Blockchain systems are undergoing a fundamental transition from decentralized ledgers for digital assets to general-purpose trust infrastructures for verifiable computation, decentralized physical resources, and automated infrastructure management. Meanwhile, the limitations of the Blockchain as a Service (BaaS) model stem from a common structural problem: outsourcing control of infrastructure to third-party service providers inevitably involves a systemic surrender of trust, flexibility, and data sovereignty. RISC-V, with its open, modular, and extensible design, provides a general-purpose computing foundation for public blockchains that is open, low-level, compileable, verifiable, and scalable. Inspired by the development and characteristics of eSIM, the embedded Blockchain infrastructure management (eBIM) is defined as a software-hardware collaborative paradigm for blockchain infrastructure management with RISC-V. This study aims to provide a comprehensive survey on eBIM supporting research and technologies, to answer the following research questions (RQs): RQ1 What is eBIM? RQ2 How does eBIM work? RQ3 What can eBIM do? By introducing the concept of eBIM, this paper establishes a foundational reference for researchers, hardware architects, and protocol designers in this rapidly evolving landscape, including cryptographic acceleration, trusted execution environments, zero-knowledge virtual machines, and smart contract execution engines. The prospects of the proposed e-BIM and its future research directions are indicated in this paper.
Electronic voting must keep individual ballots private while letting anyone verify the final tally. This paper presents an architecture that meets both goals without a trusted key dealer: each voter encrypts a ballot in the browser with a self-generated secret key under the Paillier additive homomorphic cryptosystem, and no party ever holds every key. Two server roles divide the tally. A collector combines the voters' per-ballot auxiliary values into a single group element; an aggregator uses that element to cancel the voters' random masks inside the homomorphic product and recover the exact vote sum, learning the result but no individual ballot. The Solana blockchain records every ciphertext immutably and enforces the election lifecycle, while a native C library (libtommath) performs the heavy modular arithmetic. We state six assumptions under which the protocol is correct and prove product homomorphism, mask cancellation, and sum recovery; privacy rests on the Decisional Composite Residuosity (DCR) assumption for the additive layer together with a Diffie-Hellman-style assumption on the masking base. A bit-packing scheme places an entire multi-candidate ballot in one ciphertext, cutting client work, on-chain transactions, storage, and tally cost by a factor of k (the candidate count); the slot width b is free, with only k*b bounded by log_2(N). With b = 25 and a 255-bit modulus the scheme supports ten candidates and up to 2^25 - 1 = 33,554,431 votes per candidate, about 335 million ballots, and tallies 50,000 ballots in under one second. Finally, running the collector and aggregator inside attested secure enclaves makes the tally tamper-resistant and prevents cross-role collusion to deanonymize voters. The proof-of-concept implementation is open-source; a worked numerical example in the appendix reproduces the full pipeline.
Leopold Müller, Jana Elsner, Thomas Niedermayer, Bernhard Haslhofer · 7 authors
Address clustering is an important technique in blockchain forensics, widely employed by law enforcement to trace illicit crypto asset flows. The multi-input heuristic (MIH), which clusters addresses potentially associated with the same entity, is the most widely used. Yet, despite its broad adoption, the MIH has rarely been evaluated against reliable ground truth data. We implement a reusable evaluation framework covering nine established metrics and apply it to ground truth address-to-entity mappings obtained directly from European crypto asset service providers under legally mandated reporting obligations. When evaluation is restricted to reported addresses, the MIH appears strong at dataset level: we observe no mergers between reported services and recover same-service address pairs with recall 0.71. However, this result is driven by one large service and ignores unlabeled addresses absorbed into full clusters. Metrics that assess the full clusters show substantially lower precision and recall (0.36 and 0.44), meaning that services are often only partially recovered or embedded in larger clusters. Entity-level results further reveal near-complete failures for some services. When MIH-based clusters are used to support criminal suspicion, preliminary seizure of crypto assets to secure later forfeiture/ confiscation, or as evidence in trial proceedings, prosecutors and judges must account for the heuristic's metric-dependent and entity-dependent reliability.
