Smart contracts underpin a wide range of decentralized applications—from financial services to supply-chain management—but their immutability and direct control of assets magnify the impact of any security bugs. Although many fuzz approaches have been proposed and have demonstrated their effectiveness in uncovering vulnerabilities, existing methods often rely on unguided random mutation scheduling, generate redundant inputs, and fail to adapt to smart contract-specific characteristics. To overcome these challenges, we present FuzzMaster, a feedback-driven fuzzing framework that combines deep reinforcement learning (DRL) with lightweight probabilistic scheduling to steer mutation selection at runtime intelligently. By continuously analyzing execution feedback—code coverage, function-call sequences, and vulnerability signals—FuzzMaster’s DRL agent and probabilistic tables prioritize high-impact mutations and avoid wasted effort on redundant seeds. On standard VeriSmart and SmartBugs benchmarks, FuzzMaster achieves a 66.2% detection rate with 100% precision (versus 46.9% for ItyFuzz and 43.1% for Confuzzius) and uncovers most bugs within the first second of execution. Meanwhile, in real-world Ethereum contracts, FuzzMaster identified 97 vulnerabilities in 6 categories. These results demonstrate that dynamic, vulnerability-aware mutation scheduling can dramatically improve both the efficiency and effectiveness of smart contract fuzz testing.
The rapid increase in distributed mobile e-learning systems has resulted in numerous security threats, including student data protection, secure access, transparency, and decentralized education management. Traditional cloud-based e-learning systems have been prone to various risks, such as centralization vulnerability, data access violations, identity theft, and lack of scalability in a highly variable wireless learning environment. This paper proposes a blockchain-integrated, privacy-preserving, distributed mobile e-learning architecture for securely and autonomously managing student data. In this framework, blockchain technology will be used for ensuring a decentralized ledger, lightweight cryptography, smart contract-based authentication, and distributed data storage. Blockchain transaction verification, data encryption and sharing, distributed data storage, and smart contract execution are the methodologies utilized by this system to ensure secure academic record and activity management in a mobile environment. The evaluation of the proposed architecture will involve performance measurement of the following parameters: authentication accuracy, privacy protection capability, transaction processing speed, throughput, and data storage efficiency. It was revealed from experimental studies that the suggested approach provided 98.3% in terms of identification, 97.5% in relation to data privacy protection, and 91.8% concerning storage efficiency compared to other methods, including traditional cloud-based learning systems and previous blockchain-based education platforms. In addition, the suggested system enabled reducing the transaction time to 190 ms and increasing the throughput speed up to 465 transactions per second, which proves its high efficiency and capability of functioning in a distributed wireless environment. Therefore, it can be stated that introducing blockchain technology in distributed mobile e-learning systems enhances the level of privacy, resilience against malicious attacks, traceability, and autonomy in controlling personal information. The introduced concept provides a basis for designing a highly reliable and scalable framework for the future generation of wireless educational communities based on the management of decentralized and reliable data.
Health care data management comes with numerous barriers as a result of the use of different systems of record keeping, which are not compatible and increase the risks for data protection and privacy. Medical records are frequently distributed throughout various clinics and hospitals, and due to this it is hard to share information when patients are being treated. Centralized record systems bring unauthorized access to records and the problems related to the safety of data. In order to enhance the level of confidence of people and improve the level of transparency of health care data, advanced people choose decentralized technologies and uses cryptography for these purposes. Blockchain technology offers an unchangeable and decentralized ledger that guarantees safe monitoring of all information despite the presence of any centralized body. Coupled with sophisticated encryption methods, it provides the ability to limit access to private health information. In order to provide secure and respect privacy regarding medical data sharing, an Electronic Health Record (EHR) system powered by blockchain technologies is proposed. Patient record metadata is recorded on-chain while health data itself is stored on encrypted off-chain storage. In the realm of access management, smart contracts facilitate patients in designating by whom their records can be accessed and modified. The privacy of information is further strengthened by advanced cryptographic techniques like attribute-based encryption and zero-knowledge proofs. The system provides seamless interoperability among hospitals, laboratories, and telemedicine systems while ensuring high levels of security. The results of performance evaluation demonstrate that this method facilitates reliable transaction processing while providing better security, transparency and control than traditional centralized EHR systems.
This technical report provides an empirical evaluation of Bitcoin Layer-2 execution environments (BOB, Bitlayer, Citrea, Stacks, and Rootstock) against a six-layer architectural framework designed for institutional-grade decentralized finance (DeFi). Using Tage_Root — a purpose-built reference implementation operationalizing Bitcoin-native execution (L1) and trust-minimized bridging (L2) — the analysis assesses conditions required for credible BTC-denominated yield markets, including intent-based routing, autonomous capital allocation, zero-knowledge compliance, and accountable governance. The findings reveal that while several systems have substantially solved the bridge problem at the technical level, critical higher-layer infrastructure remains absent or weak. This architectural gap explains the persistent idleness of bridged BTC and the low capital efficiency observed in BTCFi protocols, despite significant growth in bridging capacity. The report offers a code-grounded diagnostic benchmark and lays the empirical foundation for forthcoming theoretical work on the “Bridge Problem” and the pricing of Bitcoin-denominated yield. It argues that trust-minimized execution alone is insufficient for institutional capital formation in Bitcoin DeFi.
