Blockchain Papers

Zhongkai Shen, Jinan Gu, Juan Liu, Tao Xiong · 7 authors

No abstract is available for this record.

Cristian Campos Ferrer, Angeles G. Navarro, Sonia Gonzalez-Navarro

No abstract is available for this record.

Uzma Shereen, Lubna Nausheen

This research introduces a novel Unified Quantum-Resilient Blockchain-Zero Knowledge Proofs Privacy Authentication Framework (QBC-ZKPAF) aimed at enhancing security in IoT environments. The system combines post-quantum cryptography, blockchain technology, and Zero Trust Architecture (ZTA) to provide secure communication, access management, and privacy-preserving authentication. It uses a Deep Q-Network Multi-Factor safe Key (DQN-MFSK) for dynamic key selection, a hybrid Reinforcement-Lattice Blockchain Key Generation for quantum-resilient key creation, and Zero-Knowledge Proofs for privacy-preserving signatures to ensure a safe Internet of Things environment. Data privacy, secrecy, auditability, traceability, and resistance to changing threats, such as quantum attacks, are all guaranteed by this architecture. Transparency and thorough post-event audit trails are supported by the blockchain ledger's immutability, which records all access attempts, data exchanges, and device interactions in an unchangeable way. Through a tracing key kept on the audit server within the Zero Trust Architecture, the architecture allows accurate source tracing in the event of suspicious activity or breaches. QBC-ZKPAF provides strong security and privacy solutions for Internet of Things networks by adopting multi-factor authentication and decentralizing identity management. The framework's efficacy is confirmed by experimental results, which show 98% privacy preservation, 700 TPS throughput, 0.98 quantum resilience, and 96% access control effectiveness, making it ideal for contemporary blockchain and IoT applications.

Anatolii Mukha

The χ‑spectral framework developed in this work establishes a unified operator‑geometric foundation for physical law, integrating quantum measurement, modular state reduction, spectral geometry, and gravitational curvature into a single mathematically coherent structure. Physical measurement is formulated as an intrinsic operator‑spectral transition generated by the bounded self‑adjoint observable M_chi(k) = Phi_chi(k) + B_chi(k) + R_chi(k), which combines phase geometry, boundary tension, and χ‑spectral curvature into a non‑singular measurement mechanism. Probability amplitudes P_n(k) = |_chi|^2 are derived directly from the χ‑inner product, demonstrating that Born’s rule emerges from arithmetic geometry rather than axiomatic postulates. A central result of the χ‑spectral framework is the rigorous proof of compatibility between ZEBTS‑SUPER gravitational dynamics and quantum mechanics. Gravitational curvature R_chi(k) enters the measurement operator M_chi(k) as a bounded geometric observable, ensuring ultraviolet stability, finite expectation values, and strict unitarity across all scale layers. Collapse dynamics are formulated as bounded modular projections, guaranteeing non‑perturbative, divergence‑free state reduction. Decoherence is shown to be a structural spectral gradient D_chi(k) = M_chi(k+1) – M_chi(k), providing a deterministic geometric mechanism for coherence loss without environmental reservoirs. The scale‑layer commutator C_chi(k) = [M_chi(k+1), M_chi(k)] encodes contextuality and order‑dependence as structural consequences of χ‑operator geometry. Together, these results demonstrate that quantum dynamics, gravitational curvature, measurement theory, and modular collapse are fully compatible and mutually reinforcing within the χ‑spectral operator framework. The theory achieves conceptual and mathematical closure: all physical observables remain bounded, all transitions remain unitary, and quantum–gravitational consistency is established as a direct consequence of χ‑spectral geometry.

