AI now generates mathematics, code, and claims faster than anyone can review them; the limiting resource is no longer generation but trust. The honest response to "I don't trust it" is not "trust me" — it is "here is the check; run it." This deposit is a working demonstration of that response, run on the most scrutinized AI-math result of 2026: the July 2026 counterexample to the 87-year-old Jacobian Conjecture announced by Levent Alpöge with an AI as collaborator. A human directed Claude Code (Opus 4.8) as the proposer, with every mathematical claim compiled and machine-checked by Attestral, a verifier that signs an ed25519 certificate only when its own checker passes. The proposer cannot certify; the adjudicator has no stake in the proposer being right. The output is proof-carrying rather than model-asserted. Working only from the public polynomial list, the loop: independently verified the counterexample (det(JF) ≡ −2 exactly, a rational triple collision); reverse-engineered its mechanism (a non-nilpotent, degree-3 étale endomorphism — outside the classical nilpotent search space); found its hidden cubic (a three-cube-root Cardano fiber) and built an infinite tower of derived counterexamples; mapped the surrounding z-linear construction space (fold-parity obstruction, uniqueness skeleton); proved its natural four-dimensional generalization obstructed at every compensator degree in the Lean kernel; caught three of its own errors mid-run — including a finite-field prime silently collapsing to p = 3 — and discarded them; and reported an honest wall on the nilpotent normal form. Days later the same loop, unchanged, verified the counterexample to the Gaussian Moments Conjecture (Long, arXiv:2607.18186) posted in the same wave. Every claim carries a certificate any reader can re-verify offline: 20 Lean 4 kernel proofs (Mathlib, axiom-audited) for the load-bearing theorems and 23 exact-symbolic certificates (including the Gaussian-Moments companion) for the exploratory identities — two tiers, never blurred. The artifact bundle contains all 43 signed certificates, the Lean sources, the published verification key, and a standalone verifier needing only Python and pynacl: python verify_all.py → 43/43 certificates verified offline, ALL VALID. Scope, stated plainly: we verify and classify; the counterexample is Alpöge's. Certificates settle correctness only; one structural overlap is credited (Shaska, arXiv:2607.20210); no progress is claimed on the still-open plane (ℂ²) case. Interactive companion: https://simgen.dev/attestral/jacobian-counterexample/
Open access
2 source records
Polynomial and algebraic computation
Cryptography and Residue Arithmetic
Advanced Differential Equations and Dynamical Systems
The article presents a comprehensive analysis of the legal framework for public procurement in Ukraine and the European Union through the lens of balancing transparency requirements with the protection of confidential commercial information. The key principles of the Law of Ukraine “On Public Procurement” and Directive 2014/24/EU, which establish the foundations of equal treatment, non-discrimination, proportionality, and procedural openness, are examined. The practical outcomes of the Prozorro electronic procurement system are analyzed; since its launch, the system has saved over USD 8.7 billion in public funds and increased the number of bidding participants from 14,000 to 140,000. The main corruption risks at various stages of the procurement cycle are systematized – from planning and needs formulation to tender evaluation and contract execution. Based on an analysis of international studies using the Analytic Hierarchy Process (AHP) and principal-agent theory, it is established that tender evaluation is the most corruption-prone stage, with information asymmetry being the key factor. It is shown that under martial law conditions, simplified procurement mechanisms necessary for operational efficiency simultaneously expand the space for abuse. The feasibility of applying zero-knowledge proof (ZKP) protocols as a cryptographic instrument that enables combining public verification of participants’ compliance with qualification requirements while preserving the confidentiality of their commercial data is substantiated. The main classes of ZKP – interactive protocols, zk-SNARKs, zk-STARKs, and Bulletproofs – their properties, trade-offs, and practical applications in financial compliance, identity verification, and anonymous whistleblowing systems are examined in detail. Specific scenarios for integrating ZKP into public procurement procedures are considered: proof of financial capacity without disclosing reporting details, confirmation of the absence of conflicts of interest based on encrypted registry data, verification of the correctness of electronic auction results, and authentication of the supply chain. Key implementation barriers are identified: regulatory recognition of cryptographic proofs as equivalents to traditional documents, technical complexity and institutional capacity, performance and scalability concerns, legal liability for protocol errors, and compliance with GDPR requirements. A phased model for integrating ZKP into the Prozorro infrastructure is proposed, and recommendations for necessary legislative and institutional changes are formulated, including updating the Public Procurement Reform Strategy for 2024–2026, establishing independent cryptographic audit mechanisms, and developing methodological guidelines for contracting authorities.