Existing cybercrime classification schemas capture contact metadata and financial transactions but omit the psychological manipulation techniques perpetrators employ. We present a forensic schema (four categories, 35 questions) adding 11 manipulation indicators and cryptocurrency evidence fields to established forensic foundations. Applied to 10,994 victim reports via large language model (LLM)-driven annotation and validated against two human annotators (mean LLM-human $κ= 0.69$, matching inter-annotator $κ= 0.68$), the schema revealed a statistically distinct manipulation profile for each major fraud type (Cramer's $V$ up to $0.790$). A rationale-based evidence audit nonetheless exposed a forensic detail gap: detection of manipulation techniques was reliable, but victim narratives varied widely in the actionable detail supporting each Yes answer, and blockchain-specific identifiers were nearly absent. These findings point to AI-assisted victim intake with schema-informed follow-up questions as the most direct way to close the gap. The tiered annotation strategy also provides a reusable template for LLM-based extraction from other forensic text domains.
Nowadays, mobile forensics is less explored in Digital Forensics case analysis due to the increase in data protection mechanisms implemented by tech companies (i.e., Google for Android and Apple for iOS). For example, the physical acquisition or analysis of specific directories under super-user protection would corrupt the evidence; access to such data is protected, and bypassing this protection requires either privilege escalation or custom ROM installation, leading to the modification of the device state. At the same time, the demand for mobile technologies and their respective communication systems is increasing exponentially, exposing numerous security threats and risks. For that reason, this paper presents a Mobile Live Intelligent Forensics Examination (MoLIFE), a novel Digital Forensics (DF) methodology for data acquisition and analysis of mobile devices. The proposed methodology is based on NIST SP800-101 for the DF process. MoLIFE can be integrated with new and emerging technologies by exploiting their power (e.g., AI, blockchain, quantum computing). MoLIFE can also be used to prevent cyber threats and incidents, as well as DF post-mortem analysis, offering examples of applying the MoLIFE methodology and good practices for the future. To prove the technical feasibility of the methodology, a small case study on Android devices data acquisition via the mDT will be presented. As the methodology is based on new and emerging technologies, it depends on their limitations that would be overcome in a few years.
Smart contract compilers are critical to ensuring the correctness of public blockchains whose defining characteristics are open-source and immutable code. We created SolSmith, a semantics-aware differential fuzz testing tool, to improve the quality of the Solidity compiler -- the most popular compiler for the Ethereum blockchain -- and spent over three years finding compiler defects that produce incorrect code. We call these defects miscompilation bugs. During this time period, we have discovered 25 miscompilation bugs that went unnoticed, some for multiple years. Our first contribution is to make compiler testing more rigorous. SolSmith achieves this goal by generating valid test programs that are likely to stress test code generation and optimization components. This helps SolSmith find bugs missed during routine testing that could potentially have serious implications for smart contracts and their users. Our second contribution is a qualitative and quantitative analysis of miscompilation bugs that we found in the Solidity compiler. We classify miscompilation bugs found by SolSmith based on their nature, root-causes, and impact on end-users. This sheds light on some pitfalls of optimizing compilers.
Monero is a privacy-focused cryptocurrency that deploys the Dandelion++ protocol and incorporates anonymity networks (such as Tor and I2P) to prevent malicious attackers from linking transactions with their source IPs. In this paper, we demonstrate that Monero's integration of the Tor network introduces a fundamental vulnerability: a Monero Tor node's originated transactions are exclusively forwarded to two outgoing Tor hidden service nodes (proxy nodes) prior to clearnet propagation, enabling an adversary to capture originated transactions by occupying the target node's outgoing connections. Based on this observation, we propose \textit{ProxyMark}, a three-stage deanonymization framework for the Monero Tor network, comprising node role identification, originated transaction identification, and node location deanonymization. Through experiments on the live Tor network, Monero mainnet, and testnet, we empirically demonstrate the effectiveness of \textit{ProxyMark} in successfully deanonymizing transactions originating from Monero nodes over Tor.