Martin Jámbor

Quantum Cellular Theory of Space: A Testable Cosmological Model of a Dividing Causal Network Author: Martin JámborState of knowledge captured as of: 9 August 2026 Quantum Cellular Theory of Space is a research hypothesis in which space is not a fundamental continuous stage but the macroscopic manifestation of a discrete local network. In this picture, observed spacetime, matter, and fields would be emergent descriptions of the collective behaviour of its cells. The theory asks whether one physical substrate can explain the common origin of cosmic expansion, accelerated expansion, the formation of matter, an unseen clustering component, a relativistic relic, the propagation of light, and physical irreversibility. This is not a biological model. The terms cell, fuel, ash, steam, and scar denote distinct roles in the energy and state description of the network. The hypothesis is not yet an experimentally confirmed replacement for general relativity, quantum field theory, the Standard Model, or standard cosmology. In domains where those theories are validated, it must reproduce their successful laws and observational bounds. Its contribution would lie in deriving their common microscopic origin or predicting a new measurable deviation. Physical picture The basic working idea is that cells of space can locally rearrange or divide. Macroscopic expansion would then be not motion into an external void but a change in the number and arrangement of the degrees of freedom from which space emerges. The energy component that enables rearrangement is called fuel. In the effective cosmological description it has pressure close to vacuum pressure, and it can therefore carry part of the physical role attributed to dark energy and accelerated expansion. Energy and momentum must remain conserved when fuel is processed. The model investigates three possible output channels: matter as stable or long-lived excitations; ash as a nonrelativistic gravitationally clustering residue that may take over part of the role of dark matter; steam as a relativistic or freely propagating share of the energy that may leave an imprint in the early radiation or thermal background. It has not yet been determined which channels actually exist, what their fractions are, or whether they arise in parallel, sequentially, or through mixed branching. The answer must come from a common local law and observations, not from a verbal choice of mechanism. A scar is a candidate persistent change in the internal state of a cell or its links after a physical event. It is intended to carry local memory and may provide a basis for the arrow of time. It has not yet been shown whether the same mechanism can also explain a single outcome of a quantum measurement and the Born rule. Light is investigated as a wave or excitation of the common substrate. If light, matter, clocks, and measuring rods are all realizations of the same network and share one local light cone, all inertial observers may measure the same limiting c. This objective still requires derivation of the photon sector, a common metric, boost symmetry, absence of impermissible birefringence, and the equivalence principle. Central mathematical bridge The global mean-field effective overhead of rearrangement is written as delta = 1 / (<k> + C) where <k> is the mean number of face neighbours in the reference Poisson–Delaunay network and C is the working internal capacity of a cell. For <k> = 48 pi^2 / 35 + 2 ≈ 15.535 C = 28 this gives delta ≈ 0.02297 This overhead is connected to the effective equation of state of fuel: p_f = (-1 + delta) rho_f w_f = p_f / rho_f = -1 + delta The fluid form is the same as in modern cosmology; what differs is the proposed origin of w_f+1 in the geometry and capacity of the network. The value C=28 is read as the number of bosonic states in the restored phase of the Standard Model, but this identification does not yet have an independent microscopic derivation. The arithmetic 16_gluon + 8_EW + 4_Higgs = 28 counts the four real Higgs directions as already including the three directions that become Goldstone modes; it does not add them a second time. It remains open why cell capacity should count precisely bosonic and not fermionic degrees of freedom. Because the value 28 was chosen before this link was fully derived, its success in downstream calculations is not independent confirmation of the theory. If the local degree of the network varies, the overhead of one cell would have the form 1/(k+C) and its average would be <1/(k+C)>. Jensen's inequality then gives <1/(k+C)> >= 1/(<k>+C) with a strict inequality when the degree has nonzero variance. Without the distribution P(k), the value 0.02297 is therefore the mean-field value and a lower bound for this locally averaged branch, not a calculated local overhead. Cosmological background For x=ln a, the effective homogeneous model uses the densities of fuel rho_f, ash rho_c, baryons