This study aims to analyze the influence of performance-based reward systems and decision decentralization on innovation in human resource management. In an era of increasingly dynamic global competition, organizations are required not only to carry out HRM functions efficiently but also to adopt innovative approaches to address challenges posed by the work environment, technology, and employee expectations. A performance-based reward system, which directly links rewards to individual or team performance, can motivate employees to engage in innovative behavior, while decision decentralization allows for faster decision-making and greater responsiveness to local needs. This study used a quantitative approach with a survey method to collect data from structural and functional officials in six Makassar City government agencies that implement a performance-based reward system and decision decentralization. The results indicate that both variables have a positive effect on HRM innovation, both separately and simultaneously. These findings provide theoretical and practical insights into the importance of integrating a fair and transparent reward system with a more autonomous decision-making structure in encouraging innovation in human resource management. Policies that encourage these two elements can strengthen competitive advantage and organizational performance.
Digital product passports outline information about a product’s lifecycle, circularity, and sustainability-related data. Sustainability data contains claims about carbon footprint, recycled material composition, ethical sourcing of production materials, etc. Also, upcoming regulatory directives require companies to disclose this type of information. However, current sustainability reporting practices face challenges, such as greenwashing, where companies make incorrect claims that are difficult to verify. There is also a challenge of disclosing sensitive production information when other stakeholders, such as consumers or other economic operators, wish to verify sustainability claims independently. Zero-knowledge proofs (ZKPs) provide a cryptographic system for verifying statements without revealing sensitive information. The goal of this research paper is to explore ZKP cryptography, trust models, and implementation concepts for extending DPP capability in privacy-aware reporting and verification of sustainability claims in products. To achieve this goal, first, formal representations of sustainability claims are provided. Then, a data matrix and trust model for generating proofs are developed. An interaction sequence is provided to show different components for various proof generation and verification scenarios for sustainability claims. Lastly, the paper provides a circuit template for the proof generation of an example claim and a credential structure for their input data validation. The proposed approach is assessed using a scenario-based evaluation to check the performance metrics for data credential verification and proof generation for verifying material composition in a product.
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Physical Unclonable Functions (PUFs) and Hardware Security
The contemporary art world is undergoing a foundational shift, driven by the emergence of blockchain technology and its most culturally salient application: Non-Fungible Tokens (NFTs). This transition marks a move from the physical, gatekept spaces of the "White Cube" gallery to the distributed, code-governed networks of the blockchain ledger. This article argues that this is not merely a change in the medium of art's financialization, but a profound process of decentralization reshaping the core pillars of the art ecosystem-curation, valuation, ownership, and access. We analyze how blockchain disrupts traditional, centralized art market models by enabling peer-to-peer transactions, immutable provenance tracking, and fractional ownership through smart contracts. Crucially, we examine the rise of algorithmic and community-driven curation, where platforms like SuperRare or DAOs (Decentralized Autonomous Organizations) challenge the authority of the traditional curator-institution. A conceptual framework (Figure 1) maps this new ecosystem, while a comparative table (Table 1) delineates the paradigm shifts across key domains. Through case studies of NFT platforms, crypto-art movements, and artist collectives, we demonstrate both the emancipatory potential and the critical tensions within this decentralization. We conclude that while blockchain introduces new forms of transparency, accessibility, and artist empowerment, it simultaneously engenders novel hierarchies, environmental concerns, and questions about the nature of cultural value in a digitally native era. The future of visual culture will be negotiated in the space between the aesthetic aura and the verifiable hash.
The rapid evolution of digital assets transforms cryptocurrencies into one of the most volatile and data-rich financial markets. Their nonlinear and unpredictable nature limits the effectiveness of traditional forecasting models, motivating the use of machine learning methods to identify hidden patterns and short-term price movements. This study compares the performance of Logistic Regression (LR), Random Forest (RF), XGBoost, Support Vector Classifier (SVC), K-Nearest Neighbors (KNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) models in predicting the daily price directions of Bitcoin (BTC), Ethereum (ETH), and Ripple (XRP). Extensive data preprocessing and feature engineering are performed, integrating a broad set of technical indicators to enhance model generalization and capture temporal market dynamics. The results show that XGBoost achieves the highest classification accuracy of 55.9% for BTC and 53.8% for XRP, while LR provides the best result for Ethereum with an accuracy of 54.4%. In trading simulations, XGBoost achieves the strongest performance, generating a cumulative return of 141.4% with a Sharpe ratio of 1.78 for Bitcoin and 246.6% with a Sharpe ratio of 1.59 for Ripple, whereas LSTM delivers the best results for Ethereum with a 138.2% return and a Sharpe ratio of 1.05. Compared to recent studies, the proposed approach attains slightly higher accuracy, while demonstrating stronger robustness and profitability in practical backtesting. Overall, the findings confirm that through rigorous preprocessing machine learning-based strategies can effectively capture short-term price movements and outperform the conventional buy-and-hold benchmark, even under a simple rule-based trading framework.
