This study examines the potential of Zero-Knowledge Protocols (ZKPs) as cryptographic mechanisms that enhance privacy and security in the context of advancing quantum technologies. Rather than accepting current legal safe guards and regulatory structures at face value, the study critically evaluates their effectiveness, particularly in healthcare environments where highly sensitive data frequently encounters inadequate protection. The methodology employs a multifaceted approach, integrating qualitative insights, legal case studies, and framework analysis. The findings indicate that zero-knowledge proof techniques can significantly enhance the protection of personal health information. A case study of NantHealth Inc.’s quantum-safe healthcare data protection framework illustrates the practical implementation of post-quantum cryptography and homomorphic encryption, demonstrating how health care organizations may proactively address quantum computing threats while enabling secure data collaboration. The study further demonstrates that incorporating these cryptographic methods into existing legal frameworks not only addresses immediate privacy concerns but also facilitates compliance with evolving data protection standards. The study also suggests that healthcare organizations should reconsider their data security approaches by implementing advanced cryptographic measures while maintaining regulatory compliance.
Digital assets, a broad term encompassing crypto-currencies, tokens and digital representations of value, have transformed the financial landscape over the past decade. Ghana has transitioned from an unregulated crypto-currency environment to a structured, licensed digital assets space following the passage of the Virtual Asset Service Providers (VASP) Act 2025 Act 1154. Unlike traditional assets, digital assets exist exclusively in electronic form and are secured through cryptographic techniques, most notably blockchain technology. Bitcoin, Ethereum, and other crypto-currencies serve as prominent examples, alongside digital tokens used in decentralized finance (DeFi), security tokens, and stablecoins. They may serve a variety of functions, including use as a medium of exchange, for investment, or as a means of accessing goods, services, or applications within specific ecosystems. These assets include crypto-currencies, tokens, stablecoins, and other blockchain-based instruments. Global digital assets represent any item of value securely stored and managed via distributed ledger or blockchain technology. Encompassing cryptocurrencies, stablecoins, tokenized securities, and non-fungible tokens (NFTs), the sector has rapidly expanded into mainstream finance, revolutionizing global payments, portfolio diversification, and record-keeping. This article discusses the challenges and opportunities of digital currencies and the way forward. This research shows that digital currencies have advantages like making transactions faster, cheaper, and more accessible and also reveals a lot of disadvantages like creating major risks concerning compliance with regulations, cybersecurity, and potential impacts on monetary policy. The review emphasizes the necessity for robust regulatory frameworks for digital assets. It supports both innovation and stability for the digital currencies. It suggests that policymakers and financial institutions should adapt to changes and face the challenges by integrating digital currencies with existing systems. Overall, this review highlights the potential of digital currencies to transform finance. It also stresses the importance of focusing on the challenges they pose to ensure they can coexist successfully with traditional financial systems. As digital currencies evolve, the Ghanaian traditional financial sector faces pressure to adapt, with CBDCs, in particular, being explored as a secure, regulated alternative to volatile crypto-assets. nThe findings revealed that the central bank must adopt robust regulatory and licensing frameworks must align with Virtual Assets Service Providers (VASP) (Act 2025 Act 1154) by enforcing strict licensing for exchanges and custodians while adhering to AML/CFT (Anti-Money Laundering) directives. Also, the Bank of Ghana and the Securities and Exchange Commission must develop a comprehensive public education programme on the digital assets in the financial ecosystem. Given the novelty of the trend of criminality in the digital asset space, the establishment of specialized cybercrime courts to be presided over by judges, proficient in digital law and cybercrime would be of immense benefit. The mandate of such courts could be to expedite trials and ensure thorough adjudication of complex cyber cases. This would have the combined effect of empowering the Ghana Police Service and Cyber-Security Authority to fully invest time, money, and human resources towards the investigation of cybercrime, as well as serve as a deterrent for criminal elements, ultimately protecting our citizens and providing justice for those seeking redress.
