Sinchana Shetty, Tejaswini M R, Kiran Samantha D S, Vijaylaxmi H Manjunatha
Existing electronic voting platforms are persistently centralized repositories, introducing fundamental security challenged by vote manipulation, result falsification, limited weaknesses [1]. Blockchain technology has emerged as a compelling alternative, owing to its cryptographic permanence, data management. This paper proposes and evaluates a fully integrated blockchain-based electoral system built on the Ethereum network, leveraging Solidity smart contracts to address these systemic shortcomings. The proposed architecture adopts a decentralized three-tier design incorporating Web3.js communication bridges and cryptographic validation mechanisms that collectively guarantee immutability, transparency, and end-to-end verifiability throughout all electoral phases. The system incorporates hierarchical role-based access controls, real-time vote tallying, and comprehensive audit trail functionality, while preserving voter anonymity through pseudonymous addressing. Experimental results demonstrate transaction confirmation within 15–20 seconds, with a mean gas consumption of 0.0023 ETH per vote, confirming practical feasibility for medium-scale deployments. A comparative evaluation against conventional centralized e-voting solutions highlights measurable security full-stack Ethereum-based voting platform comprising Solidity improvements and the elimination of single points of failure, balanced against acceptable computational overhead.
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Biometric Identification and Security
Advanced Steganography and Watermarking Techniques
Part II, 'How Decentralised Security is Organised,’ examines the actors, infrastructures, and incentives that shape security practices in Web3—from the structural insecurity of digital infrastructure to the emergent role of white hat hackers and collaborative security initiatives they coordinate. This chapter introduces a new protagonist in the security landscape: the blockchain white hat hacker. Far from operating in the shadows, this actors play a vital role in the moral, political, and economic landscape of blockchains by helping to safeguard decentralised systems. This chapter examines the practices, motivations and incentives—both financial, moral, and reputational—that drive white hat activity, highlighting how these individuals contribute to vulnerability disclosure, incident response and the overall resilience of the blockchain ecosystem. In doing so, it situates white hats not as central figures in the evolving ecosystem of decentralised security governance.
Alexandre Pires Barbosa, Douglas Wegner, Rodrigo Pereira dos Santos
Research Context: Decentralized Autonomous Organizations (DAO) emerge as innovative structures operating on blockchain infrastructures, providing transparency, decentralization, and autonomy in digital governance and coordination processes. Scientific and/or Practical Problem: Despite their transformative potential, DAO face significant obstacles, such as scalability limitations, risks of power concentration, legal ambiguities, and complex incentive models. Proposed Solution and/or Analysis: This study investigates recent scientific literature on DAO, seeking to understand their current state, focusing on how they have been conceptualized, characterized, evaluated, and applied. Related IS Theory: The research draws on the wisdom of crowd theory, which explains how collective decision-making can overcome individual choices, and sociotechnical theory, which emphasizes the interaction between technological infrastructures and social structures. Together, these perspectives frame DAO as hybrid systems that integrate algorithmic processes with collective human governance. Research Method: A systematic mapping study was conducted, encompassing the collection, selection, and coding of 47 primary studies published in relevant scientific sources. Summary of Results: The results highlight the conceptual consensus on the decentralized and smart contract-based nature of DAO, propose categories of structural challenges, and map recurring application domains, such as decentralized finance (DeFi), open science, energy, and digital art. Furthermore, the results demonstrate the transition of DAO from algorithmic entities to sociotechnical hybrids, connected to emerging trends such as the metaverse, NFTs, and decentralized artificial intelligence. Contributions and Impact to IS area: This study provides an updated theoretical foundation for the IS area, mapping the state of the art of DAO, identifying structural challenges, and emphasizing their evolution toward hybrid models. Most importantly, it reveals the complexity and originality of uniting the three main pillars of information systems (code, governance, and automated processes), thus contributing to the design of more resilient, inclusive, and sustainable digital governance systems in emerging decentralized ecosystems.
