consensus mechanisms to accommodate the resource constraints of IoT devices. Experimental evaluations demonstrate the effectiveness of the proposed framework in improving data privacy and system scalability compared to existing solutions.
Hailang Cai, Yuwei Xu, Tianhua Li, Qiao Xiang · 6 authors
No abstract is available for this record.
Maria Smith
[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.