rho_b, and radiation rho_r: d rho_f/dx = -3 delta rho_f - lambda (H0/H) rho_f d rho_c/dx = -3 rho_c + lambda (H0/H) rho_f d rho_b/dx = -3 rho_b d rho_r/dx = -4 rho_r H^2 = (8 pi G / 3) rho_total Transfer between fuel and ash has opposite sources in the homogeneous description: Q_f = -Q_c = -lambda H0 rho_f The total background energy ledger is therefore conserved. lambda describes a family of effective transfer rates, not a derived constant of nature. The calculations use the data-calibrated reference point lambda=0.15; it is neither an independent prediction nor the only allowed value. The separately examined points 0.10 and 0.15 do not establish that the whole interval between them is allowed. A continuous physically admissible range must still pass stability, the null limit, and a joint comparison with BBN, CMB, BAO, structure growth, and lensing. Data used to select or normalize the reference point cannot be counted again as its independent confirmation. One homogeneous universe must have one expansion history H(a), independent of the Fourier mode later used to describe a perturbation. The early dimensionless perturbation coordinate z = k a / [H0 sqrt(Omega_r0)] must therefore not enter the background as a physical global scale. For p=4-3 delta, the mode amplitude is written as Phi(k) = A_f [H0 sqrt(Omega_r0) / k]^p which yields the homogeneous fuel term Phi(k) z^p = A_f a^p For the inputs used here, A_f=7809.270101963506. This is a conditional normalization of the specified background, not a new universal constant or a separate fit to observations. Linear perturbations and stability In a simplified nine-variable model with effective perfect radiation, the complete three-mode regular basis, kinetic and gradient signs, characteristic speeds, null limit, static Einstein constraints, behaviour at q={30,300,1000}, and numerical convergence were tested. No forbidden high-frequency growing instability was found within this scope. The result applies only to the stated model. It is not a microscopic no-ghost theorem, a proof of global hyperbolicity, or a complete evolution of photons, neutrinos, baryons, fuel, and ash. Static Einstein constraints alone do not prove their dynamical Bianchi propagation. The scalar cosine-Laplacian operator is exactly even in wave number, so its expansion contains no odd linear term. This property is necessary for a viable discrete scalar sector, but it does not by itself derive full Lorentz invariance, photon dispersion, or the equivalence principle. Quantitative consequences and viability conditions The following values are commitments of the specifically stated formulations. Agreement keeps them viable but does not confirm the cellular mechanism. A robust disagreement can exclude them only after a complete link between the model and the measured quantity, including uncertainties, covariances, and systematics. Quantity or phenomenon Value or physical condition Limit of interpretation extra relativistic relic Delta N_eff=0.0535, hence N_eff≈3.10 Applies to an early-decoupled two-polarisation thermal formulation; the local source, branching, exit, and reheating are not derived. scalar tilt n_s=0.9656 +/- 0.0016 Target of the exact delta/m=1/2 mechanism; the width is neither a new posterior nor an uncertainty derived from the formula. tensor-to-scalar ratio sharp target r<1e-10; broader practical marker r>=1e-3 The complete tensor operator, source, normalization, and B-mode observable map are missing. Hubble constant H0≈66.4 +/- 0.4 km/s/Mpc Condition of the frozen background, not a new global fit or a solution to the Hubble tension. clustering S8≈0.86–0.87 Condition of the simplified growth formulation, not a full Einstein–Boltzmann result. effective CPL description w0=-0.919, wa=-0.612 Joint target of the accounting reconstruction; it is not a microphysical equation of state for fuel. sterile ash no confirmed nongravitational signal A numerical experimental window can be defined only after deriving the mass, spin, abundance, lifetime, and couplings of ash. exact n_s-w relation no active claim The exact formula is not part of the current theory. time drift of delta delta=0.02297 is only a constant benchmark The function delta(a) or delta(x) and a measurable drift window have not been derived. scalar dispersion the odd linear coefficient is exactly zero The result applies only to the stated scalar operator. thermal steam or wave background T≈0.905 K, peak near 53 GHz This is the same thermal commitment as Delta N_eff; identification of the relic with gravitons has not been derived. The thermal result uses the standard entropy arithmetic for an early-decoupled bosonic relic: Delta N_eff = (4/7) g_x [10.75/g_*s,dec]^(4/3) with g_x=2 and g_*s,dec=106.75. The cellular hypothesis adds a possible causal origin of steam in the processing of vacuum fuel, but it does not yet determine what fraction of energy enters this channel or how the relic survives unt