The article presents a comprehensive analysis of the legal framework for public procurement in Ukraine and the European Union through the lens of balancing transparency requirements with the protection of confidential commercial information. The key principles of the Law of Ukraine “On Public Procurement” and Directive 2014/24/EU, which establish the foundations of equal treatment, non-discrimination, proportionality, and procedural openness, are examined. The practical outcomes of the Prozorro electronic procurement system are analyzed; since its launch, the system has saved over USD 8.7 billion in public funds and increased the number of bidding participants from 14,000 to 140,000. The main corruption risks at various stages of the procurement cycle are systematized – from planning and needs formulation to tender evaluation and contract execution. Based on an analysis of international studies using the Analytic Hierarchy Process (AHP) and principal-agent theory, it is established that tender evaluation is the most corruption-prone stage, with information asymmetry being the key factor. It is shown that under martial law conditions, simplified procurement mechanisms necessary for operational efficiency simultaneously expand the space for abuse. The feasibility of applying zero-knowledge proof (ZKP) protocols as a cryptographic instrument that enables combining public verification of participants’ compliance with qualification requirements while preserving the confidentiality of their commercial data is substantiated. The main classes of ZKP – interactive protocols, zk-SNARKs, zk-STARKs, and Bulletproofs – their properties, trade-offs, and practical applications in financial compliance, identity verification, and anonymous whistleblowing systems are examined in detail. Specific scenarios for integrating ZKP into public procurement procedures are considered: proof of financial capacity without disclosing reporting details, confirmation of the absence of conflicts of interest based on encrypted registry data, verification of the correctness of electronic auction results, and authentication of the supply chain. Key implementation barriers are identified: regulatory recognition of cryptographic proofs as equivalents to traditional documents, technical complexity and institutional capacity, performance and scalability concerns, legal liability for protocol errors, and compliance with GDPR requirements. A phased model for integrating ZKP into the Prozorro infrastructure is proposed, and recommendations for necessary legislative and institutional changes are formulated, including updating the Public Procurement Reform Strategy for 2024–2026, establishing independent cryptographic audit mechanisms, and developing methodological guidelines for contracting authorities.
Sourena Khanzadeh, Daniel Platnick, Marjan Alirezaie, Hossein Rahnama
Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data. Users require a sovereign system to securely own, govern, and disclose their context while remaining compliant across regulated domains with strict provenance, interpretability, and policy adherence. Perspective-aware AI approaches this by transforming a user's aggregated personal data into a structured identity model called a \emph{Chronicle}: a temporal knowledge graph that represents and grows with the user. Chronicles support the secure disclosure of context across federated networks. A Chronicle holder may expose a queryable, authorized view that a third-party agent may consult without centralizing anyone's data. This paper explores the problem of minimum-necessary disclosure across domain boundaries: when a requester's agent queries a Chronicle, how can the system constrain its response to release only what the requester's relationship, stated purpose, and specific task require? We propose \textbf{Provenance Preserving Chronicles} (PPC), a federated protocol that compiles each holder's Chronicle into a compact \emph{authorized evidence subgraph} governed by one rule: \emph{share no more than the request requires}. Holders keep local sovereignty; an access controller projects relationship-aware views over domain-expert ontologies; and a two-phase flow returns provenance-linked text first, releasing raw artifacts only after explicit holder approval. We frame the problem, map gaps in blockchain, P2P, and holder-sovereign designs, define the core constructs, and sketch the protocol with an explicit threat model.
Yifeng Ye, Rongji Huang, Gerui Wang, Mingchao Wan · 7 authors
In blockchain systems, peer-to-peer (P2P) overlay networks play a crucial role in providing reliable, scalable and efficient message-delivery services to upper layers. However, the consensus layer and the underlying P2P network remain mutually opaque in existing blockchains, waiving the opportunity for further improvement. In contrast to other P2P applications, blockchain can naturally be abstracted as a state machine. We therefore leverage this abstraction to record network topologies and latencies in a trusted and coordinated manner. With this support, we propose three improvements to rotating-leader consensus protocols and their underlying P2P networks: (1) accelerating leader rotation; (2) introducing a reliable-broadcast paradigm that employs tree-based dissemination in the normal case and falls back to gossip only when necessary; and (3) constructing latency-aware dissemination trees. We integrate the above ideas into Tendermint and libp2p, and conduct empirical evaluation on Amazon EC2 platform using up to 300 nodes distributed across 10 regions. The results demonstrate that, compared with gossip-based dissemination over the same topology, our prototype improves peak throughput by up to $7.26\times$.