SILMARILS is built from a minimal algebraic core over $\mathbb{F}_p$ using true randomness and perfect $2$-out-of-$2$ Shamir secret sharing. The framework supports both two-party and three-party modes. In the two-party setting, SILMARILS realizes a transferable designated-verifier (TDV) signature scheme. The designated verifier can simulate accepting transcripts indistinguishable from real ones, achieving Jakobsson-Sako-Impagliazzo DV security. The verifier may publish a receipt $r$ enabling public verification, yet even with $r$, no external party can tell whether a transcript was signed or simulated. As DV signatures permit simulation, standard EUF-CMA cannot hold for the designated verifier; instead, we prove $\mathsf{EUF\text{-}CMA}^{\neg\mathsf{DV}}$ security for all non-designated verifiers in both the random oracle model (ROM) and quantum random oracle model (QROM). In the three-party mode, adopting the broadcast model of Fitzi et al., we obtain a statistically secure signature protocol with simulation-based security and error $1/p$. We analyze security in the Pure IT model, the IT+ROM, and the QROM, extending the Fitzi et al. framework to quantum adversaries with classical I/O. Correctness, secrecy, transferability, and unforgeability for non-designated parties remain equivalent to simulation-based security. Thanks to its simple algebraic structure, SILMARILS offers very compact keys and signatures for the blockchain settings we target, where standardized PQC schemes are already more than sufficient. Our goal is not to compare SILMARILS with PQC, but to highlight its suitability for lightweight TDV authentication. A fair comparison with other DV schemes is omitted due to space and the complexity of aligning models.
This paper presents InsureConnect, a blockchain-based system for improving transparency, authentication, and auditability in property-insurance workflows after natural disasters. The system combines Self-Sovereign Identity (SSI), Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), satellite imagery, Hyperledger Fabric, and IPFS to register identities, insurance contracts, and damage claims. Property images are stored off-chain in IPFS, while content hashes and signed records are maintained on a permissioned blockchain. Users interact with the system through a desktop application, while chaincode enforces role-based access control and validates digital signatures. The prototype was evaluated under concurrent request loads from 50 to 3000 requests, measuring latency, throughput, and dropped connections. The results indicate that the system sustains increasing throughput under load, although latency rises and dropped connections appear at higher concurrency levels.
Strategic competitions in the real world, from wars to geopolitical rivalries, often involve coalitions competing against rival groups. These contests are not simple interactions between unified entities, but multilayered processes in which coalitions face external competition while dealing with internal conflicts over resources and strategy. Existing game-theoretic models typically treat inter-coalition rivalry and intra-coalition competition separately. This paper introduces the Compound Coalition-Attrition Game (CCAG), a unified framework that integrates a war of attrition between coalitions with a simultaneous war of attrition within each coalition. In this model, the endurance of a coalition in external competition is determined by the strategic choices of its members, who compete internally for shares of the outcome. We prove the nonexistence of pure-strategy equilibria and characterize the unique mixed-strategy Nash equilibrium. The analysis reveals feedback effects: external competition intensifies internal conflict, while internal discord weakens external performance. A case study compares traditional commodity markets, including gold, copper, and silver, with cryptocurrency markets, including Bitcoin, Ethereum, and Solana, using data from 2018 to 2023 in a simulation framework. The results demonstrate applicability in industrial strategy, corporate decision-making, and geopolitical competition. The CCAG framework provides a tool for analysing complex strategic environments.
Elections may be expedited, simplified, and enhanced through electronic voting. They are not frequently employed as a result of security, transparency, scalability, and voter confidentiality concerns. Our blockchain-based electronic voting system is impermeable, visible, and privacy-protective due to the use of advanced cryptographic algorithms and a permissioned distributed ledger. A permissioned blockchain that employs an expedited consensus method enhances throughput and minimizes latency during critical elections. Voter registration, voting, and tabulation are automated through the use of smart contracts. This mitigates centralization and manipulation. Privacy is safeguarded through encryption, decentralized identity (DID) frameworks, and verified methods. Comprehensive verification is facilitated by the protection of voter anonymity. In a hybrid architecture, scalability is enhanced and computational power is reduced through off-chain storage and on-chain validation. The proposed system is capable of withstanding unauthorized access, data manipulation, and duplicate voting, as evidenced by a comprehensive security and performance analysis. Furthermore, it surpasses voting systems that are founded on blockchain technology. The findings indicate that the secure digital election technology is both scalable and viable, thereby facilitating the implementation of transparent and dependable voting systems.