W. C. Yang, J. F. Qiao, J. F. Hu, Jie Wang · 5 authors

This study presents a multi-level verification system for secure communication protocols in energy billing infrastructures. The proposed framework integrates device attestation, network integrity verification, privacy-preserving aggregation, billing validation, and immutable auditing to address security vulnerabilities across Advanced Metering Infrastructure (AMI) communication chains. A Hybrid Secure-Efficient Protocol (HSEP) combining elliptic curve cryptography, homomorphic encryption, and zero-knowledge proofs is developed to provide secure authentication, privacy protection, and verifiable data integrity while maintaining low computational overhead. Experimental evaluation using a large-scale AMI testbed demonstrates that the proposed system significantly improves tampering detection capability, achieving an intrusion detection AUC of 0.94 while maintaining an average energy consumption of 1.55 J per transaction and acceptable communication latency for large-scale deployment. The architecture exhibits strong scalability, robustness, and rapid dispute-resolution performance under multiple attack scenarios. The proposed framework is particularly applicable to wireless smart metering networks and antenna-enabled AMI communication infrastructures, where reliable data transmission, secure protocol verification, and resilience against communication-layer attacks are essential for trustworthy energy billing and grid operation. This work provides an effective engineering solution for secure, privacy-preserving, and verifiable communication in modern intelligent energy systems.

Bingbing Fan, Yuxiao Fang, Zihan Wang, Fang Ma

Background Traditional Chinese Medicine (TCM) rheumatology presents unique challenges for AI-assisted clinical decision support, as the diagnostic process relies heavily on tacit knowledge and individualized reasoning. While Large Language Models (LLMs) have shown promise in medical applications, they remain limited by hallucination risks and inability to replicate expert TCM reasoning. Retrieval-Augmented Generation (RAG) offers a potential solution, yet its application to complex TCM dialectical reasoning remains underexplored. Methods We developed TCM-CoT-RAG, a hybrid framework combining RAG with Chain-of-Thought (CoT) prompting, grounded in 1,700 expert-curated clinical cases (1,600 for RAG retrieval; 100 for evaluation, including 50 for blinded expert review by three senior TCM rheumatologists). Deployed on Alibaba Cloud, the five system leverages state-of-the-art LLMs (DeepSeek-V3, Qwen3-235B) under a human-in-the-loop paradigm. We designed a dual-tier evaluation: (1) Objective extraction tasks (Task 1–2) quantified using F1-scores; (2) Generative tasks (Task 3–5) assessed using BERTScore. Two senior TCM rheumatologists (≥15 years clinical experience) blindly assessed model outputs, and a senior chief expert quantified consistency between model predictions and ground truth (GT). Comprehensive ablation studies (S1-S4, S-Skip) isolated the contributions of each CoT module. Results TCM-CoT-RAG substantially improved diagnostic accuracy across five LLMs. DeepSeek-V3 with full-chain CoT-RAG achieved Entity F1 of 44.89% (+16.45% over baseline) and Formula F1 of 32.13% (+8.74% over baseline), with BERTScore of 0.81 indicating strong semantic alignment with expert reasoning. Ablation confirmed that the complete CoT pipeline was essential—removing any reasoning module caused performance collapse below the zero-shot baseline. Two independent experts validated clinical utility (Cohen’s κ &amp;gt; 0.7). DeepSeek-V3 achieved the highest ground-truth consistency at 81.6%, and consistency metrics were quantified by the third expert holding the most senior professional title. Conclusion This proof-of-concept framework demonstrates the potential of RAG-enhanced CoT reasoning to improve diagnostic consistency in TCM, objectifying the Symptom-Diagnosis-Prescription pipeline. It is important to note that this system is designed as an AI-assisted clinical decision-support tool. All recommendations require validation by qualified TCM practitioners before clinical application.