This paper introduces Mirror Protocol as an implementation layer for the Conditions of Understanding. Rather than proposing another theory of understanding, the paper describes a practical method for protecting the conditions under which understanding can emerge. It argues that genuine understanding is often disrupted not by lack of information but by premature evaluation, guidance, intervention, or meaning fixation. Building upon The Conditions of Understanding, the paper presents a five-stage protocol consisting of Reality / Sensation / State, Project Mirror, Friction Detection Point, Meaning Non-Capture Protocol, and Leave to the World. Together these stages describe how one can remain engaged with another person’s process without prematurely directing or completing it. The paper further distinguishes reflecting from indifference, and non-capture from non-response, arguing that restraint is an active practice rather than passive inaction. Friction is interpreted not as failure but as evidence that the protocol is functioning, provided the impulse to intervene is recognized without being acted upon. Mirror Protocol is proposed not as a communication technique but as a general implementation framework for preserving the conditions in which observation, discovery, and understanding are allowed to arise naturally. It concludes by positioning the protocol as a bridge between theoretical principles and future organizational or institutional applications. This paper is part of a four-part series on the conditions and infrastructure of human understanding: This paper uses "Mirror Protocol" as a concept within Maura Theory, an independent theoretical framework concerning the conditions of human understanding. It is unrelated to the decentralized finance (DeFi) protocol of the same name operating on the Terra blockchain. (1) From Information Access to Meaning Recognition: Professional Expertise After the Cost of Information Collapses https://doi.org/10.5281/zenodo.21230076 (2) The Conditions of Understanding: Protecting the Conditions Under Which Understanding Emerges https://doi.org/10.5281/zenodo.21251927 (3) Mirror Protocol: An Implementation Layer for the Conditions of Understanding https://doi.org/10.5281/zenodo.21252084 (4) Understanding Infrastructure: Scaling the Conditions of Understanding to Organizations and Institutions https://doi.org/10.5281/zenodo.21252316
Modern information protection methods are primarily focused on increasing computational complexity: it is assumed that a task becomes secure if finding the true message requires too many resources. However, virtually all existing models --- from classical cryptanalysis to autonomous AI agents and retrospective analysis systems (Harvest \& Analyze) --- rely on one common assumption: there exists a verification signal that allows distinguishing the true interpretation from the set of false ones. In this work, we present the \textbf{HYBRA MIRAGE} storage architecture, which is based on a different problem formulation. Instead of increasing computational complexity, we propose to eliminate the very criterion of truth upon which directed search is based. The system constructs a space of plausible interpretations and physically excludes the possibility of repeated access to the used reference space~$V$: each of its vectors is applied exactly once and then destroyed on both sides. As a result, the function $\mathsf{Assemble}(C,K,p)$ remains deterministic and total, and any valid access parameter produces a formally correct result. Even with full access to the reference space $V$ and the PIN code, an autonomous analytical agent does not obtain a mechanism to confirm that the found interpretation corresponds to the original message: each vector from $V$ was used exactly once and physically destroyed. The $\mathsf{Assemble}$ algorithm is a trade secret and is not available to the analyst. Consequently, knowledge of $V$ without knowledge of the algorithm allows generating $10^{35}+$ equivalent interpretations, but does not allow singling out the single true one among them. The proposed approach does not make brute force computationally impossible; it makes the claim that the found interpretation is precisely the one embedded by the sender unprovable. Increasing computational resources, applying more sophisticated models, or massive enumeration can produce more candidates, but do not create a procedure that allows mathematically justifying the choice of a single true interpretation. For autonomous AI agents, this leads to the disappearance of the verification signal necessary for directed search. The loss function surface degenerates into a plane with zero gradient: no iterative optimization algorithm can converge to the true parameter faster than random guessing. HYBRA MIRAGE does not compete with classical cryptographic algorithms and does not replace them. The architecture serves as an environment model for analyzing the behavior of autonomous agents under conditions of the absence of a reliable verification signal and can be used as an infrastructure layer on top of existing storage methods. The architecture does not eliminate the agent's ability to generate candidates; it eliminates the possibility of using the generation result as proof of achieving truth. The analyst finds themselves trapped in a state of epistemic equilibrium, where truth and hallucination are architecturally indistinguishable from each other.