Large-scale biometric identification in outsourced settings requires two properties simultaneously: biometric templates and queries must remain protected during computation, and the encrypted similarity outputs produced by an untrusted compute node must be verifiably correct before any application result is released. Existing FHE-based biometric systems primarily address confidentiality, while practical verifiability introduces two bottlenecks in the underlying encrypted 1:N matching layer: rotation- and bandwidth-heavy similarity evaluation and the high cost of proving repeated homomorphic similarity traces. We present BioZKFHE, a framework for scalable encrypted biometric identification via verifiable homomorphic similarity evaluation that combines BGV homomorphic computation with committee-mediated proof opening/decryption and smart-contract verification of opened proof batches. To reduce encrypted storage and avoid rotation-heavy encrypted 1:N matching, we propose Single-Coefficient Multi-Value (SCMV) packing, which binds multiple quantized embedding values into each plaintext entry through base-T expansion. To make proof generation practical, we propose Parallelizable and Verifiable Similarity Computation (PVSC), which exploits the Double-CRT execution structure of BGV to decompose each blockwise similarity trace into parallel proof instances that are opened and checked before result release. Under standard lattice assumptions and explicit committee/verifier assumptions, we analyze recoverability, noise growth, confidentiality, encrypted-output integrity, and finalized-result integrity. Experiments on FaceNet and MobileFaceNet show near-lossless biometric utility, up to 67 percent encrypted-storage reduction, and about 22 to 44 seconds end-to-end proof-verified runtime for 10k to 40k templates.
In Ethereum, transaction inclusion is rarely in question; what matters is the delay until inclusion. Currently, block builders could exercise censorship across consecutive blocks, threatening time-critical applications, such as on-chain auctions. To mitigate this risk, existing proposals such as FOCIL, scheduled for deployment in late 2026, assign a committee to list transactions for mandatory inclusion. However, no committee member is held accountable for the actual inclusion of the transactions: an adversary can bribe the entire committee to omit any transaction for less than 2 Euro per block under current conditions. We argue that accountability, i.e., requiring all exclusion decisions to be publicly disclosed and verifiably complete, with violations attributable to a specific party, substantially raises censorship costs. To this end, we propose Fair Forward Inclusion Lists (FairFIL) as an accountable censorship resistance mechanism for Ethereum. In FairFIL, every builder must publish all transactions the builder chooses to censor, subject to a protocol-anchored policy; a committee verifies the completeness and validity of this disclosure. The subsequent builder must include these transactions, forfeiting the full block reward upon any omission. Therefore, under FairFIL, extending censorship beyond a single slot requires an assembler to forfeit a full block reward. We show that compliance is rational for all participants within our behavior model. Our empirical evaluation on Ethereum mainnet indicates that multi-block censorship costs one order of magnitude more than under existing proposals, while leaving the builder's MEV extraction freedom largely intact. Initial measurements further suggest that the mempool consistency FairFIL requires is met in practice.
Intent-based decentralized exchanges delegate execution to a competitive class of agents -- solvers -- whose behavior is shaped by protocol-designed reward rules. We measure how a change to those rules reshapes who captures value, using a governance-dated natural experiment: CoW Protocol CIP-74 (effective 8 December 2025), which replaced a fixed solver-reward cap with one tied to protocol revenue and introduced an ad-valorem volume fee. Using daily solver shares over 395 days, we find the reform reallocated trading value by order size. The robust signature is a monotone size gradient: concentration fell in small orders and rose in large ones across four order-value buckets (Spearman rho=1.00, exact permutation p=0.042) -- a pattern that survives dropping the single largest solver. Aggregate concentration also rose (volume-weighted HHI 0.176->0.241), substantially carried by the incumbent top solver. By trade count the market de-concentrated (count-HHI -0.060). A simple solver-economics model rationalizes the pattern: an ad-valorem fee is competitively neutral, while a revenue-linked reward cap raises the marginal payoff to inventory-rich solvers on large orders -- consistent with restricted-entry predictions (Chitra et al. 2024). A control venue (UniswapX) shows no matching break. We detect no change in average execution quality (~7 bps bound). A triple-difference exploiting a February 2026 fee cut is directionally consistent but underpowered. Reward design measurably reallocates who captures value in intent markets, without moving the average price users receive.