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A model artifact can be verified on disk without establishing which model is computing at runtime. Trustfall Lite is an open-source command-line tool (Apache-2.0) that scans local Hugging Face and Ollama model caches, computes the SHA-256 of each artifact, and verifies the hash against a signed registry whose records are JWS-signed and verified against a published JWKS. Every artifact resolves to one of four statuses: verified, unknown_variant, not_enrolled, or pilot_available. The tool runs locally; model bytes are not transmitted, and file paths and filenames are not sent to the verification API. By default, artifact hashes may be queried against the Fall Risk API; --local-only verifies against a cached registry without network lookup. This note describes what artifact-level verification establishes, where it stops, and how it relates to the runtime structural identity measurement developed across the Fall Risk Research program. Artifact verification is necessary but not sufficient: the same SHA-256 can serve different runtimes, models can be loaded over the network without touching disk, and disk-time identity does not guarantee runtime identity. The boundary between these two evidence classes — file-level and runtime — is the subject of this note. The Neural Network Identity Series — Mathematical foundations, empirical validation, and governance frameworks for verifying which model is running Newest addition: Technical Note: The Disappearing Window — AI Logprob Access Withdrawal and the Structural Verifiability of Frontier Model Contracts (DOI: 10.5281/zenodo.20362098) Paper 1: The δ-Gene: Inference-Time Physical Unclonable Functions from Architecture-Invariant Output Geometry (DOI: 10.5281/zenodo.18704275) Paper 2: Template-Based Endpoint Verification via Logprob Order-Statistic Geometry (DOI: 10.5281/zenodo.18776711) Paper 3: The Geometry of Model Theft: Distillation Forensics, Adversarial Erasure, and the Illusion of Spoofing (DOI: 10.5281/zenodo.18818608) Paper 4: Provenance Generalization and Verification Scaling for Neural Network Forensics (DOI: 10.5281/zenodo.18872071) Paper 5: Beneath the Character: The Structural Identity of Neural Networks — Mathematical Evidence for a Non-Narrative Layer of AI Identity (DOI: 10.5281/zenodo.18907292) Paper 6: Which Model Is Running?: Structural Identity as a Prerequisite for Trustworthy Zero-Knowledge Machine Learning (DOI: 10.5281/zenodo.19008116) Paper 7: The Deformation Laws of Neural Identity (DOI: 10.5281/zenodo.19055966) Paper 8: What Counts as Proof? — Admissible Evidence for Neural Network Identity Claims (DOI: 10.5281/zenodo.19058540) Paper 9: Composable Model Identity — Formal Hardening of Structural Attestations in the Enterprise Identity Stack (DOI: 10.5281/zenodo.19099911) Paper 10:Where Identity Comes From: Path Sensitivity and Endpoint Underdetermination in Neural Network Training (DOI: 10.5281/zenodo.19118807) Paper 11: Post-Hoc Disclosure Is Not Runtime Proof: Model Identity at Frontier Scale (DOI: 10.5281/zenodo.19216634) Paper 12: Family-Dependent Response to Reasoning Distillation Across Structural and Functional Identity Layers (DOI: 10.5281/zenodo.19298857) Paper 13: Safety-Alignment Removal as a Model-Identity Failure — Structural Evidence from Published Weight-Level Mutation Checkpoints (DOI: 10.5281/zenodo.19383019) Technical Note: Agent Identity Is Not Model Identity (DOI: 10.5281/zenodo.19240883) Technical Note: Gap Invariance: Why PPP Measurements Are Domain-Independent by Construction (DOI: 10.5281/zenodo.19275524) Technical Note: Measured Model Substitution Under Valid Agent Credentials (DOI: 10.5281/zenodo.19342848) Technical Note: Artifact Identity Is Not Runtime Identity — Trustfall Lite and the Boundary of File-Level Model Verification (DOI: 10.5281/zenodo.20019127) Formal Verification Stack for Neural Network Structural Identity (IT-PUF Coq Proofs) (DOI: 10.5281/zenodo.18930621) Copyright (c) 2026 Anthony Ray Coslett / Fall Risk AI, LLC. All Rights Reserved. Confidential and Proprietary. Patent Pending (Applications 63/982,893, 63/990,487, 63/996,680, 64/003,244).