Arithmetization-oriented (AO) hash functions are the dominant cost in zero-knowledge proof systems, and their security against the strongest known attacks rests on the hardness of the constrained-input constrained-output (CICO) problem, solved by Gröbner-basis techniques. Raising the nominal algebraic degree of a design is known not to suffice, as recent attacks (FreeLunch, CheapLunch, resultant methods) have repeatedly shown. This work identifies a positional design lever for AO substitution-permutation networks over the Goldilocks field with the power-map S-box x^7: folding a low-degree quadratic coupling into the input of the S-box adds one bit of CICO ideal degree per round, whereas the same coupling placed in the linear layer or after the S-box adds nothing. The ideal degree follows the measured law D_I = 7^(R·m) · m · 2^(R−1) against a baseline of 7^(R·m), where R is the number of rounds and m the number of free input branches. Measurements in the msolve Gröbner engine indicate that the added degree is genuine rather than a nominal inflation (the F4 solving degree rises; an auxiliary-variable-free model reproduces the ideal degree; a resolved large instance rules out competing laws), that it is generic across four unrelated coupling patterns, that it is independent of the coupling density (one term per round suffices), and that it carries no differential/linear cost. The principle is instantiated as Alaniz-AO, a Goldilocks sponge whose HADES partial-round schedule reaches 0.74x the constraint cost of Poseidon2 at a 128-bit target under an explicit ω=2 cost model. A secondary result: the branch number of the linear layer does not govern algebraic CICO security. Measurements are reproducible and use proxy primes sharing the exponent structure of Goldilocks. Round counts and cost figures are extrapolations from the measured degree law under the stated cost model; instances beyond three rounds exceed the solver on commodity hardware and are reported as gaps. A reference implementation and reproduction scripts accompany the paper.
Open access
2 source records
Cryptographic Implementations and Security
Cryptography and Residue Arithmetic
Physical Unclonable Functions (PUFs) and Hardware Security
This working paper introduces selected findings from Flow Extraction Theory (FET), an independent research program studying economic-state representation in decentralized financial systems. The paper argues that event history is not equivalent to state, and that observed pressure is not equivalent to explained pressure. Using a bounded Aave V3 case study at Ethereum block 20,000,000, the paper distinguishes historical event evidence, frozen protocol state, token-level representation, account-level aggregate outputs, inference, and unknowns. The study shows that event-derived reconstruction can disagree with exact frozen state, and that health-factor distance can be observed with high confidence while the evidence required to explain that distance remains incomplete. The paper introduces representation risk as the risk created when different evidence classes are collapsed into one operational view of “state.” This public version summarizes selected findings only. It does not disclose implementation details, private tooling, execution logic, complete artifacts, or trading signals.
Este artículo analiza la naturaleza jurídica y la eficacia obligacional de los smart legal contracts (slc) en el ámbito del derecho comercial internacional. Ante la ausencia de un marco regulatorio específico, el estudio examina si los instrumentos vigentes —tales como los marcos normativos europeos (Reglamento Roma I), el sistema interamericano (Convención de México) y la Convención de las Naciones Unidas sobre los Contratos de Compraventa Internacional de Mercaderías (cvcim)— ofrecen criterios idóneos para resolver los conflictos de leyes derivados de la tecnología blockchain. A través de una metodología cualitativa con enfoque analítico y teórico-jurídico, se aborda la distinción doctrinal entre Smart Code Contracts y Smart Legal Contracts, contrastando la inmutabilidad del código con la exigibilidad del acuerdo legal. La investigación concluye que, pese a los desafíos técnicos, la validez y ejecutabilidad de los slc pueden sustentarse en los principios generales del derecho internacional privado, particularmente mediante el ejercicio de la autonomía de la voluntad conflictual. El artículo sistematiza los criterios esenciales para dotar de seguridad jurídica a esta modalidad de contratación en el escenario transfronterizo.