Aircraft maintenance records are critical to airworthiness and asset valuation, yet they are often fragmented across stakeholders, creating verification bottlenecks and information asymmetry that may suppress aircraft residual value. This paper proposes a blockchain-anchored decentralized application (dApp) based on a dual-layer architecture that combines InterPlanetary File System (IPFS)-based off-chain storage with on-chain anchoring of Content Identifiers (CIDs) and selected metadata. With respect to off-chain file size, the on-chain payload per record remains $\mathcal{O}(1)$, compared with $\mathcal{O}(n)$ for direct on-chain file storage. The architecture incorporates metadata and traceability controls informed by Federal Aviation Administration (FAA) electronic recordkeeping guidance. The main contribution is an economic framework that models the relationship between tamper-evident maintenance-record provenance, audit workflow duration, aircraft residual value, and operational cost. In a 7-kB experiment conducted on the BNB Smart Chain testnet, CID anchoring reduced gas consumption by 93.9\% compared with direct on-chain storage. Under explicitly stated scenario assumptions, the audit-cost model indicates potential savings of more than 90\%. These results support the technical feasibility of the prototype and illustrate its economic potential, while the estimated financial benefits remain to be validated using operational data.
Blockchain and its killer applications, particularly decentralized finance (DeFi), are gaining widespread adoption, with over 5,200 DeFi projects deployed on mainstream blockchains as of January 2026. At the same time, security risks in DeFi are becoming increasingly serious. However, existing DeFi detection tools usually cover only specific attack types, exhibiting severely limited detection coverage. In this paper, we argue that an effective way to address this gap is to pre-screen vulnerable instances from large volumes of smart contract functions and call sequences. This is motivated by a key phenomenon we term "perilous temporal asymmetry". Inspired by this, we propose DeFiScreener, the first automated pre-screening framework for DeFi attacks that uses historical exploit cases to identify potentially vulnerable functions and call sequences. Given the full source code of a target project, DeFiScreener builds Function Call Trees (FCTs) and generates semantic embeddings for each function using a large language model (LLM), allowing both program structure and function intent to be analyzed together. It then applies a dual-level screening process. At the function level, function embeddings are matched against an Attack Pattern Library of historically exploited functions. At the sequence level, the proposed Attack Pattern Oriented Monte Carlo Tree Search (APO-MCTS) efficiently explores the FCTs and screens vulnerable call sequences. The identified candidates are ultimately passed to an LLM for further interpretive and security analysis. We empirically evaluate the DeFiScreener over datasets comprising 207 real-world DeFi attack incidents. Experimental results demonstrate that DeFiScreener achieves a remarkable 98.55% recall and 84.30% precision in attack pre-screening.
Ethereum non-fungible tokens (NFTs) implement ownership, transfer, authorization, and metadata operations through smart contracts, making contract vulnerabilities a direct risk to digital assets. Existing static analyzers provide efficient rule-based screening but can struggle with application-specific logic, whereas unconstrained large language model analysis may be distracted by irrelevant code or produce inconsistent outputs. We present a vulnerability-detection method that combines vulnerability-focused code slicing, an ERC-721-oriented knowledge base, and constrained DeepSeek analysis. Regular-expression patterns locate candidate statements for reentrancy, integer overflow or underflow, and timestamp dependence. A structure-aware context-window algorithm then extracts line-numbered code slices. DeepSeek analyzes each slice using explicit decision rules and a fixed output schema, and the resulting records support automated batch processing. On 450 NFT contract samples, the full configuration produced 437 positive labels, corresponding to a reported positive-label rate of 97.1%. Removing the external knowledge base reduced this rate to 87.11%, while analyzing complete contracts without the knowledge base reduced it to 73.78%. These results indicate that focused code context and domain constraints materially affect the detector's reported output.