Probate stands as a bastion of legal formalism, seemingly resistant to the transformative currents of digital innovation that have swept through other domains of American law. While financial transactions, real property conveyances, and contract execution have increasingly begun exploring the use of Web3 technologies such as blockchain and smart contracts, estate and probate law remain tethered to paper-based procedures and rigid execution requirements. Nevada was the first state to provide legal support for Web3 technology, amending its Uniform Electronic Transactions Act statutes in 2017 to recognize blockchain-based transactions as valid and judicially enforceable. Yet despite this progressive legislative framework, the state’s estate and probate laws remain unchanged. What reforms are required to extend this legal recognition of blockchain to testamentary instruments and probate administration? To explore this, I begin in Part I by examining Nevada’s existing statutory framework for traditional paper wills, electronic wills, and probate administration, identifying where these laws diverge from the state’s more progressive legislation governing blockchain-based transactions. In Part II, I introduce the concept of a blockchain will, explain its technical functionality, and discuss how such instruments can be amended, revoked, or rendered obsolete. I then propose specific legislative reforms that could allow blockchain wills to serve as legally recognized alternatives to traditional paper wills, including the creation of a state-managed blockchain will registry that would provide the procedural infrastructure for securely filing, validating, and preserving blockchain wills. To illustrate how these proposals might operate in practice, hypothetical examples modeling blockchain-based testamentary execution and probate are included. Finally, I analyze the policy considerations both for and against reform, examining the legal barriers that must be addressed and the potential benefits this technology could bring to probate courts.
Ashwag Alotaibi, Huda Aldawghan, M. M. Hafizur Rahman
This study summarizes the body of research on the IoT and NFTs overlap, highlighting important security concerns, the function of blockchain technology, and implications for future study and smart environment applications. IoT devices provide creative solutions that boost operational effectiveness and enhance user experiences as they spread throughout different sectors. But there are also serious drawbacks to this expansion, especially in terms of security and privacy. At the same time, NFTs unique digital assets verified by blockchain technology—have become extremely popular because of their unique features and wide range of uses. This paper carefully looks at how security frameworks in digital ecosystems may be impacted by the integration of IoT and NFTs. The results emphasize how urgently this integration must be studied further to minimize new risks and maximize the advantages of IoT and NFTs across a variety of sectors. The study intends to contribute to a more secure and effective IoT ecosystem by examining the difficulties presented by this integration. Contributing to the development of a more robust and secure IoT ecosystem is the ultimate aim of this research. This study aims to open the door for future developments that optimize the benefits between the two technologies while reducing risks by recognizing and evaluating the difficulties brought about by the integration of IoT and NFTs. Both academics and industry stakeholders navigating the rapidly changing IoT and blockchain world will find great significance in the results of this research.
David Arroyo, Rafael Mata Milla, Marc Almeida Ros, Nikolaos Lykousas · 7 authors
Crime as a Service (CaaS) has evolved from isolated criminal incidents to a broad spectrum of illicit activities, including social media manipulation, foreign information manipulation and interference (FIMI), and the sale of disinformation toolkits. This article analyses how threat actors exploit specialised infrastructures ranging from proxy and VPN services to AI-driven generative models to orchestrate large-scale opinion manipulation. Moreover, it discusses how these malicious operations monetise the virality of social networks, weaponise dual-use technologies, and leverage user biases to amplify polarising narratives. In parallel, it examines key strategies for detecting, attributing, and mitigating such campaigns by highlighting the roles of blockchain-based content verification, advanced cryptographic proofs, and cross-disciplinary collaboration. Finally, the article highlights that countering disinformation demands an integrated framework that combines legal, technological, and societal efforts to address a rapidly adapting and borderless threat
As the Ethereum platform continues to mature and gain widespread usage, it is crucial to maintain high standards of smart contract writing practices. While bad practices in smart contracts may not directly lead to security issues, they elevate the risk of encountering problems. Therefore, to understand and avoid these bad practices, this paper introduces the first systematic study of bad practices in smart contracts, delving into over 47 specific issues. Specifically, we propose SCALM, an LLM-powered framework featuring two methodological innovations: (1) A hybrid architecture that combines context-aware function-level slicing with knowledge-enhanced semantic reasoning via extensible vectorized pattern matching. (2) A multi-layer reasoning verification system connects low-level code patterns with high-level security principles through syntax, design patterns, and architecture analysis. Our extensive experiments using multiple LLMs and datasets have shown that SCALM outperforms existing tools in detecting bad practices in smart contracts.
