Smart contract vulnerabilities are predominantly logic bugs whose detection requires structured, step-by-step procedural knowledge of attack patterns and contract semantics. Existing LLM-based methods struggle to generate this knowledge automatically: prompt-based methods rely on manually crafted detection rules, while fine-tuning requires massive labeled datasets that are inherently scarce in this domain. We present EvoVuln, an automated framework that reformulates vulnerability detection as a procedural knowledge evolution problem, synthesizing and refining detection logic using only a minimal number of labeled samples. To achieve this, EvoVuln introduces two key mechanisms. First, a Runtime with an Inversion of Control (IoC) architecture compiles detection rules into Executable Policies. This strictly decouples deterministic control flow from LLM semantic reasoning, ensuring faithful logical adherence and producing dense diagnostic telemetry for precise error localization. Second, a two-phase evolution pipeline refines the rule via abductive semantic debugging without any parameter updates: Cold Start bootstraps and stress-tests an initial rule using auto-synthesized corner cases; Few-Shot Evolving then grounds the policy in real-world semantics using only five vulnerable and five safe examples per vulnerability type. Evaluated across five real-world vulnerability types, EvoVuln achieves a 71% macro-average F1-score, outperforming all baselines. The evolved procedural knowledge is portable across models: it enables a lightweight, low-cost model to surpass a much larger zero-shot model by 19 percentage points, and transfers to other LLMs without retraining, at a one-time evolution cost under $50.
Our study examines the impact of climate policy uncertainty on the volatility of Bitcoin, Ethereum and Litecoin. Using monthly Climate Policy Uncertainty Index data from 2010 to 2024, we forecast daily cryptocurrency volatility with a GARCH-MIDAS model. The results show that higher climate policy uncertainty significantly increases volatility across all three cryptocurrencies over the full sample period. Out-of-sample analysis, which captures structural changes in energy consumption, reveals stronger effects for Bitcoin. Ethereum shows insignificant responses following its transition to a proof-of-stake mechanism, while Litecoin exhibits a significant positive relationship with uncertainty. Overall, climate policy uncertainty proves to be a strong predictor of cryptocurrency volatility, particularly for energy-intensive assets. The findings highlight the importance of policy-related information in shaping investor behaviour in crypto markets and provide useful implications for cryptocurrency issuers, retail investors and portfolio managers seeking to manage risk under changing regulatory and environmental conditions.
Zero-knowledge proofs (ZKPs) are emerging as a core technology for privacy-preserving computation. Despite steady progress in protocol and algorithm design, generating these proofs remains computationally intensive, driving growing interest in hardware acceleration for kernels such as number-theoretic transform (NTT) and multi-scalar multiplication (MSM). Among them, the sumcheck protocol offers a compelling alternative with O(n) prover complexity compared to O(nlog n) for NTT-based approaches, yet our analysis reveals its execution is fundamentally memory-bound, with severely underutilized compute resources. This characteristic demands a memory-centric acceleration strategy, in contrast to compute-centric approaches of prior work.
Zero-Knowledge Proof (ZKP) is a cornerstone in privacy-preserving computing, addressing critical challenges in domains such as finance and healthcare by ensuring data confidentiality during computation. However, the high computational overhead of ZKP, particularly in proof generation and verification, limits its scalability and usability in real-world applications. Existing efforts to accelerate ZKP primarily focus on specific components, such as polynomial commitment schemes or elliptic curve operations, but fail to deliver an integrated, flexible, and efficient end-to-end solution that includes witness generation on commercial computing platforms.
ASEGUNLOLUWA E. BABALOLA, DAVID O. ILESANMI, PREYE ADEOLA
Electronic voting can improve the speed of ballot processing and result generation, but conventional systems often depend on centrally controlled infrastructure that may create concerns relating to record alteration, transparency and administrative control. This study presents the development of a blockchain based electronic voting prototype that integrates election creation, candidate management, voter address authorization, ballot submission and result retrieval within a web application. The system adopts an Ethereum based architecture comprising a Next.js user interface, Web3 communication, MetaMask wallet connection, Solidity smart contracts and a local blockchain environment provided by Ganache. A factory smart contract is used to create separate election contracts, enabling each election to maintain its own candidates, authorized voter addresses, election status and vote totals. Before a ballot is accepted, the relevant election contract verifies that the election is active, that the submitting address is authorized and that the address has not previously voted. The developed prototype provides interfaces for election creation, voting and result presentation, demonstrating the integration of the web application with the smart contract and blockchain components. The study provides a basis for the independent management of multiple elections through separate smart contract instances.
