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94,742 results · page 242 of 3,948
Suha Sahib Oleiwi, Lateef Abd Zaid Qudr, Abdul Samad Shibghatullah, Sadiq T. Bunyan · 10 authors
No abstract is available for this record.
Giovanni Scire', gioia arnone, giovanni mistretta
This paper examines how banking compliance frameworks, particularly Italy’s Legislative Decree 231/2001 (MOG 231), are evolving in response to emerging technologies such as artificial intelligence (AI), blockchain, and smart contracts. Originally designed to regulate corporate criminal liability, MOG 231 must now address decentralised financial services, such as crypto wallets and tokenised payments, progressively integrated into traditional banking. This convergence of conventional banking and decentralised finance (DeFi) generates both opportunities and risks, demanding a reassessment of compliance, governance, and value creation models. While cryptocurrencies enable financial inclusion, microfinance, and operational efficiency, they also introduce vulnerabilities related to fraud, anonymity, and misuse by organised crime. These developments challenge legacy compliance systems to manage increasing technological and regulatory complexity. The study employs a conceptual methodology grounded in academic and regulatory literature, drawing on governance, financial regulation, and technology management. To capture the dynamic complexity of compliance adaptation, a system dynamics (SD) approach is used, with causal loop diagrams mapping interactions between compliance structures, technology adoption, performance, and risk exposure. Preliminary findings indicate that integrating AI and blockchain can enhance compliance capacity, regulatory responsiveness, and organisational resilience. However, persistent challenges, such as algorithmic accountability, smart contract enforceability, and integrating decentralised operations into centralised frameworks, suggest MOG 231 requires significant adaptation to effectively govern digitally enabled financial systems.
Miguel Gómez Carpena, Jorge Lanza, Luı́s Sánchez
No abstract is available for this record.
Daniele Battista, Francesco Colace, Simon Pierre Dembele, Muhammad Naeem Khan · 6 authors
No abstract is available for this record.
Baysah Guwor, Rijwan Khan, Mohammad Shabaz
It is evident that blockchain offers strong guarantees of integrity and transparency for handling digital evidence; however, its practical adoption has remained a challenge due to factors such as privacy, deployment constraints, and admissibility issues in the real word environment. This study, therefore, proposes GAS4SEC, a framework for designing, validating, and deploying a secure, cost effective, and forensically sound blockchain-based evidence management system. The system combines formally bound smart contract architecture with role-based access control, record of immutable evidences and custody processes to maintain authenticity, traceability and accountability. In order to overcome the security risks and challenges, the research includes the systematic vulnerability analysis correlated with the OWASP smart contract risks to make sure that unauthorized access, logic abuse, and invalid state transitions are addressed. A validation-based process of development imposes forensic invariants and security guarantees across the lifetime of a contract, and controlled gas optimization is used to achieve better deployment without affecting the evidentiary integrity. The proposed system is deployed and tested on the Polygon Layer-2 blockchain, with functional testing, security testing, gas testing, and stress testing with evidence operations and role change concurrency. The experiment proves that the approach can be used to achieve scalable and cost-effective on-chain forensics operations without sacrificing the high levels of security assistance and forensic integrity and proves to be applicable to the management of digital evidence in practice.
N K Vasilieva, J. D. Darmilova, А.П. ГОРБАТКО, A. N. Kalinichenko
This article examines the concept of cryptocurrency and its specific features. Based on the collection and analysis of information, the paper identifies the dual nature of cryptocurrency, which manifests itself both in the provision of new financial opportunities and in the expansion of corruption and fraudulent schemes. The article explores legal measures and approaches to combating cryptocurrency-related offenses, as well as current methods of detecting corruption involving cryptocurrencies.
K. V. Geetha Devi, K. Supritha
No abstract is available for this record.
Hazlaili Hashim, Md Shukor Masuod, Marcus Kan Hoe Yin, Khairol Nizat Lajis
No abstract is available for this record.
Quanhao Chen
Centralized exchanges (CEXs) dominate cryptocurrency markets due to liquidity and low latency, but their opaque internal ledgers create custodial risk. Meanwhile, privacy concerns motivate private exchanges that blind the platform to user balances and order flow. Recent work such as Pisces [1] explores private and compliable exchanges, but one critical piece in compliance, public verifiable full solvency, remains unresolved. When liabilities are hidden from the platform, the platform cannot construct plaintext-based commitments and cannot be trusted to disclose complete liability sets at audit time, creating a fundamental privacy–solvency conflict. We address this conflict by designing two systems that enforce both solvency and platform-side privacy: * **Audit-then-Check Private and Solvent Exchange System:** Uses an RSA accumulator to provide constant-size membership witnesses; users verify inclusion after the auditor publishes an audit snapshot, and omission yields publicly verifiable evidence. * **Certify-then-Audit Private and Solvent Exchange System:** Eliminates user participation by introducing trusted hardware that certifies each transaction acceptance via a monotonic counter log, enabling the auditor to verify completeness without learning transaction contents. We provide rigorous security analysis that formally establish privacy against a malicious platform and solvency soundness against a malicious user-platform coalition. We implement both schemes and evaluate performance against the state-of-the-art baselines. Our prototype achieves average per-procedure computation under 35 ms, communication bounded by 14 KB per operation. For solvency verification, our online prover time remains nearly constant across user scales, achieving a 41.6× speedup over the state of the art and a 268.6× speedup over deployed baselines at $N = 2^{14}$ users, demonstrating that frequent auditing remains feasible at scale.
Anthony Pachay, Geovanny Brito-Casanova, Ariosto Vicuña, Orlando Erazo · 5 authors
No abstract is available for this record.
Ba Chu, Ilias Tsiakas
No abstract is available for this record.