Financial software sits at the center of modern economic infrastructure, yet the programming languages used to build it provide no formal guarantees about the semantic correctness of financial operations. Double-entry bookkeeping’s duality constraint, the rule that every economic event must produce balanced inflows and outflows, is universally encoded at the application layer, where it can be omitted, miscoded, or deliberately bypassed. No existing compiled programming language includes a type rule for accounting duality. This paper presents Equis, a compiled, self-hosting systems language that elevates the Resource–Event–Agent (REA) model to first-class syntactic constructs and enforces accounting duality as a static, compile-time invariant. The compiler rejects any event declaration whose flow block is not balanced before emitting a single instruction of LLVM IR. Equis uses fixed-point 64-bit integer arithmetic scaled by 106 throughout, eliminating IEEE 754 accumulation error from financial code paths entirely. Memory management relies on automatic reference counting with a resource-state borrow checker, giving deterministic, GC-pause-free behavior in long-running settlement services. The compiler is self-hosted, bootstrapped from ANSI C, and verified via Diverse Double Compilation to address Thompson’s trusting-trust problem. Contributions include the formal duality typing rule and its soundness proof, the full REA primitive syntax integrated into a systems language, role-based access control enforced statically at the agent-type level, an append-only ledger primitive with compensating-transaction semantics, and a 20-module standard library covering collections, ledger management, accounting, compliance, database access, HTTP, channels, and fibers. Equis is, to the author’s knowledge, the first compiled general-purpose language to embed REA semantics in its type system. Compile-time duality enforcement eliminates an entire class of financial logic errors with zero runtime overhead.
Yongming Zhang, Chaoyue Li, Lei Liu, Yangjun Sun · 5 authors
Cooperative V2X is evolving toward city-scale deployment, yet current infrastructures still lack a network substrate that jointly provides cross-domain trust, low-latency finality, and privacy-preserving, auditable evidence for safety-critical decisions. This paper proposes a federated-trust sharded blockchain that turns heterogeneous vehicular and roadside measurements into accountable records and enables real-time forensic collaboration and secure data sharing across operators and city management authorities. A federated trust oracle fuses GNSS, OBD, IMU, RSU observations, and device attestations into uncertainty-aware scores that steer committee election, voting weights, and traffic shaping in each shard. On this basis, we design a hybrid cross-shard commit protocol with adaptive finality, combining atomic channels for forensic-critical transactions and optimistic channels for routine collaboration, and we establish safety/liveness conditions and provide proof sketches under the stated partial-synchrony assumptions and bounded collusion. For the forensic layer, a two-stage pipeline anchors minimal sufficient evidence with sub-second local finality, while editable proofs built on traffic-aware extended Merkle trees and zero-knowledge attestations support publicly verifiable, legally compliant edits with \(O(\log n)\) verification overhead. An SLA-aware, learning-assisted scheduler adapts committee size, batching, and cross-shard parallelism to dynamic traffic and attack patterns so as to meet latency, throughput, and rollback targets. Large-topology containerized emulation on a dedicated workstation, complemented by a small hardware-in-the-loop testbed, shows that the proposed framework achieves sub-second forensic anchoring and 95th-percentile cross-shard finality below \(1.2\) s. Across the representative baselines used in this study, it improves effective throughput by up to \(35\%\) ; in particular, at comparable \(L_{p95}\) , it achieves \(1.6\) – \(2.3\times \) higher TPS than the single-chain HotStuff baseline under the tested emulation conditions, while reducing rollback rate and per-event bandwidth by up to \(40\%\) and \(25\%\) , respectively. These results indicate that the proposed system can shorten incident response, strengthen accountability in crash investigations and recalls, and provide a practical foundation for privacy-preserving, transparent data collaboration between mobility operators and urban management departments.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Preliminary results: Gemini — 6.3% hallucination rate (Baseline 57.5%). ChatGPT — 0.0% (Baseline 22.2%). Claude — 0.0% on both. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. COMP (the compression mandate) is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional.