Abdulhadi Sahin, Kemal Akkaya, Sukumar Ganapati, A. Selcuk Uluagac
While blockchain technology has the potential to become one of the enablers of distributed applications and autonomous organizations (DAOs) with its decentralized structure, practical implementations reveal the existence of power and resource concentration at various levels. This concentration raises serious security concerns regarding the core consensus mechanisms, which regulate block creation and the interaction between the nodes of blockchain, potentially preventing the realization of the technology’s full potential. To this end, in this paper, we analyze one of the most commonly deployed consensus protocols, namely Proof of Stake (PoS), from a security perspective. We demonstrate how PoS inadvertently encourages the concentration of power, which may cause some users to leave, thereby endangering blockchain security. Specifically, in PoS, nodes with higher stakes have a greater likelihood of being selected as block proposers, leading to power concentration among a small group of users. This situation increases the risk of collusion and compromise of the consensus mechanism. To address these issues, we propose and analyze an alternative incentive mechanism for PoS by utilizing theories on optimal taxation from behavioral economics. Our proposed model bases the block proposer selection process on a modified and relatively more balanced distribution. It offers preferential treatment to low-stake holders while also integrating a reputation mechanism to mitigate potential Sybil attacks encouraged by equitable rewards. Using a game-theoretic model, we demonstrate the optimal balance of incentives between earning potential and blockchain network sustainability for both high- and low-stake holders. We also conducted extensive performance analyses, including real data from Uniswap, which showed that our proposed mechanism can mitigate inequality and provide an appealing solution for keeping the users in the network to sustain the security of the consensus mechanisms and thus the secure and sustainable operation of blockchain applications.
Gabriela Mariutac, Claudiu Brândaș, Otniel Didraga, Mihai Plesa
The voluntary carbon market (VCM) has faced sustained legitimacy stress since 2023, when peer-reviewed work found that fewer than one in six issued credits represented a real emission reduction. In parallel, tokenisation through Web3 protocols, decentralised autonomous organisations (DAOs), and regenerative finance (ReFi) infrastructures introduced new participants interacting with incumbent registries without a shared coordination framework. Existing scholarship examines commons governance, complex system governance (CSG), and tokenised carbon markets largely in isolation; the gap addressed here is the absence of an integrated system-of-systems (SoS) governance treatment of the tokenised VCM. This study develops and empirically applies a polycentric SoS governance framework for the tokenised VCM, structured around four research questions and five foundational contributions. We treat the tokenised VCM as an SoS that is polycentric in configuration but not by design, and develop a system-of-systems engineering (SoSE) governance reading of it. We reformulate Ostrom’s eight design principles as SoS governance criteria for digital–physical hybrid commons, map each to CSG metasystem functions, and apply the framework to four cases: KlimaDAO, Toucan Protocol, Regen Network, and the post-2023 Verra reforms. Qualitative coding is complemented by on-chain and Base Carbon Tonne spot-price evidence from October 2021 to December 2025. Disclosure by an analytical intermediary acted on the SoS roughly seven weeks before formal regulatory action and was associated with about 90% of the observed bridging slowdown, interpreted descriptively rather than causally. We derive an eight-item reform agenda, six DAO–registry interface specifications, and a five-level governance maturity rubric.
Open access
Systems Engineering Methodologies and Applications
Cüneyt Gürcan Akçora, Murat Kantarcioglu, Yulia R. Gel
In this chapter, you will learn how to write, deploy, and interact with smart contracts using Solidity. We will cover fundamental data types, control structures, functions, and contract organization. You will understand the Ethereum Virtual Machine, how contracts send and receive Ether, and how to use events, modifiers, and visibility specifiers. The chapter also introduces reference types like arrays and mappings, common security practices, and techniques for optimizing gas usage.