Decentralized social protocols such as Nostr introduce a new paradigm for user-generated content (UGC) in the Web3 era, where content production, dissemination, and reward mechanisms operate without centralized governance. This paper presents one of the first large-scale empirical analyses of Nostr, based on 22.3 million user events collected from four major publicly accessible relays. Guided by three research questions, we examine (1) the temporal and spatial distribution of user participation, (2) the structural characteristics of decentralized UGC networks, and (3) thematic and incentive patterns in content creation and Zap-based rewards. Our analysis shows rapid growth followed by long-tail stabilization, while the interaction network remains highly modular and loosely connected, indicating fragmented yet persistent communities. Embedding-based clustering of textual posts identifies ten clusters on several topics: technical discussions, ideological debates, personal expression, community coordination, and media sharing, highlighting a hybrid ecosystem of social and technical discourse. We further find that knowledge-oriented content in Clusters 1 and 5 receives higher Zap engagement, suggesting the socialization of a primarily technical infrastructure. These findings advance the understanding of decentralized multimedia ecosystems by linking network decentralization with observed participation and engagement patterns in the absence of centralized moderation.
Classical Block Withholding (BWH) attacks have been extensively studied in block-dependent reward schemes, where pool members are compensated upon a block discovery within the pool. However, most contemporary mining pools operate under share-based schemes, wherein participants are paid immediately upon submission of valid shares. In this paper, we analyze BWH under Pay-Per-Share (PPS) and Full-PPS (FPPS) schemes for Nakamoto-style blockchains and prove that these mechanisms are not incentive compatible -- contrary to claims in prior literature. Under PPS/FPPS, the optimal strategy for a BWH attacker is the All-out Attack (AoA): the adversary allocates its entire hashpower toward the victim pool, submitting only partial Proof-of-Work shares (pPoW) while withholding all valid blocks, i.e., full Proof-of-Work (fPoW). Prior to the first difficulty adjustment, the adversary incurs negligible loss from withheld fPoWs. After the adjustment reduces block difficulty, the adversary either generates more pPoWs per unit time or, if pPoW difficulty is held fixed, earns a higher reward per share, in both cases achieving a relative gain of $\fracα{1-α}$ over pre-adjustment rates, where $α$ is the adversarial hashpower fraction. Honest miners benefit at the same rate as the adversary per unit hashpower, while the victim pool operator bears all losses, paying out-of-pocket for pPoW submissions without receiving fPoW compensation in return. Finally, advanced BWH variants such as Fork After Withholding (FAW) yield no additional profit under PPS/FPPS.
Sushila Dhaka, Jane-Hwa Huang, Chin-Min Yu, Li-Chun Wang
This paper proposes an SNR-adaptive optimal threshold design framework for energy detection in Dynamic Spectrum Access (DSA). Unlike conventional constant false-alarm rate (CFAR)-based schemes that determine the sensing threshold solely from a predefined false-alarm constraint, the proposed method directly minimizes the total probability of error by deriving a closed-form analytical solution. The threshold optimization problem is formulated as a quadratic expression whose coefficients explicitly characterize the effects of signal-to-noise ratio (SNR) and number of samples. This analytical structure enables adaptive threshold selection under heterogeneous SNR conditions without exhaustive numerical search. Simulation results demonstrate that the proposed approach reduces the error probability compared with fixed-threshold and detection-constrained schemes, particularly in low-SNR regimes. Furthermore, the impact of SNR and number of samples on detection performance is systematically analyzed, providing deeper insight into the trade-off between false alarm and missed detection. The proposed framework improves sensing reliability and practical adaptability in dynamic spectrum access systems. It also establishes a foundation for secure cooperative spectrum sensing, including blockchain-assisted aggregation mechanisms.
Smart Contracts participate in contract performance by converting contractual terms into executable code, presenting new challenges to traditional contract law. Portugal’s current contract legislation lacks explicit provisions for Smart Contracts, with key legal issues including the determination of contract formation and validity, the coordination between automatic execution mechanisms and contractual remedies, and liability allocation for technical risks. Through analyzing Portugal’s contract law framework and the technical characteristics of Smart Contracts, as well as referencing international legislative and judicial experiences, this study proposes an applicable solution within Portugal's existing contract law system. By maintaining technical neutrality and contractual functionality, Smart Contracts can achieve harmonious application through holistic assessment of conduct, differentiated execution remedies, and tiered liability allocation.