The development of financial technology has led to the emergence of cryptocurrency as a decentralized digital instrument that enables fast and cross-border financial transactions. While this technology offers efficiency and flexibility in digital financial activities, it also creates opportunities for misuse in various forms of crime, including terrorist financing. This study aims to analyze the use of cryptocurrency as a means of financing terrorist activities in Indonesia, examine the existing legal framework governing terrorist financing, and identify the challenges faced in law enforcement. This research employs a normative legal method using statutory, conceptual, and case study approaches. The findings indicate that the use of cryptocurrency as a medium for terrorist financing still fulfills the elements of a criminal offense as regulated under Law Number 9 of 2013 concerning the Prevention and Eradication of Terrorism Financing. However, the characteristics of cryptocurrency, such as anonymity, decentralization, and cross-border transactions, create significant challenges in the processes of evidence gathering, transaction tracing, and identification of perpetrators. In addition, there is a regulatory gap between the recognition of crypto assets as economic commodities and the supervision of their potential misuse for terrorist financing. Therefore, stronger regulations are needed to explicitly integrate crypto assets into the terrorist financing prevention regime, along with improving the capacity of law enforcement agencies in blockchain transaction analysis and strengthening international cooperation to enhance the effectiveness of law enforcement in the digital economy era.
The intricate and unpredictable nature of cryptocurrency markets has brought Bitcoin price prediction into the spotlight because of the relatively high volatility levels of cryptocurrencies. Conventional centralized machine learning solutions pose challenges on the issue of data privacy, security, and scalability, especially with financial applications. To respond to these issues, this paper outlines an overall execution of a federated learning system to predict Bitcoin prices. K-Nearest Neighbours, Decision Tree, Linear Regression, and Federated Long Short-Term Memory (FL-LSTM) model are federated, trained, and tested on past Bitcoin market data. Within the proposed framework, the process of model training is executed at each of several clients locally, and only model parameters or predictions are transmitted without data privacy. Experimental data reveal that classical federated machine learning models have poor performance in modelling complex price dynamics. Although Federated Linear Regression reflects similar goodness of-fit, the FL-LSTM proposed model is always associated with the lower prediction error and is highly close to the real price movements. Also, the FL-LSTM model is used to predict the short-term future, which proves that this model can be useful to anticipate future fluctuations in Bitcoin prices. The results affirm that federated learning, which has been combined with deep learning models, is a viable and privacypreserving solution in cryptocurrency prediction in a decentralized setting. Root Mean Square Error (RMSE) and$\mathbf{R}^{\mathbf{2}}$were used to measure the proposed models. The results of the experiment show that the FL-LSTM model possesses the lowest prediction error, and it is much closer to real Bitcoin price trends than the other federated models.
Blockchain smart contracts automate agreements, replacing third-party intermediaries with immutable and enforceable algorithms. Despite their potential, the complexity of blockchain often undermines human trust and their wide adoption. To address this challenge, we systematise existing knowledge on three critical human-centric qualities: transparency, accountability and understandability. Although these qualities are frequently invoked as pillars of trust in decentralised systems, they remain ambiguously defined and inconsistently operationalised across the literature and platforms. To establish a clearer and more coherent understanding of these qualities in the context of public blockchains and smart contracts, we introduce a structured model that organises existing knowledge into five levels: output, algorithm, external data, process, and application, acquiring insights from literature. This structured approach provides a comprehensive understanding by revealing gaps and areas of consensus, aiding researchers in identifying areas requiring further investigation. To address unclear or conflicting interpretations, we incorporated insights from experienced blockchain developers. We also conduct a comparative analysis to examine whether the characteristics of public blockchains align with standard definitions of transparency, accountability, and understandability. Our findings show that smart contracts support visibility and traceability at low system levels but lack clarity, answerability, and ease of understanding at higher organisational and user interaction levels. These gaps highlight the need for improved communication practices, clearer governance disclosure, and more human-centred design approaches.
The integration of Internet of Things (IoT) technologies into precision agriculture has transformed farming practices through real-time monitoring, automated irrigation, and data-driven decision-making. However, centralized access control mechanisms remain vulnerable to single points of failure, scalability issues, and security breaches such as spoofing and replay attacks. To address these challenges, this paper proposes a decentralized blockchain-based framework for access management in agricultural IoT environments. The architecture integrates IoT devices, edge gateways, smart contracts, and a distributed ledger to provide secure identity management, automated authorization, and immutable audit trails. Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) are combined to enable context-aware authorization, while Zero-Knowledge Proofs (ZKPs), Multi-Factor Authentication (MFA), and end-to-end encryption strengthen resilience against identity theft and unauthorized access. Performance evaluation demonstrates a$\mathbf{6 5 \%}$reduction in authentication latency and an access control accuracy of 98.5 %, confirming the framework's scalability and security effectiveness for large-scale precision agriculture deployments.