Anthony Coslett

Model identity verification is only as trustworthy as the reference against which identity is resolved. A system may correctly establish that a model running now corresponds to an enrolled reference while remaining unable to establish that the reference itself was the authentic release of the named publisher. This technical note separates those two claims as identity continuity and enrollment provenance. It formalizes the poisoned-enrollment failure, in which an inauthentic artifact is enrolled under a legitimate model name and subsequently passes continuity verification correctly. The failure is therefore not a false acceptance by the measurement system, but an upstream identity-binding failure. The note shows that this boundary is shared across artifact signing, behavioral fingerprinting, reference-anchored activation auditing, and structural identity measurement, and relates the problem to established software supply-chain trust models. It proposes E0–E4 enrollment assurance profiles, distinguishes provenance profile from current attribution state, and describes remediation through revocation and re-establishment of provenance without discarding historical continuity evidence. No new measurement result is reported. The contribution is an evidence boundary, threat-model construction, assurance vocabulary, and remediation model for model identity verification. The Neural Network Identity Series — Mathematical foundations, empirical validation, and governance frameworks for verifying which model is running Paper 1: The δ-Gene: Inference-Time Physical Unclonable Functions from Architecture-Invariant Output Geometry (DOI: 10.5281/zenodo.18704275) Paper 2: Template-Based Endpoint Verification via Logprob Order-Statistic Geometry (DOI: 10.5281/zenodo.18776711) Paper 3: The Geometry of Model Theft: Distillation Forensics, Adversarial Erasure, and the Illusion of Spoofing (DOI: 10.5281/zenodo.18818608) Paper 4: Provenance Generalization and Verification Scaling for Neural Network Forensics (DOI: 10.5281/zenodo.18872071) Paper 5: Beneath the Character: The Structural Identity of Neural Networks — Mathematical Evidence for a Non-Narrative Layer of AI Identity (DOI: 10.5281/zenodo.18907292) Paper 6: Which Model Is Running?: Structural Identity as a Prerequisite for Trustworthy Zero-Knowledge Machine Learning (DOI: 10.5281/zenodo.19008116) Paper 7: The Deformation Laws of Neural Identity (DOI: 10.5281/zenodo.19055966) Paper 8: What Counts as Proof? — Admissible Evidence for Neural Network Identity Claims (DOI: 10.5281/zenodo.19058540) Paper 9: Composable Model Identity — Formal Hardening of Structural Attestations in the Enterprise Identity Stack (DOI: 10.5281/zenodo.19099911) Paper 10:Where Identity Comes From: Path Sensitivity and Endpoint Underdetermination in Neural Network Training (DOI: 10.5281/zenodo.19118807) Paper 11: Post-Hoc Disclosure Is Not Runtime Proof: Model Identity at Frontier Scale (DOI: 10.5281/zenodo.19216634) Paper 12: Family-Dependent Response to Reasoning Distillation Across Structural and Functional Identity Layers (DOI: 10.5281/zenodo.19298857) Paper 13: Safety-Alignment Removal as a Model-Identity Failure — Structural Evidence from Published Weight-Level Mutation Checkpoints (DOI: 10.5281/zenodo.19383019) Technical Note: Agent Identity Is Not Model Identity (DOI: 10.5281/zenodo.19240883) Technical Note: Gap Invariance: Why PPP Measurements Are Domain-Independent by Construction (DOI: 10.5281/zenodo.19275524) Technical Note: Measured Model Substitution Under Valid Agent Credentials (DOI: 10.5281/zenodo.19342848) Technical Note: Artifact Identity Is Not Runtime Identity — Trustfall Lite and the Boundary of File-Level Model Verification (DOI: 10.5281/zenodo.20019127) Technical Note: Artifact Identity Is Not Runtime Identity — Trustfall Lite and the Boundary of File-Level Model Verification (DOI: 10.5281/zenodo.20019127) Technical Note:: The Disappearing Window — AI Logprob Access Withdrawal and the Structural Verifiability of Frontier Model Contracts (DOI: 10.5281/zenodo.20362098) Formal Verification Stack for Neural Network Structural Identity (IT-PUF Coq Proofs) (DOI: 10.5281/zenodo.18930621) Copyright (c) 2026 Anthony Ray Coslett / Fall Risk AI, LLC. All Rights Reserved. Confidential and Proprietary. Patent Pending (Applications 63/982,893, 63/990,487, 63/996,680, 64/003,244).