Why do local elected representatives facing similar institutional constraints choose different strategies? This dissertation develops a theory of strategy choice under incomplete decentralization, where municipal councilors remain electorally accountable but depend on bureaucratic and higher-level political actors for implementation, finance, and approval. Administrative, fiscal, and political constraints define the institutional setting, while leverage, the capacity to induce response, and cover, protection from sanction, capture councilors’ unequal positions within it. Drawing on more than 450 interviews, 67 municipal council meeting transcripts, and an original survey of 506 current and former councilors in urban India, I distinguish collaborative strategies based on coordination and follow-up from combative strategies based on public pressure and cost-imposition. Collaboration overwhelmingly dominates. Perceived bureaucratic discretion is the strongest correlate of movement toward combativeness, while leverage and cover do not reliably predict the binary shift between strategies. Instead, leverage more clearly distinguishes procedural from discretionary forms of collaboration. These findings show that incomplete decentralization does not eliminate local representation. It channels representation through continued dependence on actors councilors do not command and shifts attention from whether councilors collaborate to how they collaborate and when they escalate.
Direct user-specified research topic: Autonomous agent wallets spend under English mandates like 'only stablecoin swaps under $200 daily, never bridge, never touch unaudited pools', yet deployed policy engines (Safe Transaction Guards, ERC-7579 modules, session-key allowlists) enforce only stateless numeric and selector limits and cannot express 'unaudited' or 'per day', while a naive base-model prompt over raw hex calldata cannot recover function, recipient or token flow and confabulates verdicts. Evaluate a tool-augmented structured-decoding LLM judge that fetches ABIs from Sourcify and Etherscan, decodes calldata including multicall and Permit2 payloads, simulates via eth_call state overrides for token-flow and approval deltas, attaches counterparty features (contract age, verification), and emits constrained JSON: in_policy, violated_clause quoted verbatim, offending_calldata_field. Read Ethereum and Base: ERC-20 Transfer/Approval logs, Uniswap/1inch routers, Across/Stargate bridges, Permit2 at 0x000000000022D473030F116dDEE9F6B43aC78BA3. Measure macro-F1 and clause-attribution precision on 600 hand-labeled mandate/transaction pairs plus replay accuracy on transactions whose approvals owners later revoked, beating a naive raw-hex prompt and a Safe Guard numeric-allowlist baseline. Deliver as the prototype a minimal runnable Python MCP server (stdio) exposing the priced AI tool screen_transaction_against_mandate that invokes a language or ML model over onchain data to produce its output, with a typed input/output schema, an x402-style pay-per-call metering stub that records a per-call price in USDT and emits a settlement receipt, and one smoke test that exercises the tool end to end.. Investigate this topic end-to-end: survey the state of the art, identify a concrete tractable research question within it, design and run an experiment, and report results.
The growing presence of institutional capital in crypto asset markets has reopened the debate on whether Bitcoin and similar digital assets can act as safe havens, the way gold or sovereign bonds have been built historically. This thesis tackles that question with a quantitative framework rather than the qualitative arguments that dominated the early literature. The dataset covers November 2019 to May 2026 (2,380 daily observations for Bitcoin, 2,381 for the full asset universe). I fit GARCH-t and EGARCH-t models to capture conditional variance, apply Extreme Value Theory to isolate the tail directly, and run Monte Carlo simulation to estimate capital requirements over 30-day horizon.
Cryptocurrency's convenience is a convenient truth — granted here in full, with receipts. A permissionless ledger settles across borders without account approval, banking hours, or correspondent chains; Nakamoto designed exactly that, on purpose. The correction is that the convenience and the danger are the same property: what makes the transfer fast and unstoppable is that it is final — no chargeback, no administrator, no undo. Institutions can price that trade. A person cannot, and the proposal is that the rational personal policy is a wall, not a judgment call. Offered as a proposal, not a result.