Abstract – The rapid proliferation of blockchain-based decentralized applications has introduced critical security challenges ranging from vulnerable smart contracts to privacy leakage in on-chain transactions. Existing tools address these challenges in isolation, leaving practitioners to integrate disparate solutions. OmniShield is a unified, open-source blockchain security platform that consolidates AI-powered smart contract vulnerability scanning, zero-knowledge proof (ZKP) private transfers, and a private QBFT consensus network into a single cohesive system. The scanner combines static pattern analysis, symbolic execution, and a Gemini-LLM reasoning layer to detect reentrancy, integer overflow, access-control flaws, and twelve other vulnerability classes with severity ratings. Private transfers leverage Groth16 zk-SNARKs over Circom circuits so balances remain hidden on-chain while cryptographic validity is enforced. The underlying network runs on Hyperledger Besu with QBFT consensus, providing Byzantine-fault-toleran block production. Experimental results show the scanner correctly identifies known vulnerabilities in benchmark contracts, ZKP proof generation completes in under 15 seconds on consumer hardware, and end-to-end private transfers finalize within two consensus rounds. OmniShield demonstrates that enterprise-grade blockchain security can be packaged as an accessible, developer-friendly platform. Key Words: blockchain security, smart contract analysis, zero-knowledge proofs, zk-SNARKs, Hyperledger Besu, QBFT consensus, AI vulnerability scanner, reentrancy, Solidity.
This paper demonstrates practical arbitrage trading on the cryptocurrency market. It provides guidance on how to build a high-frequency trading system that benefits from exhibiting arbitrage opportunities. It reveals the algorithm of the trading bot that incorporates the order placement and execution strategy between decentral and central cryptocurrency exchanges. The arbitrage algorithm is implemented on two different blockchains that interact with Uniswap and Balancer folks. Current research explores arbitrage opportunities with back-testing models, the paper focuses on trades with realized arbitrage trades. Practical arbitrage includes all operational costs, liquidity constraints, direct effects on markets, and competition with peer arbitrage traders.
Orfeas Anastasios Koidis, Francesco Giumelli, Oskar Josef Gstrein
Purpose There is a growing debate about the use of cryptocurrencies to evade sanctions. This paper aims to systematically collect and organize the available literature on cryptocurrencies and sanctions evasion. The aim is to map the debate, identify gaps and clarify the implications for global governance and the international order. Design/methodology/approach This research conducted a systematic literature review using a keyword-string search method across relevant databases. Due to limited peer-reviewed literature, additional “grey” literature was included to broaden the evidence base. Findings The mapping reveals a fragmented debate over a strong link between cryptocurrencies and sanctions evasion grounded in cryptocurrencies’ design features. It identifies three main gaps concerning the scale of this form of evasion, the mechanisms through which it operates, and whether it represents a novel challenge or a reconfiguration of established practices under new technical infrastructure. Further research on these issues would contribute to an enhanced understanding of sovereignty, global governance and power. Originality/value While much of the literature on cryptocurrencies and illicit finance has centred on money laundering, their role in sanctions evasion remains underexplored. To the best of the authors’ knowledge, this paper provides the first systematic consolidation of the dispersed academic and policy literature on the topic. It brings together peer-reviewed research and verified grey literature into a consolidated evidence base that can serve as a stepping stone for future debates and research on cryptocurrency-enabled sanctions evasion.