Dynamiczny rozwój technologii rozproszonych rejestrów (DLT – Distributed Ledger Technology) oraz rosnące oczekiwania społeczne w zakresie transparentności finansów publicznych skłaniają do analizy możliwości wdrożenia technologii blockchain w systemie zarządzania wydatkami jednostek samorządu terytorialnego (JST). W artykule poddano ocenie potencjał blockchain jako narzędzia eliminującego asymetrię informacyjną i zwiększającego społeczną kontrolę nad finansami JST. Technologia ta, dzięki niezmienności rejestrów oraz kryptograficznemu potwierdzaniu transakcji, może przyczynić się do redukcji ryzyka korupcji i nadużyć budżetowych. Szczególną uwagę poświęcono aspektom prawnym implementacji blockchain w sektorze publicznym, w tym jego zgodności z ustawą o finansach publicznych, przepisami dotyczącymi zamówień publicznych oraz regulacjami RODO. W artykule przeprowadzono także analizę porównawczą międzynarodowych wdrożeń blockchain w administracji publicznej oraz zaproponowano model implementacji tej technologii w kontekście polskich JST.
The research presents SmartProof as an artificial intelligence system which uses large language models and blockchain technology to create automated decentralized agreement generation and auditing and validation processes. SmartProof combines natural language code generation with AI security evaluation and IPFS-based decentralized storage and EIP-712 compliant digital signature functionality. The system enables users to develop smart contracts from high-level descriptions which then undergo automated verification before the system finishes the agreement process through blockchainbased verification of on-chain registration. The prototype system shows that AI-based contract creation tools shorten development periods and minimize programming mistakes and the multiagent auditing system identifies system weaknesses to generate trust-based risk assessment for deployment. The system achieves improved performance because it stores data outside the blockchain network and manages digital signatures which reduces gas costs and boosts system performance. SmartProof enables organizations to handle multiple agreements through one system which provides complete agreement transparency and complete security from contract inception to blockchain deployment.
An open question recently posed by Fawzi and Ferme [IEEE Transactions on Information Theory 2024], asks whether non-signaling (NS) assistance can increase the capacity of a broadcast channel (BC). We answer this question in the affirmative, by showing that for a certainK-receiver BC model, called Coordinated Multipoint broadcast (CoMP BC) that arises naturally in wireless networks, NS-assistance provides multiplicative gains in both capacity and degrees of freedom (DoF), even achievingK-fold improvements in extremal cases. Somewhat surprisingly, this is shown to be true even for 2-receiver broadcast channels that are semi-deterministic and/or degraded. In a CoMP BC,Bsingle-antenna transmitters, supported by a backhaul that allows them to share data, act as oneB-antenna transmitter, to send independent messages toKreceivers, each equipped with a single receive antenna. A fixed and globally known connectivity matrix specifies for each transmit antenna, the subset of receivers that are connected to (have a non-zero channel coefficient to) that antenna. Besides the connectivity, there is no channel state information at the transmitter. The receivers have perfect channel knowledge. We show that NS-assistance has no DoF advantage in a fully connected CoMP BC. The DoF region is fully characterized for a class of connectivity patterns associated with tree graphs, for which the classical sum-DoF value is shown to be the number of leaf nodes, while the NS-assisted sum-DoF value is the total number of all (non-root) nodes. For arbitrary connectivity patterns, the sum-capacity with NS-assistance is bounded above and below by the min-rank and triangle number of the connectivity matrix, respectively, leading to matching bounds in many cases, e.g., if min(B,K) ≤ 6. While translations to Gaussian settings are demonstrated, for simplicity most of our results are presented under noise-free, finite-field (Fq) models. Converse proofs for classical DoF are found by adapting the Aligned Images bounds to the finite field model. Converse bounds for NS-assisted DoF/capacity extend the same-marginals property to the BC with NS-assistance available to all parties. Beyond the BC setting, even stronger (unbounded) gains in capacity due to NS-assistance are established for certain ‘communication with side-information’ settings, such as the fading dirty paper channel.