Traditional mainstream economics has long relied on the neoclassical paradigm, assuming that economic systems reside in or gravitate toward static equilibrium guided by central coordination or a Walrasian auctioneer. However, real-world markets, industries, enterprises, and socio-economic networks are fundamentally complex adaptive systems composed of a multitude of autonomous decision-making agents. This paper systematically constructs a theoretical framework for "Economic Self-Organization Studies" to examine how economic systems spontaneously generate macro-order, structural patterns, and functional properties without central control, administrative commands, or centralized planning, relying solely on local non-linear interactions among micro-agents. The paper integrates dissipative structure theory, synergetics, hypercycle theory, and evolutionary economics into a unified economic analytical model. We rigorously formulate the thermodynamic conditions of non-equilibrium states, where an open economic system absorbs negative entropy flow d S_e to counteract internal entropy production d S_i (satisfying d S = d S_e + d S_i < 0), thus driving the system toward higher structural organization. Utilizing Haken's slaving principle, we demonstrate how short-term micro-fluctuations (fast variables) are governed by long-term macroeconomic rules and standards (slow variables/order parameters slow_u). Furthermore, we model how local fluctuations delta_x(t) are amplified through non-linear positive feedback when control parameters cross critical bifurcation thresholds lambda_c, while negative feedback provides systemic stabilization. This theoretical framework elucidates the spontaneous formation of spatial industrial clusters via reaction-diffusion mechanisms, price emergence in decentralized continuous double auctions and automated market maker (AMM) algorithms, network topology evolution driven by preferential attachment, and organizational self-governance in Decentralized Autonomous Organizations (DAOs). Finally, the study highlights a shift in policy paradigm from traditional top-down "command and control" to "evolutionary steering," where policymakers focus on shaping system openness, inducing order parameters, and constructing safety guardrails. Ultimately, this research provides a novel dynamical methodology for understanding decentralized market operations and resilient economic system design in an increasingly complex world.
We construct the Settlement Modernisation Index, a panel dataset of 809 reform events across 24 advanced economies between 1993 and 2024, decomposed into three economic channels and three adoption phases. We document an S-curve in inside money elasticity with two interior turning points at SMI = 0.27 and 0.93, separating a liberation phase, a post-global-financial-crisis compliance valley, and a mature-infrastructure recovery phase. We show that settlement modernisation generates network-conditional balance sheet efficiencies through a T2S event-study with year-by-year EMIR decomposition (saturation beta = +0.557, p < 0.01) and an out-of-sample synthetic control null on Switzerland's post-2021 SDX deployment. Applied along the BIS three-layer connectivity taxonomy, the framework forecasts +13.4 percent efficiency recovery from the ECB's Pontes initiative over 2027-2032. Conditional UK and US accession to the Appia composability layer (2028) raises the ceiling to +37.5 percent. Balance-sheet efficiencies from atomic settlement are a property of the bilateral pair, not the node.
Financial fraud detection is challenged by decentralized data, severe class imbalance, and privacy constraints. This paper presents QuantumChain, a secure Quantum Federated Learning (QFL) framework that combines hybrid quantum-classical neural networks, encrypted federated aggregation, blockchain-based auditability, and quantum-secure communication. Each client trains a local hybrid model in which a variational quantum circuit is embedded between classical neural layers, while model updates are protected through homomorphic encryption, threshold secret sharing, and QKD-based keying. A permissioned blockchain records aggregation events and supports reputation-weighted trust among participants. We evaluate QuantumChain on financial transaction data using a compact, size-matched classical baseline to isolate the effect of the quantum layer. Results show that the HQNN achieves comparable accuracy while improving fraud-class recall in most settings, reaching 94.6% recall compared with 93.2% for the classical model. The Deep QLayer improves performance in full-data settings, suggesting that added circuit depth helps recover representational capacity when the shallow circuit becomes limited. Mixed-state simulations further show that the recall trend persists under non-ideal quantum evolution. In federated deployment with 10 heterogeneous clients, global accuracy increases from 97.7% to 98.8% over five rounds before stabilizing. These results show that QuantumChain can integrate depth-aware hybrid quantum models into a secure federated fraud-detection pipeline while maintaining stable global convergence.
Maximal extractable value (MEV) arises when privileged participants select, exclude, insert, or reorder pending transactions for private gain. We specify and analyze the Themis Consensus Extension v1, first published by Mangata in 2021. The design separates value extraction by reordering (VER) from value extraction by denial (VED). For VER, block construction and execution occur across consecutive producers: one producer commits a transaction set, and the next derives a publicly verifiable, deterministic, previously un- predictable seed and executes a seed-determined, dependency-preserving permutation. For selective VED, a user may encrypt a transaction for a designated builder and executor. The builder removes an outer layer and commits the opaque inner ciphertext; the executor reveals and executes the plaintext only after commitment. Under selfish but non-colluding validators, an adversary below the underlying consensus fault threshold, secure cryptography, and accountable role performance, the construction limits unilateral post-commit ordering control and hides transaction intent from relays and the builder. It does not provide send-order or receive-order fairness, complete censorship resistance, resistance to builder-executor collusion, or per-transaction price guarantees. We analyze probabilistic extraction, spam, dependent transactions, decryption liveness, session boundaries, total denial, and threshold coalitions. We also document the initial Aura-based Substrate implementation and its subsequent transition to a BABE-based sr25519/VRF seed path, together with delayed execution, Fisher-Yates shuffling, and Xoshiro256++. The result preserves the original proposal while narrowing its claims to explicit assumptions.