Anonymous digital credentials allow a user to prove possession of an attribute that has been asserted by an identity issuer without the user revealing any extra information about themselves. For example, a user who has received a digital passport credential can prove their “age is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>></mml:mo> <mml:mn>18</mml:mn> </mml:mrow> </mml:math> ” without revealing any other attributes such as their name or date of birth. Despite their clear application to privacy-preserving authentication, anonymous credential schemes have been difficult to deploy at scale. Part of the difficulty arises because schemes in the literature, such as BBS+, use new cryptographic primitives that require system-wide changes to existing issuer infrastructure. In addition, issuers often require digital identity credentials to be device-bound by incorporating the device’s secure element into the presentation flow. As a result, schemes like BBS+ require updates to the hardware on every user's device. We propose new ZK techniques which enable the construction of an anonymous credential scheme for the legacy Elliptic Curve Digital Signature Algorithm (ECDSA) signature scheme. By adding efficient ZK arguments for statements about SHA-256 and document parsing for ISO-standardized identity formats, we construct the first ZK proof of posession of a credential that can be deployed without changing any issuer processes, without changes to mobile devices, and without requiring non-standard cryptographic assumptions. Furthermore, our proof system itself only relies on SHA-256 as its complexity assumption. Producing ZK proofs about ECDSA signatures has been a bottleneck for other ZK proof systems because standardized curves such as P256 use finite fields which do not support efficient number theoretic transforms. We overcome this bottleneck by designing a ZK proof system around sumcheck and the Ligero argument system, by designing efficient methods for Reed-Solomon encoding over the required fields, and by designing specialized circuits for ECDSA. Our proofs for ECDSA can be generated in as little as <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>≈</mml:mo> <mml:mn>20</mml:mn> </mml:mrow> </mml:math> ms. When incorporated into a fully standardized identity protocol such as the ISO MDOC standard, our system can generate a zero-knowledge proof for the MDOC presentation flow in a few hundred ms on mobile devices. These advantages make our scheme a promising candidate for privacy-preserving digital identity applications.
Penelitian ini bertujuan mengimplementasikan smart contract Ethereum dengan pendekatan hybrid untuk memperkuat verifikasi dokumen dan transparansi pada sistem crowdfunding beasiswa. Permasalahan utama yang diangkat adalah rendahnya kepercayaan publik terhadap platform donasi pendidikan ketika dokumen persyaratan, status verifikasi, dan realisasi penggunaan dana hanya dikelola melalui basis data terpusat. Metode yang digunakan adalah penelitian pengembangan perangkat lunak dengan model prototype yang mencakup komunikasi kebutuhan, perencanaan cepat, pemodelan desain, konstruksi prototipe, serta penyerahan dan evaluasi umpan balik. Sistem dibangun menggunakan Next.js, SQLite, Prisma ORM, Solidity, Ethers.js, MetaMask, dan jaringan Ethereum Sepolia Testnet. Hasil penyusunan sistem menunjukkan bahwa arsitektur hybrid mampu memisahkan penyimpanan dokumen fisik secara off-chain dari pencatatan bukti integritas secara on-chain. Smart contract ScholarshipRegistry dirancang untuk mencatat hash dokumen, status verifikasi, alamat wallet verifikator, timestamp, dan log nominal donasi tanpa menggunakan mata uang kripto sebagai alat pembayaran. Fitur audit publik memungkinkan donatur dan masyarakat mencocokkan hash dokumen, memantau bukti pencairan dana, serta melaporkan indikasi kejanggalan. Secara kritis, blockchain meningkatkan integritas rekam jejak, tetapi tidak otomatis menjamin kebenaran substantif isi dokumen; karena itu validasi administratif, kontrol akses, dan mekanisme pelaporan publik tetap diperlukan. Penelitian ini berkontribusi pada model crowdfunding beasiswa yang lebih transparan, efisien, dan dapat diaudit. This study aims to implement an Ethereum smart contract using a hybrid approach to strengthen document verification and transparency in a scholarship crowdfunding system. The main problem addressed is the limited public trust in digital education donation platforms when eligibility documents, verification status, and fund realization records are controlled only through a centralized database. The study applied a software development method based on the prototype model, consisting of communication, quick planning, quick design modeling, prototype construction, and delivery with feedback evaluation. The prototype was developed using Next.js, SQLite, Prisma ORM, Solidity, Ethers.js, MetaMask, and the Ethereum Sepolia Testnet. The resulting design demonstrates that the hybrid architecture can separate physical document storage in an off-chain layer from integrity proof recording in an on-chain layer. The ScholarshipRegistry smart contract records document hashes, verification status, verifier wallet addresses, timestamps, and donation amount logs without using cryptocurrency as the payment instrument. The public audit feature enables donors and the public to compare document hashes, monitor disbursement evidence, and submit reports on suspected irregularities. Critically, blockchain improves the integrity of audit trails, but it does not automatically verify the substantive truth of uploaded documents; therefore, administrative validation, role-based access control, and participatory reporting remain necessary. This study contributes a transparent, cost-efficient, and auditable model for scholarship crowdfunding systems.