Background: Mental health accounts for an estimated 14% of the global disease burden yet receives less than 2% of health budgets in most countries, with even lower investment in low- and middle-income settings. This study examines federal mental health financing trends from 2021-2025 to assess whether legislative reform translated into fiscal prioritization. Methods: A mixed-methods policy analysis was conducted, combining quantitative analysis of federal budget appropriation documents (2021-2025) with qualitative documentary review and comparative case studies. Mental health allocations were assessed by recurrent and capital expenditure, institutional distribution, and proportional share of total federal health spending. WHO reports, national policy documents from Ghana and Kenya, and peer-reviewed literature informed comparative analysis. Results: Federal mental health allocations increased from ₦23.33 billion in 2021 to ₦88.24 billion in 2025, a 278% nominal rise. However, the sector’s share of the total health budget declined from 3.67% to 3.12%, indicating relative marginalization. Over 90% of funding supported recurrent expenditures in ten federal neuropsychiatric hospitals, with minimal investment in community-based services or primary care integration. In contrast, Ghana and Kenya more effectively leveraged legislation, fiscal decentralization, and insurance mechanisms to expand access. Conclusion: Despite legislative reform, Nigeria’s mental health financing remains centralized, hospital-focused, and misaligned with population needs. Institutional inertia, weak coordination, and delayed implementation of the Act have constrained equitable scale-up. Activating the Mental Health Fund and integrating mental health into national financing mechanisms are urgently required to prevent deepening inequities.
Amid intensifying challenges of global climate change, China—as the world’s largest carbon emitter and a major manufacturing hub—occupies a pivotal position in the global industrial green transformation. Drawing on environmental federalism theory and China’s decentralized governance model, this study develops a framework of “green finance–local government competition–industrial green transformation.” Using panel data from 283 cities in China, we employ spatial econometrics and mediation effect models to test the dual mechanisms by which green finance promotes industrial green transformation. The findings indicate that (1) green finance promotes industrial green transformation; (2) green finance advances industrial green transformation by dismantling China’s traditional local government competition–based development model and removing the institutional suppression arising from “race-to-the-bottom competition”; (3) the effect of green finance exhibits long-run characteristics and a “benchmark–imitation” pattern; (4) baseline environmental conditions strengthen the influence of green finance on industrial green transformation; (5) incorporating ecological civilization development into officials’ performance evaluations can effectively reshape policy incentives and amplify the positive role of green finance. Thus, we propose differentiated green finance policies, the construction of a governance mechanism that integrates fiscal–financial–ecological compensation, and the optimization of ecological civilization assessment indicators to curb campaign-style governance.
The withdrawal of the USA from the World Health Organization and the freeze on USAID are among the major events in the realm of U.S. foreign policy under the U.S. president. Within his broader “America First” policy, aimed at reducing the U.S.‘s international commitments and rethinking its role in global organizations and foreign aid, this review attempts to make a case for Africa by examining the implications of recent reductions in U.S. funding. We conducted a comparative case study of Nigeria, Ghana, Zambia, and Rwanda, selected for their aid volume, exposure to disruption events, and availability of outcome data. Using process tracing and critical narrative synthesis, we analyzed policy documents, expenditure reports and peer-reviewed studies to assess how each country responded to aid disruptions and what structural factors shaped their resilience or fragility. Three dominant patterns emerged: acute service interruptions (Nigeria, Zambia), structural fragmentation (Ghana), and resilient adaptation (Rwanda). Key drivers of vulnerability included overreliance on tied aid, SAP-era health system legacies, and underdeveloped domestic financing mechanisms. Rwanda’s ability to maintain high ART coverage and reduce malaria deaths by 88% during funding cuts reflects a deliberate break from aid dependency through community-based insurance, decentralized governance, and regional procurement strategies. Donor transitions are not neutral events; they expose and exacerbate pre-existing structural weaknesses. Current models that frame aid withdrawal as empowerment risk, replicating past harm unless coupled with institutional reform and reciprocal accountability. This study suggests assessing transition readiness and reorienting global health partnerships toward equitable, resilient, and sovereign systems.