Devin Bostick

Abstract This orientation presents the architecture, results, boundaries, and reading paths of the Identity-Persistence Program, a research program on the structural conditions under which bounded evaluators can make reproducible judgments of identity, persistence, admissibility, and verification under declared regimes. The program’s foundational layer establishes three forcing results: structural floors for coherent identity claims, admissible transformation, and sufficient regime specification. These are bracketed below by the requirement that cumulative inquiry possess a stable same/not-same criterion and above by an identification ceiling: within the finite declared class, admissible evidence identifies only up to the declared quotient. The guide then maps the program’s post-floor structural theory. For a declared question family, maximal structure-compatible safe congruences yield canonical demand-relative normal forms and a theory of regime equivalence and refinement. Recurrence is classified in the one-degree homogeneous case; symmetry reduction is separated from operable quotient structure through an independent-redescription compatibility criterion; nested regimes compose through backward demand propagation and forward certificate compression; and reconstructibility, blocking cuts, and verification complexity are characterized at the mechanization layer. Condensation Dynamics adds a finite dynamical theory in which safe quotienting has an exact potential and path-independent total budget, interaction defects measure noncanonical allocation, serial nesting obeys a no-free-acceleration law, and structural conditions for zero defect are identified. The orientation also distinguishes these theorem-bearing results from the program’s finite-interior analyses of interaction, omission, representation, and declaration dependence; from interpretive accounts of endogenous regime formation; and from downstream runtime engineering. The resulting architecture is not a claim about final ontology or unrestricted knowledge. It is a class-relative theory of what bounded evaluators can license, preserve, compress, compose, and independently verify once the governing regime has been sufficiently declared. Corpus-native instantiation, selected extension classes, and independent formal proof verification remain open. This document proves no new theorem. It is the program guide: it records dependency structure, claim status, scope boundaries, and reading order, while the individual papers remain authoritative for their results.

Yahua Ruan

No abstract is available for this record.

Wang Lei, Jasni Mohamad Zain, Nur Atiqah Sia Abdullah, Marina Yusoff · 7 authors

The proliferation of Internet of Medical Things devices within the predictive healthcare paradigm necessitates robust, privacy-centric collaborative learning frameworks to detect and mitigate rapid clinical deterioration. Traditional federated learning methodologies, while attempting to preserve patient data locality, are fundamentally constrained by multi-round gradient synchronization protocols, imposing prohibitive communication latency and remaining susceptible to false negatives under extreme non-independent and identically distributed conditions. To address these challenges, this study introduces the Feature-Augmented Analytic Federated (FaFL) Architecture, which fundamentally replaces iterative gradient synchronization with a single-round closed-form computational paradigm. By instituting a proactive feature mixing mechanism via a decoupled zero-knowledge proof global buffer, the proposed framework empowers local grassroots nodes to neutralize extreme clinical heterogeneity in a single phase. The architecture employs a closed-form analytic solution combined with a trace-weighted absolute aggregation protocol to rigorously guarantee stochastic convergence and absolute cryptographic resilience without requiring recursive parameter exchanges. Extensive empirical evaluations against existing baselines under severe Dirichlet non-independent and identically distributed conditions and Byzantine poisoning attacks demonstrate that the framework fundamentally eradicates high false-negative rates in resource-constrained clinics. Consequently, the proposed architecture robustly guarantees generalization stability, substantially outperforms existing paradigms in predictive fidelity and computational efficiency, and establishes a new operational standard for mission-critical clinical networks.

Bilal El Issaoui

MRS‑AUTH is a novel authentication framework that achieves deniability even against an active verifier who may adaptively query candidate credentials both before and after receiving a challenge. Unlike ring signatures or zero‑knowledge proofs – where the prover holds a single secret witness that can be extracted under coercion – MRS‑AUTH exploits the multiplicative structure of linear Diophantine equations. Through recursive decomposition, it generates a Diophantine forest of exponentially many syntactically valid credential chains. The authentic chain is sampled uniformly from this forest and committed together with k‑1 indistinguishable aliases using a fixed‑shape Merkle tree with dummy leaves, eliminating structure‑ and length‑based side‑channel leakage. The Forest Symmetry Theorem proves that all chains are structurally information‑theoretically indistinguishable. However, the full index‑anonymity against an active verifier is computational and bounded in Theorem 6.6 by k · ε_SHA3 + ε_coll + negl(λ). For cryptographic scales N ∼ 10⁴², the Ehrhart‑based continuous‑volume approximation yields an effective entropy exceeding 371 bits, with a statistical distance to the perfect uniform distribution of Δ ≤ 2⁻¹³⁵ – well below the 128‑bit security threshold. Empirical validation via exact enumeration and a chi‑squared test (χ²/dof ≈ 0.985) confirms the uniformity. A constant‑time Rust implementation, leveraging the subtle and zeroize crates, exhibits an execution time of approximately 0.12 ms across four orders of magnitude of N, demonstrating practical deployability. The work also formalises the Active Verifier Game model, a new adversarial definition that quantitatively captures coercion resistance in a post‑quantum setting.