The automotive industry is transitioning to Zonal-oriented Architectures (ZoA) for Software-Defined Vehicles (SDVs), enabling frequent over-the-air (OTA) updates for 100+ Electronic Control Units (ECUs). While OTA updates improve efficiency, they introduce safety-critical security risks. Current standards like Uptane and AUTOSAR Adaptive rely on Public-Key Infrastructure (PKI). However, PKI-based authentication creates bandwidth bottlenecks in in-vehicle and vehicle-to-cloud (V2I) communication as ECU density increases. It also risks exposing sensitive vehicle configurations and passenger privacy due to centralized architectures. Next-generation Zonal SDVs require decentralized, scalable authentication with data privacy. To address this, we propose zk-ScalHard, a hardware-rooted, privacy-preserving authentication protocol. We introduce a decentralized, hierarchical trust-promotion model utilizing Silicon Physical Unclonable Functions (PUFs) and two novel Zero-Knowledge Proof (ZKP) circuits: (1) Zonal Identity and Integrity (ZIDI) and (2) High-Performance Computing Aggregation (HPCA). These circuits employ multi-party computation (MPC) and recursive aggregation to achieve decentralization and scalability. The integration of ZKPs and PUFs ensures 100% vehicle-level data sovereignty. Benchmarked against Uptane, zk-ScalHard achieves constant O(1) communication and verification complexity, improving upon the linear O(n) complexity of current systems. Evaluation shows a 99.2% reduction in authentication bandwidth and a 99.9% reduction in the temporal attack surface. Our results demonstrate that zk-ScalHard provides a scalable, secure, and GDPR-compliant architecture for future Zonal SDVs.
Open access
3 source records
cs.CR
Physical Unclonable Functions (PUFs) and Hardware Security
Abstract Zero-knowledge machine learning (zkML) enables cryptographic verification of machine learning inference while preserving privacy, but proof generation remains a significant computational bottleneck. Existing work primarily focuses on reducing proof cost through post-training optimizations, whereas the influence of architectural design choices during model development has received less attention. This work presents an empirical study of the relationship between neural network ReLU activation count and zero-knowledge proof generation cost using the ezkl/Halo2 framework. Across controlled experiments, ReLU activation count exhibits a strong correlation with proof generation time (Pearson r = 0.90) and proof size (r = 0.91), while parameter count is held constant for the primary comparisons. Motivated by these observations, a lightweight proxy metric is proposed to estimate relative proof cost directly from model architecture without executing the proof pipeline. On MNIST, reducing the number of ReLU activations from three to one decreases proof generation time by approximately 6.5% and proof size by 2.3%, while maintaining comparable classification accuracy. These results suggest that ReLU activation count is a useful architectural indicator of proof cost in the ezkl/Halo2 backend and that incorporating proof-cost considerations during architecture selection may improve the efficiency of zkML deployment. The proposed proxy metric provides a fast method for comparing candidate architectures before proof generation.
Open access
2 source records
Adversarial Robustness in Machine Learning
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Blockchain applications may have preferences over the order in which transactions execute: an automated market maker may use an external feed to price its liquidity, and require that the oracle update incorporating this price execute before any swap; an exchange may want to execute cancellations of limit orders before incoming market orders; an application may run an on-chain auction by executing bids from highest to lowest, so that the first bid wins. However, the ordering of transactions is chosen by the underlying blockchain and may not be compatible with the requirements of a specific application. In this paper, I tackle this problem by introducing an algorithm called unanimity override. The intuition is that when all the applications agree on how to order two transactions, the underlying blockchain should respect this agreement; a default order - the order in which transactions appear in the block - settles the rest. The problem with this naive approach is that application unanimity may form cycles, which the algorithm must break. Cycle-breaking is also the rule's main vulnerability because an attacker can insert transactions to manufacture a cycle. Yet two guarantees hold against any attacker who sets the default order, deploys applications, and inserts transactions. All transactions that interact with a single application that expressed preferences are ordered according to that application's preferences, even when they also interact with other applications that did not express preferences. Also, gated transactions - those that cannot be outranked in the unanimity order by any transaction crafted by an attacker - always execute as the applications unanimously prefer, even when they touch many applications. The two guarantees identify the preferences the protocol can protect, and they tell applications and senders in advance which transactions will execute in the intended order.