Part 2: Enhanced Pure-Milk Green Finance Matrix – Toward Net-Positive Regenerative Dairy Systems builds upon the original prospectus (DOI: 10.5281/zenodo.21538664) by integrating abundant low-cost clean energy, advanced on-site CO₂ scrubbers, intelligent multi-functional greenbelts, and decentralized vertical hydroponics. This evolution transforms New Zealand dairy farms from environmentally sustainable operations into active net-positive regenerative systems that function as carbon sinks, biodiversity enhancers, and water quality producers, while maintaining or increasing economic output. By leveraging current technological convergence — including satellite virtual fencing, AI-driven optimization, renewable power, and closed-loop nutrient cycling — the model delivers accelerated ROI, greater resilience for smaller farms, and a scalable blueprint for global pastoral agriculture. The enhanced framework resolves long-standing tensions between productivity and environmental stewardship, positioning New Zealand as a leader in high-tech regenerative food systems for the 21st century. (Word count: 148 – suitable for presentations, funding proposals, or DOI metadata) Keywords (for search, tagging, academic indexing, or presentation metadata) Primary Keywords: Pure-Milk Green Finance Matrix Regenerative dairy farming Sustainable intensification Net-positive agriculture New Zealand dairy transformation Technical & Solution Keywords: Virtual fencing On-site Direct Air Capture (DAC) Decentralized vertical hydroponics Methane-scrubbing greenbelts Agritech closed-loop systems Renewable energy integration Carbon sequestration farming Strategic Keywords: Macroeconomic transformation Green finance KiwiSaver reinvestment Shared-equity sharemilking Global agritech IP export Climate-smart agriculture Net-zero dairy
Open access
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Agriculture Sustainability and Environmental Impact
ComputeGrid is a concept paper and feasibility framework for a utility-integrated network of provider-owned compute nodes hosted at commercial buildings, public facilities, and — through a heat-recovery variant — homes. Hosts receive full metered reimbursement of node electricity plus a separate credit; nodes are aggregated by an orchestration and settlement platform (ComputeGrid OS) into one secure, grid-aware, dispatchable compute layer beneath hyperscale data centers. Version 3.0 evaluates the concept against two structural facts: residential retail electricity is the most expensive power a compute operator can buy, and a decade of distributed-compute ventures (spot marketplaces, deploy-first token networks, and heat-recovery operators) shows which configurations survive. The paper therefore leads with commercial and public-building deployment, admits residential nodes only where waste heat displaces heating the host would otherwise purchase, and requires every site to pass at least one of four economic qualifiers — near-commercial power price, monetizable heat, a priced locality premium, or measurable grid-flexibility value — before hardware is committed. The paper includes a two-sided illustrative unit ledger, host consumer-protection and property-rights baselines, rules preventing host-purchased “income” hardware, a staged offtake-first pilot plan with published kill criteria, and a claim framework that treats all economics as illustrative pending Stage 0 diligence. It is an open concept paper, not peer reviewed; no field deployment or empirical dataset is reported. Version 1.0 drafting was assisted by OpenAI ChatGPT; Versions 2.0 and 3.0 critique and revision were assisted by Anthropic Claude under the author’s direction. The author is responsible for the final claims and release.
This study investigates critical success factors crucial for the effective implementation of blockchain-based smart contracts in supply chain management. Through qualitative content analysis of expert interviews, diverse perspectives from industry professionals and blockchain technologists were synthesized. The findings emphasize critical dimensions such as technological infrastructure, stakeholder collaboration, regulatory compliance, data privacy, security, organizational culture, and change management. These factors collectively form a comprehensive framework essential for successful adoption. This research offers valuable guidance for organizations aiming to integrate blockchain-based smart contracts into supply chain operations. The insights derived from eight expert interviews provide strategic direction for practitioners, policymakers, and academics navigating the complexities of blockchain and smart contract technology in supply chain ecosystems.