This paper presents zero knowledge proofs, their cryptographic significance and applications. It presents a basic classification: interactive and noninteractive zero knowledge proofs. It presents and compares three protocols of non-interactive zero knowledge proofs: ZK-SNARK, ZK-STARK and Bulletproofs. It presents the quadratic residue problem and proofs it with both interactive and non-interactive zero knowledge proofs. The non-interactive protocol used to prove the quadratic residue problem is ZK-SNARK. The proof is implemented in the Python programming language, using python-snark library.
The digital transformation of finance and accounting is accelerating with AI, blockchain, and automation, reshaping financial operations, auditing, and compliance. This study conducts a thematic analysis of academic literature (2018–2025) and industry reports from PwC, Deloitte, EY, HSBC, and central banks to examine key trends. Six themes emerged: automation and efficiency, security and fraud prevention, decentralization, financial inclusion, regulatory challenges, and adoption barriers. Findings show that AI and RPA enhance financial reporting and fraud detection, while blockchain improves transparency and security but poses scalability and regulatory challenges. Decentralized finance (DeFi) and digital currencies like JPM Coin and the Digital Yuan are transforming transactions but raise concerns over compliance and illicit activity risks. Mobile banking and blockchain-based solutions improve financial inclusion, yet digital literacy and security risks remain barriers. Using NVivo-based thematic analysis, the study identifies key trends shaping the future of financial digitalization. While AI and blockchain drive efficiency, regulatory complexities and adoption barriers must be addressed for sustainable transformation. Future research should explore scalability, AI-enhanced compliance, and blockchain’s role in financial security.
The article presents an empirical comparison of three contemporary Layer-2 scaling solutions for the Ethereum blockchain: Scroll, Linea, and Base, representing zk-rollup and optimistic rollup architectures. The study aims to evaluate the transaction processing speed and stability of selected Layer-2 networks using real-time data collected from blockchain explorers (Blockscout, Lineascan, Basescan). The dataset comprises 45,000 transactions processed in October 2025 and aggregated at one-second resolution (1 Hz). Statistical analyses include ANOVA, Kruskal–Wallis, Levene, and Brown–Forsythe tests, as well as ADF and KPSS stationarity diagnostics, used to assess diferences in throughput and operational stability across the examined networks. The results indicate that the Base network achieves the highest mean throughput (≈ 102 TPS) and the lowest temporal volatility, whereas Linea and Scroll exhibit non-stationary, highly variable transaction dynamics driven by periodic batching. The fndings confrm the persistence of the scalability trilemma—where improvements in performance may come at the cost of higher centralization and operational dependency. This research contributes to the quantitative assessment of rollup efciency and provides a reference point for further empirical studies on blockchain scalability.
Saiful Ruchiyat Cosahan, Ahmad Yunani, Asrid Juniar, Muzdalifah Muzdalifah
This Systematic Literature Review (SLR) analyzes 38 empirical studies published between 2015 and 2025 (sourced from Scopus and Sci-ScienceDirect) to map blockchain-based funding mechanisms in the context of venture capital (VC) and entrepreneurial finance. The review addresses four research questions concerning the evolution of these mechanisms, their impact on startup performance, and associated risks and regulatory challenges. The findings establish a robust taxonomy of mechanisms, including Initial Coin Offerings (ICOs), Security Token Offerings (STOs), and Decentralized Autonomous Organizations (DAOs), each presenting unique features and regulatory profiles. Crucially, the review highlights significant gaps in long-term performance data, revealing challenges related to investor protection, fraud risk, and regulatory uncertainty. By integrating Signaling Theory and Governance Theory, the study discusses how tokenomics and team credibility function as signals instead of traditional VC due diligence, presenting a critical comparison between token-based funding and traditional-al venture capital financing. This paper offers valuable insights for academics, policymakers, and industry practitioners by providing a com-comprehensive map of the field, suggesting avenues for future empirical research, and offering focused policy implications regarding regulation and investor safety in emerging markets.
The thesis deals with the development of a decentralized Ethereum-based application for purchasing, selling and playing music. The goal of the application is to demonstrate the use of a blockchain-based platform that can replace corporate intermediaries.