To meet the throughput demands of modern blockchain systems, protocols for State Machine Replication (SMR) increasingly have many processors disseminate blocks of transactions in parallel, with consensus then establishing a total ordering on the blocks of all producers. Such designs face a choice as to when a block may enter the ordering. Certified approaches wait for a quorum to attest a block's availability, which is robust but adds message delays to every transaction. Uncertified approaches let proposals reference blocks immediately, which is fast but degrades rapidly when referenced data must be fetched on the critical path. Raptr, the state of the art, takes a middle course, finalising the longest prefix of the leader's proposal that a quorum holds, so that no processor ever blocks or fetches. The remaining weakness is sensitivity to order: if the data behind a single early batch is withheld, the proposal finalises little or nothing, so individual faulty producers can still deny the system its optimistic path. We present Multimmit, a protocol for $n \ge 5f+1$ processors combining a consensus layer requiring one round of voting per view with multi-chain data dissemination. Votes are cast relative to the leader's proposal, reporting per chain how far the voter can support it, and may themselves attest fresh blocks beyond it. A transaction block disseminated at time $t$ is ordered by $t+3δ$ in expectation and $t+2δ$ at best, measured from the block's dissemination rather than the leader's proposal. Degradation under faults is graceful: a faulty producer delays only its own chain's blocks, costing other chains at most a one-view wait for placement. No leader can both finalise its leader block and exclude a fresh, well-circulated block of an honest chain. Consensus traffic is tens of kilobytes per view, independent of transaction volume.
Out of Time proposes a new philosophy of law for an age in which technological, environmental, and political change outpaces the legal institutions designed to govern it. Through the original concept of the "anachronism clause," Northon Salomão de Oliveira argues that every legal system silently depends on assumptions about the world that inevitably become outdated. The central challenge of twenty-first-century jurisprudence, therefore, is not merely to create valid rules, but to develop institutions capable of recognizing and correcting their own obsolescence before legal certainty becomes legal illusion. Drawing on the works of Hans Kelsen, H. L. A. Hart, Ronald Dworkin, Robert Alexy, Lon L. Fuller, John Finnis, and other leading legal philosophers, the book examines how this hidden structural problem emerges across the defining challenges of our century, including artificial intelligence, climate change, democratic legitimacy, biotechnology, international security, economic inequality, resource sustainability, mental health, disinformation, quantum computing, space governance, decentralized finance, longevity, and persuasive technologies. Rather than treating these issues as isolated fields of regulation, Out of Time reveals them as expressions of a single philosophical question: How can law remain legitimate when the world it was designed to govern no longer exists? Blending rigorous legal theory with philosophical reflection and memorable narrative, Out of Time offers an original framework for understanding the relationship between law, time, institutional adaptation, and the future of human civilization. It is a work intended for scholars, jurists, policymakers, and anyone interested in the future of legal thought in an era of accelerating change. Philosophy of Law Jurisprudence Legal Theory Institutional Adaptation Artificial Intelligence and Law Space Law Legal Obsolescence Philosophy of Law, Jurisprudence, Legal Theory, Legal Philosophy, Constitutional Theory, Constitutional Law, Rule of Law, Legal Positivism, Natural Law, Legal Interpretation, Comparative Law, International Law, Public Law, Global Governance, Democratic Legitimacy, Human Rights, Justice Theory, Institutional Design, Institutional Adaptation, Legal Certainty, Legal Innovation, Legal Reform, Legal Obsolescence, Institutional Resilience, Adaptive Governance, Future of Law, Emerging Technologies, Law and Technology, Artificial Intelligence, AI Governance, AI Regulation, Algorithmic Decision-Making, Digital Governance, Digital Rights, Digital Society, Cyber Law, Data Governance, Quantum Computing, Quantum Law, Evidence Law, Space Law, Space Governance, Outer Space Treaty, Extraterrestrial Resources, Climate Change Law, Environmental Law, Sustainability, Intergenerational Justice, Resource Governance, Biotechnology Law, Bioethics, Longevity, Mental Health