Ethereum Layer-2 (L2) ecosystems improve scalability but also fragment users, liquidity, gas funding, and execution across rollups. Consequently, cross-rollup interoperability is not only a bridging problem but also a wallet, execution, and validation problem. Ethereum Interop Layer (EIL) proposes a voucher-based architecture in which users create voucher requests on an origin chain and redeem XLP-signed vouchers on a destination chain. When reproducing the evaluated SDK version in a controlled local environment, we observed a compatibility issue in the \texttt{UserOperation} path: paymaster-related data can differ after signing, preventing a stable comparison between the user-authorized representation and the representation later inspected by the local validation flow. This paper presents a reproducible two-L2 validation framework and a controlled compatibility mitigation for that issue. We build a deterministic local testbed over Arbitrum- and Optimism-style development chains, deploy the core paymaster and bridge-related components, implement mock bundlers and event-driven XLP providers, and introduce a sanitized paymaster-data handling path together with a compatible multichain account wrapper. Using this framework, we execute the core voucher lifecycle from request creation to destination-chain voucher redemption and asset release. The contribution is an empirical diagnosis of an implementation-level compatibility barrier, a bounded mitigation that restores controlled end-to-end execution, and an inspectable validation artifact for studying voucher-based interoperability. The work does not claim a new interoperability protocol, universal wallet compatibility, or production readiness; it identifies the remaining gaps toward standard-account validation, one-signature multichain authorization, and full dispute-settlement support.
Abstract This article analyses the European Union’s regulatory evolution regarding Distributed Ledger Technology (DLT) in financial markets, tracing the journey from the inception of Regulation (EU) 2022/858 to the transformative Market Integration and Supervision Package (MISP). It explores the foundational value proposition of tokenisation, namely atomic settlement and fractionalisation, while contrasting institutional successes like Project Guardian with systemic failures such as the ASX CHESS replacement. The study identifies the ‘ceiling on success’ inherent in the initial DLT Pilot Regime (DLTR), characterised by restrictive capitalisation thresholds and a lack of native cash leg integration. The analysis further evaluates the 2025 ESMA recommendations and the Commission’s subsequent MISP proposal, which seeks to establish a permanent, scalable architecture through unbundled CSD services introducing DLT Notaries and Account Keepers, and significantly elevated aggregate thresholds of €100 billion. The article concludes by arguing that the framework’s ultimate success depends on securing European technological sovereignty and maintaining an agile, national-level supervisory model rather than succumbing to premature centralisation.
This replication package contains the curated Solidity benchmark, prompt templates, experiment scripts, and saved outputs used to reproduce the study on LLM-based smart contract vulnerability detection. It includes the ground-truth annotations, raw model predictions, evaluation metrics, and post-processing utilities.
This paper establishes, inside the Lean 4 proof assistant, a three-level formal identification. The levels are: (i) Belnap multilattice axioms for Weyl–Heisenberg covariant SIC-POVMs at $d=2^n$; (ii) the Zauner conjecture; and (iii) the mixed-signature Stark conjecture for the ray class field $K_d=\mathbb{Q}(\sqrt{(d-3)(d+1)})$, a real-quadratic case of Hilbert's Twelfth Problem. Fiducials are unit-normalized and satisfy $(d+1)|\langle\psi,D_{a,b}\psi\rangle|^2=1$. The equivalence hilbert_embedding_equiv_zauner is proved by rfl: the Belnap embedding into $\mathbb{C}^{2^n}$ and the Zauner conjecture at $d=2^n$ are definitionally the same proposition. The Belnap skeleton (orbit size $4^n$, Frobenius closure $\mu\circ\delta=\mathrm{id}$, join-equiangularity, Born rule) contains zero sorries. Open arithmetic content is marked by named gap axioms for Stark units on WH frames; a proof of Stark would close all three levels at once. For dimension $d=12$ we prove SICPOVM_Exists 12 outright. We construct an exact fiducial in a finitely presented $\mathbb{Q}$-algebra, verify 143 overlap identities with native_decide, and transfer everything to $\mathbb{C}^{12}$ along a ring homomorphism. The theorem crystal_forces_d12_sic depends on no axiom beyond Lean 4's standard foundations and compiler trust. This is, to our knowledge, the first machine-checked SIC-POVM existence in any dimension. For the frontier dimension $d=2048=2^{11}$ the transport apparatus is formalized and sorry-free. It includes a forward map $\varphi\colon B^{\oplus 11}\to\mathbb{C}^{2048}$, a reduction $\psi$ with $\psi\circ\varphi=\mathrm{id}$, a conditional reduction to Stark, and a non-real character obstruction that blocks the false branch. Unconditional existence remains open; the machinery that surrounds it is closed.