Financial issues particularly affect individuals and their security. Conducting social research for 28 years, I have observed, among other things, changes in the operationalization of finance, its formal security, and, after the transition to electronic forms, the security in this area. I noticed differences in security with respect to fiber optic transmission and Wi-Fi. I also examined electronic investment methods commonly known as stock exchanges. In my country, Poland, electronic banking and stock exchanges appeared much later than in the United States. There is reason to assume that it was US finance that initiated stock exchanges in Poland, a country treated by overseas officials as a form of financial and economic colonization. Consequently, the United States became a subject of interest, both in terms of the emerging social class, which I have termed "the stock market rich," distinguishing them from those who obtain wealth through their own work and are creating a new social structure. In my research, I set out to identify individual and group behaviors, both formal and informal. The areas I addressed included need satisfaction, mutual cooperation, and motivation. I've noticed a certain uniqueness recurring in all human structural forms, regardless of location or type of implementation. To my surprise, it involves the negation of existing rules and is dependent solely on the duration of an entity's existence. It doesn't depend at all on whether it's an economic, administrative, educational, or financial entity. This article focuses on society and its operation within a financial framework in an electronic context.
This study addresses the persistent challenges of limited transparency and inefficiency in accounting information systems, particularly in the context of financial reporting and auditing. It aims to examine the role of blockchain in enhancing transparency and improving audit processes within accounting systems. The research adopts a systematic literature review approach by analyzing 43 selected academic articles and relevant industry reports published between 2019 and 2026. The analysis focuses on identifying key characteristics, mechanisms, and implications of blockchain adoption in accounting practices. The findings indicate that blockchain has strong potential to improve data transparency, traceability, and reliability through features such as distributed ledgers, immutability, and smart contracts. These characteristics support real-time financial reporting and enable more continuous and efficient audit processes. The study also identifies several implementation challenges, including regulatory uncertainty, high adoption costs, and limited professional expertise. Furthermore, this research proposes a conceptual framework integrating blockchain into accounting information systems to support better governance and decision-making. The study contributes to the growing discourse on digital transformation in accounting, particularly in emerging economies.
The Criminal Evidence Management System using Blockchain is designed to provide a secure, transparent, and tamper-resistant platform for managing digital criminal evidence throughout its lifecycle.Traditional evidence management systems rely on centralized databases, making them vulnerable to unauthorized access, data manipulation, and single points of failure.Such limitations can compromise the integrity of evidence and weaken the chain of custody during legal proceedings.To address these challenges, the proposed system leverages blockchain technology to ensure the authenticity, immutability, and traceability of digital evidence.The system employs Ethereum blockchain and Solidity smart contracts to securely record evidence-related transactions, while Python, Django, and Web3 facilitate seamless interaction between users and the blockchain network.Role-based access control enables administrators and investigating officers to perform authorized operations such as evidence submission, retrieval, and verification.Every transaction is permanently recorded on the blockchain, creating an auditable history that enhances accountability and prevents unauthorized modifications.The proposed solution improves the reliability and efficiency of evidence management by eliminating the risks associated with centralized storage and manual record-keeping.Through secure storage, transparent access, and automated verification, the system strengthens the chain of custody, increases trust among law enforcement agencies, and supports the admissibility of digital evidence in judicial processes, making it a robust solution for modern forensic investigations.
Martin Brennecke, Muriel-Larissa FRANK, Nils MESSERSCHMIDT, Gilbert FRIDGEN
Research on innovation resistance has revealed various barriers to the use of digital technologies. However, these studies are typically constrained to siloed perspectives, which prevent comparisons between digital technologies. Therefore, this paper is an initial attempt to explore barriers to adoption across two digital technologies of recent years: generative artificial intelligence (GAI) and distributed ledger technology (DLT). To critically assess the continued applicability of Innovation Resistance Theory (IRT) in relation to these two digital technologies, we analyze a dataset containing over 38,000 Reddit comments. Notably, we identify functional, psychological, and environmental barriers pertaining to both digital technologies, thus enabling us to propose an extension to IRT. Our insights contribute to a better understanding of the adoption of complex digital technologies by uncovering both unique and shared barriers. Thus, this work goes beyond mere absence of adoption factors and can inform the design of digital technologies and organizational adoption management strategies.