Online disruption of financial systems is one of the most meaningful paradigmatic shifts between centralized institutional frameworks and decentralized blockchain-based infrastructure. In the present research paper, the author thoroughly reviews how blockchain technology and FinTech innovation can transform financial services, payment systems, and capital markets. Our inquiry focuses on the role of distributed ledger technologies (DLTs) in mitigating such areas as transaction speed, cost reduction, improved security, and transparent audit trails. The article dwells upon the ciphertext-policy attribute-based encryption (CP-ABE) systems that are embedded into blockchain networks and used to offer advanced access control and privacy in a multi-cloud financial system. The main technological advancements that are identified by our research are smart contracts, decentralized finance (DeFi) protocols, and blockchain-based custodial solutions. We examine experimental applications that show the increase in performance in terms of transaction processing, efficiency in encryption, and validation of authorization in blockchain-enabled financial networks. The paper deals with issue of regulation, and scalability as well as integration of old financial systems. Results indicate that financial systems based on blockchain are able to cut transaction costs by 87 percent and still have the same level of cryptographic security as current banking systems. The study will add value to comprehending the best blockchain set-ups of financial services providers and give recommendations based on evidence about digital transformation strategies. Future trends are creation of interoperable blockchain networks, high-privacy preserving technologies, and regulatory frameworks that facilitate financial innovation.
This article presents a novel, first-of-its-kind predictive RegTech solution to address this challenge using machine learning methods. The rapid global adoption of Real‑Time Payment Systems (RTPS) has created a significant “velocity gap” in regulatory compliance. While expanding financial accessibility, these systems introduce new vulnerabilities into existing AML frameworks. Static, rule-based systems and batch processing architectures cannot effectively counter money laundering in sub-second transaction environments. This limitation enables sophisticated activities such as digital layering and smurfing that move illicit financial flows across networks faster than regulatory systems can react. The core of our solution involves the use of graph neural networks (GNNs). This approach enables real-time, pre-settlement risk assessment, preventing illicit transactions before execution. Unlike traditional AML systems that evaluate transactions in isolation, this framework analyzes the entire transaction network to detect coordinated illicit behavior in real time. GNNs capture complex structures such as loops, funnels, and bridges that indicate illicit activity. To support efficient implementation, the framework integrates Event-Driven Architecture (EDA). The proposed architecture introduces the concept of the Zero-Knowledge Proof (ZKP) protocol layer in order to make risk-sharing possible in a secure manner across multiple institutions. This allows the banks to cooperate with each other in order to combat financial crimes while maintaining their data sovereignty. With predictive graph analytics, event-driven integration, and private cooperation, the proposed architecture enables proactive compliance in real-time payment environments, including real-time payment systems such as FedNow, against high-speed financial crime.
Cüneyt Gürcan Akçora, Murat Kantarcioglu, Yulia R. Gel
This chapter traces the intellectual and technological lineage of Bitcoin and digital money. While Nakamoto’s white paper launched Bitcoin, its roots extend through decades of economic theory, cryptographic innovation, and activist movements. We examine how the Austrian and Chicago Schools of Economics provided a framework for stateless and non-inflationary money, and how Cypherpunk ideals shaped the push for privacy and decentralization. The chapter reviews early experiments with digital currencies such as DigiCash, b-money, and e-gold, highlighting the technical shortcomings, regulatory battles, and user adoption barriers that prevented their success but furnished essential building blocks for Bitcoin. We then contrast the classical financial attributes of money—medium of exchange, unit of account, and store of value—with additional digital requirements such as offline spendability, identity-less spendability, and fungibility. Finally, we show how Bitcoin resolved the long-standing double-spending problem without a central authority through Proof of Work, situating it as both a culmination of earlier efforts and the starting point for a new era of cryptocurrencies.
Cüneyt Gürcan Akçora, Murat Kantarcioglu, Yulia R. Gel
In this chapter, you will explore the vulnerabilities and attack surfaces of blockchain systems that arise from their open, permissionless nature. You will learn how privacy and security issues manifest at different layers of blockchain architecture, including peer-to-peer networking, transaction propagation, block mining, and smart contract execution. The chapter introduces you to key privacy challenges such as identity leakage, transaction linkability, and deanonymization in UTXO and account-based systems. You will also study how adversaries can mount attacks that exploit consensus protocols, timestamp synchronization, and transaction ordering. The chapter concludes with detailed examples of smart contract vulnerabilities, including reentrancy, front-running, and oracle manipulation, and highlights the economic and technical incentives that make these attacks feasible in Decentralized Finance ecosystems.