Historical Context and Problem Statement The digital revolution has created two parallel challenges that have resisted comprehensive solutions: Internet Data Transfer Limitations: Despite decades of progress, internet download speeds remain constrained by inefficient protocols that don't adapt to network topology dynamics. Traditional download managers like IDM operate with static segmentation strategies that ignore the quantum-inspired probabilistic nature of network paths. Web3 Liquidity Fragmentation: Decentralized finance (DeFi) suffers from fragmented liquidity across multiple venues, resulting in significant MEV exploitation. As documented by Qin et al. (2021), MEV extraction has cost users over $680 million in 2021 alone, with no comprehensive solution addressing the root cause. These seemingly disconnected problems share a common underlying structure: both involve the transfer of "value" (data or financial assets) across complex networks where efficiency is hampered by non-resonant transmission strategies.
Hau Vasio Sarmento Soares, Sundaru Guntur Wibowo, Syahrul Anwar
This study analyzes the legal framework of Non-Fungible Token (NFT)-based digital vaccine certificates in the context of digital free trade, focusing on security, privacy, and international recognition. Using normative and comparative legal research methods with a multidisciplinary approach, the study integrates perspectives from law, digital technology, and international policy. The study examines three main aspects: first, security, evaluating how NFTs ensure authenticity, data integrity, and protection against manipulation through encryption, blockchain, and smart contracts; second, privacy, analyzing how personal data and the privacy rights of certificate holders are protected under national and international regulations, emphasizing data minimization, user consent, and secure access; and third, international recognition, assessing the extent to which NFT-based certificates can be recognized globally, highlighting regulatory harmonization and legal barriers. The findings indicate that NFT-based vaccine certificates provide strong technical security and privacy protection, but legal recognition across jurisdictions remains inconsistent. The study concludes that while NFTs have significant potential to facilitate secure and verifiable digital health credentials in global trade, harmonization of national and international regulations and the implementation of legal standards are crucial to ensure their effectiveness and legal validity worldwide.
The development of digital technology has enabled the emergence of Non-Fungible Tokens (NFTs) as digitally authenticated assets recorded on blockchain networks, including their use in representing ownership of digital land within metaverse ecosystems. However, Indonesia has not yet formulated explicit regulatory provisions governing the legal classification of NFTs, the scope of supervisory authority, or the standards for consumer protection. This regulatory absence results in legal ambiguity regarding the placement of NFTs within the framework of Financial Sector Technology Innovation (ITSK) under Law No. 4 of 2023, and simultaneously presents risks to consumers, including fraud, data misuse, loss of access to digital assets, and a lack of clear accountability mechanisms on NFT platforms. This research examines the legal status of NFTs in relation to ITSK and analyzes the adequacy of current consumer protection measures in NFT-based digital land transactions. Through a normative juridical method, the study finds that NFTs have not been formally classified within ITSK, nor assigned to a definitive supervisory authority, whether OJK or Bappebti. As such, consumer protection remains reliant on general norms under Law No. 8 of 1999, which are insufficient to address the specific risks inherent in NFT transactions. This research recommends the issuance of derivative regulations by OJK and/or Bappebti to clarify NFT classification, establish platform obligations, and strengthen consumer protection.
The web3 applications have recently been growing, especially on the Ethereum platform, starting to become the target of scammers. The web3 scams, imitating the services provided by legitimate platforms, mimic regular activity to deceive users. However, previous studies have primarily concentrated on de-anonymization and phishing nodes, neglecting the distinctive features of web3 scams. Moreover, the current phishing account detection tools utilize graph learning or sampling algorithms to obtain graph features. However, large-scale transaction networks with temporal attributes conform to a power-law distribution, posing challenges in detecting web3 scams. To overcome these challenges, we present ScamSweeper, a novel framework that emphasizes the dynamic evolution of transaction graphs, to identify web3 scams on Ethereum. ScamSweeper samples the network with a structure temporal random walk, which is an optimized sample walking method that considers both temporal attributes and structural information. Then, the directed graph encoder generates the features of each subgraph during different temporal intervals, sorting as a sequence. Moreover, a variational Transformer is utilized to extract the dynamic evolution in the subgraph sequence. Furthermore, we collect a large-scale transaction dataset consisting of web3 scams, phishing, and normal accounts, which are from the first 18 million block heights on Ethereum. Subsequently, we comprehensively analyze the distinctions in various attributes, including nodes, edges, and degree distribution. Our experiments indicate that ScamSweeper outperforms SIEGE, Ethident, and PDTGA in detecting web3 scams, achieving a weighted F1-score improvement of at least 17.29% with the base value of 0.59. In addition, ScamSweeper in phishing node detection achieves at least a 17.5% improvement over DGTSG and BERT4ETH in F1-score from 0.80.