Law, Disinformation, Information Integrity, Persuasive Technology, Behavioral Regulation, Economic Inequality, Decentralized Finance, Financial Regulation, Regulatory Theory, Institutional Trust, Political Philosophy, Ethics of Technology, Future Studies, Civilization Studies, Legal Systems, Normative Theory, Twenty-First Century Law, Northon Salomão de Oliveira Northon Salomão de Oliveira ORCID: 0009-0007-4038-0609 Biography Northon Salomão de Oliveira is a Brazilian writer and jurist specializing in communication law, whose intellectual career is distinguished by its interdisciplinary approach, integrating Law, Communication Studies, Advertising, Marketing, Philosophy, Anthropology, Psychology, Psychiatry, Organizational Theory, and Literature. His scholarly work explores the dynamic relationship between law, technology, culture, and society, addressing some of the defining challenges of the twenty-first century, including climate change, artificial intelligence and automation, global governance and democracy, biotechnology and human survival, international security, economic inequality, the sustainability of natural resources, mental health, disinformation, and the ethical, philosophical, and legal reconstruction of civilization. His editorial portfolio includes books published in different international markets by distinguished publishers such as the Portuguese-Brazilian Kotter Editorial and the British Camden House, in addition to worldwide digital distribution through platforms including Amazon KDP and Google Play Books. In July 2026, he published The Odyssey (English Edition) and A Odisseia (Brazilian Edition), companion collections featuring a curated selection of sixty works chosen by his readers. Beyond his books, he has authored more than 1,500 articles published in academic repositories, legal platforms, and major media outlets, including SSRN (Elsevier), SciELO, Academia.edu, Zenodo (CERN), Folha de S.Paulo, Administradores, Jus, and Jusbrasil.
After Turing: The Fold Machine is the standalone 396-page paper for the completed Classical Computation branch of the third clean-room reconstruction of Smithian Fold Theory (SFT). From separately admitted Foundation, Mathematics and Information Science receipts it derives, in dependency order, Formal Computation; Computability; Computational Complexity; Algorithms and mathematical data structures; Semantics and mathematical programming theory; Concurrent and Distributed Computation; Cryptography and Computational Security; Learning and Intelligence Theory; and Scientific Computation. The branch does not import a Turing machine, lambda calculus, conventional complexity class, probability cause, cryptographic hardness assumption, pretrained model, fitted parameter, floating proof value, application answer or earlier SFT derivation as a premise. Every object is an exact generated finite carrier, held label, relation, trace, resource ledger, interface, observation class or proof record. Empty One is structural rather than numerical zero; complementary held labels replace negative proof quantities; and randomized algorithms execute complete registered deterministic schedule support rather than assume an uncaused stochastic transition. The frozen inventory contains 113 dependency-ordered claims. Their grammars execute 28,928 generated candidates and preserve 28,928 decisions, 113 unique survivors, 113 depth-independent base/successor certificates, 452 adverse controls and 113 implementation-distinct validations. The manuscript documents every claim in full: dependencies; exact theorem; eight structural axes; all first-failure elimination counts; unique survivor; minimality; named-shape uniqueness; operational laws; live witnesses; induction certificate; controls; meaning; correspondence boundary; limitations; and exact source, census, seal, validator and engine-receipt identities. The central result is a native Fold machine whose states, words, actions and computations preserve complete provenance. The branch derives universal interpretation only after languages, automata, rewriting, recursion, binding, abstract machines, circuits, processes and composition close. Halting and incompleteness follow from exact self-description and held complement operations. Security requires exact adversary and resource grammars. Learning retains complete hypothesis alternatives and sealed evaluation. Scientific simulation proves consequences of its registered model but does not select natural laws. The accompanying open release contains the PDF, complete Markdown manuscript, frozen inventory, all 113 claim packages and candidate/decision ledgers, executable sources, independent validators, receipts, evidence map, tests and checksum ledger.