We present ECO/CPO-DAG, a domain-specific accountability protocol for adversarial supply chains that formalizes contradiction detection as a supplemental validation layer rather than a consensus or truth-establishing mechanism. Participants publish signed Event Claim Objects (ECOs) into a causally ordered, append-only directed acyclic graph (DAG) whose edges encode happened-before relations. When two claims about the same subject violate a domain constraint, any observer can compile a Contradiction Proof Object (CPO), a self-verifying object binding the two signed claims and the violated rule, which, on public verification, triggers economic slashing of a determinately blamed party. We map constraints to GS1 EPCIS 2.0 event semantics (spatial uniqueness, temporal monotonicity, quantity conservation, quality monotonicity, regulatory validity), so detection targets inconsistencies that are meaningful in practice. Selective disclosure via commitment schemes and, optionally, zero-knowledge contradiction proofs lets parties withhold claim contents until a challenge forces the minimal opening. We give an analytical treatment: an independent-observer detection model $1-(1-p_{\min})^h$, a deterrence condition $S>g(1-p)/(kp)$ under $k$-party collusion, and a storage estimate of order 1 GB per participant per year under stated assumptions. The protocol's boundary is explicit: it detects provable contradictions, not consistent lies; a party that never contradicts itself is invisible to it, so the layer complements, and does not replace, source verification and oracle aggregation. A single-machine reference implementation corroborates the detection model, with the predicted coverage band overlapping the measured 95% confidence interval at every observer count, and records zero false accusations; the fully zero-knowledge CPO, multi-party propagation, and adaptive-adversary evasion remain analytical.
In the era of digital revolution many contemporary events that changed the world were shaped through the internet. Nowadays, the emergence of internet of things (IoT), combining physical objects with virtual networks is expected to have even more influence. This new 'decentralised' structure in the world raises questions such as power, governance and the notion of democracy online. The aim of this paper is to investigate these notions. We have taken the examples of Bitcoin and Wikipedia and examined their decision-making process. Our analysis has found some inconsistencies in their policies, that are in contradiction with democracy and consensus principles of governance. Starting from our findings, we present further improvements that can be used to achieve more democracy and equity in the digital context.
INTRODUCTION:The distributed digital economy, characterized by decentralization and cross-entity data flow, improves factor allocation efficiency but increasingly raises concerns over data security and privacy abuse. OBJECTIVES: Unlike the conventional digital economy, which often centers on centralized platforms (e.g., e-commerce, cloud computing), the distributed digital economy in this paper specifically refers to an economic system where data—as a production factor—is stored, computed, and circulated across multiple independent nodes without a central coordinating authority, relying on technologies such as blockchain, distributed ledger, edge computing, and peer-to-peer networks. Its core governance features include decentralized data control, consensus-based verification, and peer-to-peer economic activities. METHODS: This paper studies data security and privacy protection in the distributed digital economy from two aspects: economic impact and governance mechanism. Based on panel data from 30 provinces in China from 2018 to 2023, this paper uses the entropy weight-TOPSIS method, a two-way fixed effects model, a mediation effect model, and a spatiotemporal heterogeneity model to empirically test the economic impact and transmission mechanism of data security and privacy protection on the distributed digital economy. RESULTS: The empirical analysis results show that the level of data security and privacy protection significantly and positively promotes the development of the distributed digital economy, with each unit increase leading to a 0.412 unit increase in the development index. Blockchain smart contracts, privacy computing standards, and cross-border data flow rules play significant mediating roles, accounting for 93.7% of the total mediating effect. This positive economic effect exhibits significant spatiotemporal differences, increasing year by year, and is significantly higher in the eastern region than in the central and western regions. CONCLUSION: Based on empirical analysis results, optimization paths are proposed from four levels: collaborative governance, technology empowerment, regional balance, and institutional improvement, in order to improve the level of data security and privacy protection in the distributed digital economy.