Junchen Zhu

Stateful cryptographic schemes—exemplified by the hash-based signatures XMSS (RFC 8391) and LMS (RFC 8554)—require the signer to advance a local state monotonically; any rollback is catastrophic, yet a verifier has no way to check it. IETF guidance on state and backup management for hash-based signatures states explicitly that the verifier must simply trust the signer not to have reused state. We define verifiable monotone chains (VMC), a primitive that makes such state discipline cryptographically verifiable: state evolves along a finite poset (S, ⪯) under inflationary monotone operators, every transition carries a zero-knowledge proof, and a public commitment to the state provides an audit trail. We formalize two security notions: monotone-unforgeability (MU), which captures that an external adversary cannot certify an illegal or rolled-back transition, and auditability (AUD), which captures that signer rollback cannot be hidden from a public root history. Both notions reduce, with explicit advantage bounds, to position binding of the underlying vector commitment and knowledge soundness of the proof system. We instantiate VMC as RSEP-XMSS, in which each XMSS signature carries a proof that the signed leaf advanced along the chain FRESH ≺ USED ≺ SPENT in a Poseidon-based state Merkle tree, and we give a complete algorithmic specification with a concrete circuit design (~6041 R1CS constraints estimated, Groth16 proving time estimated at 5–15 ms, signature overhead of about 1–3 KB). RSEP-XMSS is one-way compatible with standard XMSS: legacy verifiers verify the core signature, while enhanced verifiers reject unprotected signatures, preventing downgrade attacks.

Bharath M B, Latha N R

Web security has become a critical domain as modern applications increasingly rely on dynamic user-generated content, making them highly vulnerable to Cross-Site Scripting (XSS) attacks. Traditional detection systems struggle to cope with evolving payload patterns, limited generalisation across institutions, and strict privacy restrictions that prevent sharing of sensitive request logs. To address these challenges, this work proposes a Zero-Knowledge Federated Sequence Learning (ZK-FSL) framework that enables collaborative XSS detection without exposing raw data or intermediate gradients. The model integrates attention-based deep sequence learning with zero-knowledge proof validation, ensuring both strong predictive capability and verifiable trust among participating clients. Experimental evaluation demonstrates that ZK-FSL achieves superior performance compared to centralised and federated baselines, reaching 96.3% accuracy , 96.7% precision , 95.9% recall , 96.3% F1-score , and an AUC of 0.98 . These results confirm that the proposed framework effectively enhances privacy-preserving threat detection while maintaining high robustness against diverse and sophisticated XSS attack patterns.

Nihan Kır

The disclosure duty of arbitrators does not carry a big stick: the consequence attached to its breach is near to none. The duty is carried out through a black-box judgment call; no reasoning for how the arbitrators weed out what not to disclose is made available to the parties. There may be circumstances falling under a grey area but have ended up undisclosed due to, for instance, confidentiality obligations. Exhaustive disclosure and minimum revelation of sensitive information would serve the greatest benefit of all stakeholders. Zero-knowledge proofs (ZKP) – a class of cryptographic protocols – may make this possible.

Z. P. Zhu, Clarence Lam, Alexander Frolov, Ian Miers · 5 authors

We present zk-Analytics, a distributed cloud analytics system that enables publicly verifiable analytics without revealing raw logs or relying on trusted hardware in analytics providers' infrastructure. Today's cloud analytics are largely self-assertive: providers collect telemetry, perform aggregation, and report results, leaving external parties unable to verify correctness without access to sensitive data or trusted execution environments. zk-Analytics addresses this gap by augmenting analytics pipelines with lightweight append-only log commitments and verifiable aggregation and query execution using zero-knowledge proofs. The system cleanly separates online log commitment from offline, distributed batch aggregation and query verification, enabling scalability while keeping online overhead low. We implement zk-Analytics using a zkVM-based execution environment and evaluate it on real-world and synthetic workloads, demonstrating that verifiable, privacy-preserving cloud analytics is feasible for real-world cloud workloads. zk-Analytics is open-sourced at https://github.com/Froot-NetSys/zk-Analytics.