Michael Neubert, Wolfgang Rams, Patrick Gruhn, Marcel Lötscher
No abstract is available for this record.
Ashley Card, Diego Marmsoler
Smart contracts deployed on the Ethereum blockchain execute on the Ethereum Virtual Machine (EVM) and handle financial operations such as payments, asset transfers, and auctions. Given the high value they control, correctness in these contracts is critical, as errors and vulnerabilities have led to losses totalling hundreds of millions of dollars. To address this problem, we develop a novel formalization of the EVM. Compared to existing formalizations, our formalization is in Isabelle/HOL, covers all current EVM opcodes, and formalizes cross-contract execution. Thus, it allows us to express properties which are out of scope for other formalizations. To allow for the execution of our formalization, we implement a code generator, allowing it to be exported as a stand-alone Haskell program. We then validate the semantics by executing νmprint{25000} test cases from the official Ethereum test suite. Our formalization can be used to verify concrete smart contracts but also to reason about the correctness of tools and techniques which manipulate bytecode, such as compilers or optimizers.
Koresh Galil
No abstract is available for this record.
Oliver Pegani Olsen
Prediction markets have grown from niche research focused platforms into a multi-billion-dollar industry, yet the academic literature on the properties of these new platforms has not caught up. Prediction markets on the touch probability of traded assets are a new form of contract, in which traders bet on whether an asset will reach a specified price level within a given window. They represent a structurally distinct and largely unexamined category. Because these contracts reference a continuously traded underlying with a deep options market, the probability they quote may already be embedded in existing market data. This thesis asks if Polymarket Bitcoin price-target contracts contribute to price discovery, or whether they merely repackage the touch probability already implied by the Bitcoin spot and options markets. The analysis uses 258 monthly barrier contracts traded between October 2024 and March 2026 and proceeds in three stages: a Mincer-Zarnowitz calibration regression, per-contract Granger causality tests at the hourly frequency, and a cross-sectional comparison of Polymarket prices against a closed-form one-touch barrier probability evaluated under both implied and realised volatility. The calibration test cannot reject Polymarket prices are unbiased probability forecasts of their resolution outcomes. The Granger causality tests reveal that Polymarket no detectable predictive content for next-hour Bitcoin returns. A closed-form barrier probability computed from the spot price, strike, time to maturity, and a volatility estimate explains over 95% of the cross-sectional variation in Polymarket prices under both implied and realised volatility, though the joint null of exact equality is rejected. The price tracks the realised-volatility benchmark and sits below the implied-volatility one, so the level departure is consistent the variance risk premium embedded in options rather than independent information about Bitcoin. The three results replicate out of sample on 252 Ethereum contracts. Taken together, the findings suggest that financial-asset prediction markets contribute little information beyond what is already priced in the underlying spot and options markets.
David Krause
No abstract is available for this record.
David Krause
No abstract is available for this record.
Craig S Wright
No abstract is available for this record.
Aurélien Perez
No abstract is available for this record.
Muhammad Noraiz Abid
No abstract is available for this record.
Vikram Dham
No abstract is available for this record.
Nemanja Zdravković
The widespread adoption of Learning Management Systems (LMSs) as mission-critical digital infrastructures in higher education has introduced significant security and trust challenges. While centralized LMS architectures provide operational efficiency, they remain structurally vulnerable to insider threats, silent database compromise, mutable audit logs, and credential forgery. Existing blockchain-based research in education has largely focused on certificate authentication and transcript portability, leaving internal LMS integrity and enterprise-grade threat mitigation insufficiently addressed. This paper proposes a blockchain-enabled audit extension architecture for LMS environments, designed to enhance assessment integrity, traceability, and institutional trust without replacing existing platforms. Building upon a formal threat model tailored to LMS infrastructures, we derive security requirements including immutability, non-repudiation, auditability, confidentiality, and trust separation. To satisfy these requirements, we introduce a permissioned distributed ledger layer based on Hyperledger Fabric, operating alongside the institutional Information System. The architecture employs event-based transaction modeling, identity-bound cryptographic signatures, distributed endorsement policies, and minimal on-chain storage through hash anchoring of sensitive data. A proof-of-concept implementation within a controlled institutional test network demonstrates the feasibility of recording grade submission and modification events as append-only ledger transactions. The prototype validates distributed validation, identity attribution via Certification Authority infrastructure, and tamper-evident audit logging using a Raftbased ordering service and CouchDB world state management. The results indicate that integrating a permissioned blockchain layer can significantly strengthen enterprise security posture by mitigating structural weaknesses inherent in centralized LMS systems. Although the current deployment remains limited in scale, the proposed model establishes a scalable foundation for secure, verifiable digital education infrastructures and future large-scale institutional integration.
Maxat Kassen
No abstract is available for this record.
Michael Fiolka, Tobias Jornitz, Luisa Strehl
Since the emergence of the blockchain and the uprising of ChatGPT, the Distributed Ledger Technology (DLT) and Artificial Intelligence (AI) are well-discussed topics both in public and professional circles, but especially in the domain of Supply Chain Management (SCM). These subjects are tech-savvy, complicated to explain and even more complex to use. On top of that, there is a scientific discussion around synergies in combining both technologies. Together they can be useful in engaging current challenges in SCM, where transparency-related data has to be generated, processed and formed into decisions and reports. To investigate the potentials of these technologies working together in a non-financial reporting environment, we performed a systematic literature review. We also included literature focusing solely on the technological perspective. The objective is a comprehensive overview on how a combination of DLT and AI could help to solve current challenges arising from sustainability related regulations. Further, we discussed ideas around Internet of Things applications or Federated Learning approaches, that use data from different entities and can be used in sustainability reporting, exploring possibilities to enhance compliance and responsible business conduct in SCM.