There Is No Nothing, Methods Paper 00 version 0.3.0, preserves the two inaugural premise-free results and publishes the shared two-layer roadmap for the Smithian Fold Theory knowledge tree: secure each branch foundation at its exact evidence boundary, then extend it across the full field without treating a publication as a permanent lock. Later branch laws remain separate admissions and are not retroactive premises. The accompanying standard-library-first Python repository implements one fail-closed admission engine for registration, dependency and provenance closure, zero-parameter and no-axiom enforcement, generated candidate enumeration, exactly-one-survivor forcing, minimality, named-shape uniqueness, adverse controls, cryptographic sealing, implementation-distinct recomputation, empirical target custody and publication gates. The engine and verification authority remain cryptographically sealed; an adverse or halted result cannot be converted into a pass by editing the authority surface. The paper gives full candidate, decision, proof, control, source, validator, seal and receipt identities; an engine threat model; the blind empirical protocol; the open licensing and Ernos Labs conformance model; a supersession ledger for prior SFT generations; and a file-level paper-to-evidence map. Version 0.3 publishes the ordered full-field roadmap through Chemistry while Materials remains outside this coordinated release. Branch completion always means dated current-evidence completion at a declared boundary and remains open to lawful extension, correction and falsification.
Christian Cachin, David Lehnherr, Juan Villacis, François-Xavier Wicht
Sender untraceability hides the account spent by a cryptocurrency transfer among a set of candidates, its masking set. What a transfer does to that set separates two designs: classical schemes retain the whole set and append a nullifier marking the spent account, so the ledger grows with every transfer; constant-state schemes instead consume and replace the entire set. We ask how this choice affects synchronization. We formalize the two designs as the linear and constant untraceable asset transfer objects (LUAT and CUAT) and locate them in the consensus hierarchy. In LUAT, transfers from distinct accounts commute. Its consensus number is 2, compared with 1 for standard asset transfer, independently of the masking-set size and of the untraceability notion, and LUAT is starvation-free. Partitioning the accounts into fixed masking sets lets exhausted sets be garbage-collected without increasing that number. In CUAT, a transfer consumes and replaces every account of its masking set, so two transfers whose sets intersect cannot both take effect. We formalize this with the conflict graph on masking sets, whose edges join sets sharing an account. Under weak untraceability, which protects a transaction in isolation, the consensus number is unbounded already for one-round protocols. Under strong untraceability, which protects against an observer of the complete history, untraceability holds on a history exactly when any two accounts sharing a masking set occur in the same number of the masking sets in it. This uniform incidence bounds the conflict graph, and matching constructions attain it, so the consensus number is determined exactly and grows quadratically in the masking-set size. Finally, CUAT is not starvation-free. The two objects therefore pay for the same privacy differently: LUAT in storage, CUAT in synchronization and fairness.
Privacy-preserving machine learning auditing protocols allow auditors to assess models for properties such as accuracy or fairness, without revealing their internals or training data. This makes them especially attractive for auditing models deployed in sensitive domains such as healthcare or finance. For these protocols to be meaningful in real-world audit settings, though, their guarantees must reflect how the model will behave once deployed, rather than merely certifying its behavior during an audit. Existing security definitions often miss this mark: most certify model behavior only on a fixed audit dataset, without ensuring that the same guarantees generalize to other datasets drawn from the same distribution. As we show, this gap allows a model provider to attack many cryptographic model certification (CMC) schemes built on secure zero knowledge proofs (ZKP) by carefully engineering training data, resulting in models that exhibit benign behavior during an audit, but pathological behavior in practice. For example, we empirically demonstrate that an attacker can certify that a model achieves over 99% accuracy on an audit dataset, but less than 30% accuracy on fresh samples from the same distribution. To address this gap, we formalize rigorous cryptographic security notions tailored to CMC frameworks, introduce a generic protocol template, and prove that it satisfies these requirements. Our results thus offer both cautionary evidence about existing approaches and constructive guidance for designing secure, privacy-preserving ML auditing protocols.