This preprint develops a contract-based framework for evaluating operational claims in open, partially observable, and potentially adaptive systems. Rather than treating safety, service delivery, resilience, or recovery as intrinsic attributes of a system, it represents them as typed, evidence-carrying propositions relative to a declared physical and institutional boundary, environment mechanism, observation history, intervention regime, policy class, shared resources, and finite physical horizon. The framework integrates hybrid path-space models generated by a common modular mechanism; exact physical ledgers that distinguish atomic events from non-atomic finite-variation flows; calibrated observation models and measurement uncertainty; causal identification and transportability; scenario-fixed experiment interfaces; and policy-uniform correspondences between evidence models, computable concrete models, and abstractions. Its principal formal result is a finite-horizon, one-sided deployment certificate that transfers an abstract lower safety value to deployment under partial observation. Statistical coverage over learning datasets, deployment-path probabilities, reconciliation discrepancies, and implementation or abstraction radii are kept as distinct quantities rather than combined into a single confidence score. Claim-sufficient scopes are not assumed to be unique. They are evaluated through a Pareto profile covering completion nonemptiness, query diameter, decision stability, action support, latent sensitivity, and query type. Explicit verdict semantics distinguish accepted claims, contradictions, unsupported refusals, unresolved decision margins, incomparable claims, and invalid records. A machine-readable implementation based on JSON Schema Draft 2020-12 and exact decimal arithmetic checks finite types, relation coverage, physical balance, provenance exclusivity, artifact containment, hashes, and recomputation of certificate quantities. Synthetic examples involving a distributed AI service and human–AI emergency logistics, together with finite counterexamples and reproducible stochastic fixtures, illustrate the framework. The validator does not establish the truth of external evidence, causal assumptions, statistical models, or real-world safety. The work does not propose a universal performance scale, a new causal calculus, or a replacement for formal assurance cases or runtime monitoring.
Open access
2 source records
Adversarial Robustness in Machine Learning
Systems Engineering Methodologies and Applications
Description This preprint presents the Bharat Secure Digital Identity (BSDI) framework, a conceptual policy model for privacy-preserving and citizen-centric digital identity governance. The paper explores how decentralized identity technologies—including Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and Zero-Knowledge Proofs (ZKPs)—may support secure digital verification while minimizing unnecessary disclosure of personal information. BSDI proposes a governance model in which citizens retain primary control over their digital identity through secure digital wallets, the government serves as a trusted root issuer, and digital service providers function as cryptographic verifiers without retaining sensitive identity data. The framework also discusses lawful and targeted access mechanisms for national security within transparent legal oversight. This work is intended as a conceptual research and policy proposal rather than an implemented technical system. It aims to contribute to ongoing discussions on digital identity, privacy, cybersecurity, digital governance, and citizen sovereignty, and to encourage future interdisciplinary research, policy development, and public debate.
Cüneyt Gürcan Akçora, Murat Kantarcioglu, Yulia R. Gel
In this chapter, you will learn about the privacy limitations of public blockchains such as Bitcoin and Ethereum, and how these limitations have led to the development of privacy-focused cryptocurrencies. You will study the motivations for privacy coins and the risks posed by government-issued digital currencies. The chapter introduces and compares three major privacy coins: Zcash, Dash, and Monero. For each, you will explore their underlying technologies, including zero-knowledge proofs (zk-SNARKs), CoinJoin-style mixing, and ring signatures with RingCT and stealth addresses. You will also learn about consensus protocols, supply models, and the trade-offs each project makes between privacy, usability, and scalability. Finally, you will analyze the comparative strengths and weaknesses of these systems and understand the broader implications of privacy on blockchains.
Cüneyt Gürcan Akçora, Murat Kantarcioglu, Yulia R. Gel
This chapter introduces blockchain network structures in both UTXO- and account-based systems. It begins with Bitcoin’s transaction and address graphs, showing how Satoshi Nakamoto’s design defines network topology and enables modeling through transaction graphs, address graphs, and chainlets. Privacy coins like Monero and Zcash extend this framework with ring signatures and zero-knowledge proofs that obscure data but still permit partial inference. Ethereum shifts focus to account-based networks, covering coin and token transactions, contract interactions, and trace analysis. Ripple concludes the chapter with credit networks built on trust lines and path-based settlements, showing how global credit flows can be modeled graphically.