Information and Communication Technologies such as blockchain can significantly contribute to achieving the Sustainable Development Goals (SDGs). Without a doubt, blockchain, as one of the most valuable technological advancements, has been introduced over the past decade and has played a significant role in the industrial revolution. Blockchain technology is progressively taking over the business world. Blockchain as a disruptive technology and a driver for social change has exhibited great potential to promote sustainable practices and help organizations and governments achieve the United Nations’ Sustainable Development Goals (SDGs). The emergence of other technologies derived from blockchain, such as decentralized finance (DeFi) and the Metaverse, has fundamentally transformed people’s daily lives and profoundly impacted future versions of digital businesses. The Blockchain technology revamped several industries, including Real Estate, Healthcare, Education, and Legal industry to name a few. It opened new doors of opportunities and profit for the entrepreneurs and established brands. The paper's main contribution is to advance knowledge about the role of blockchain for economic and sustainable development in countries of the world. Grounded in the innovation forecasting literature, this paper explores blockchain-based innovations and research in the context of economic and sustainable development.
Smart contracts have achieved significant success, however, their security remains a long-standing challenge. The immutability and transparency of smart contracts require establishing a strong mechanism to prevent private leakage and trusted data tampering. Apart from traditional logic and code-level vulnerabilities arising from insufficient control over contract variables and function parameters, smart contracts may store private-dependent information in blockchain records, which is a critical type of vulnerability, but often overlooked in existing security analysis. In this paper, we present an automated approach for synthesizing security policies, named SmartIFSyn, to eliminate information flow vulnerabilities in smart contracts. We formalize the semantics of Solidity, the most widely used smart contract language, and analyze information flow security of Solidity smart contracts from two perspectives: local-variable security and global-interaction security. We present a type system to guide the elimination of local-variable vulnerabilities by inferring a policy and resort to constraint solving to synthesize a desired policy in case that the type system fails. The policy ensures both local-variable and global-interaction security while it is maximally aligned with user preference. Furthermore, the policy can be subsequently converted into enforceable specifications. We implement our approach in a tool and evaluate it on 17,160 real-world Ethereum smart contracts. The experimental results demonstrate the efficacy of our approach, e.g., detected 243 vulnerabilities in 223 real-world Ethereum smart contracts.
For over half a century, the core paradigm of query optimization has been defined by a monotonic, scalar minimization convergence model aimed at suppressing computational resource consumption. This paper presents a radical paradigm shift that fundamentally subverts this traditional framework by establishing the Axiomatic Topological Inverse Query and Complexity Maximization Theory (ATIQ-CMT). Instead of pursuing local or global minima within discrete equivalence graphs, we reconstruct the relational algebra space into a non-Hausdorff, locally compact topological space governed by five foundational axioms. By introducing the Inverse Lipschitz Affine Expansion Mapping (ILAEM) under operator braid transformations, we demonstrate how compact query plans can be inversely dilated into divergent flows across high-dimensional complex affine varieties, creating irreversible mathematical obstructions for traditional gradient-based cost models. To maximize computational complexity natively, we execute a non-commutative extension of the relational algebra core via algebraically twisted join operators embedded in infinite-dimensional Lie algebras, effectively destroying the classic commutative-associative symmetry. We further inject un-decidable Diophantine predicates and 3-SAT arithmetical homomorphic graphs as computational obstructions, rigorously proving a non-polynomial exponential lower bound for physical query execution times. Utilizing sheaf theory and de Rham cohomology on chain complexes, we provide a definitive topological proof that the absolute semantic integrity of the query remains invariant throughout this chaotic dilation. Finally, we formulate a deterministic chaotic operator execution flow driven by high-order Lorenz mappings, maximizing the algebraic Shannon entropy of intermediate states. ATIQ-CMT bridges declarative relational logic and high-level structural topology, unlocking revolutionary potentials in zero-knowledge proof circuit synthesis, active cybersecurity defense, and the theoretical computational limits of neuro-symbolic and quantum systems.
Wireless Sensor Networks (WSNs) are widely used in critical applications such as environmental monitoring, healthcare, industrial automation, and military surveillance; however, their resource constraints, wireless communication, and unattended deployment make them highly vulnerable to node capture attacks.In such attacks, adversaries physically compromise sensor nodes to extract cryptographic keys and sensitive information, leading to key leakage, node impersonation, communication disruption, and large-scale network compromise.Existing key management schemes often rely on static key structures, they lack forward secrecy, and fail to identify structurally vulnerable nodes, resulting in weak resilience against progressive node capture attacks.To address these limitations, this paper proposes a threshold-based ECDHE-TSSS key management framework to detect vulnerable nodes and mitigate node capture attacks in WSNs.The proposed scheme introduces an attack matrix based on graph-theoretic metrics to identify high-risk nodes and provide adaptive protection through decentralized masking of secret shares.The Proposed Scheme integrates Elliptic Curve Diffie-Hellman Ephemeral (ECDHE) with Threshold Shamir Secret Sharing (TSSS) to achieve forward secrecy and strong resistance against node compromise while maintaining lightweight operations suitable for resource-constrained environments.A layered security architecture incorporating Schnorr-based Non-Interactive Zero-Knowledge Proof (NIZKP) authentication and distributed key revocation further enhances network resilience and secure communication.Simulation results demonstrate that the proposed scheme significantly reduces key compromise probability and improves overall network robustness compared with existing approaches.
The management and transfer of student archives in China constitute are mission-critical administrative processes governed by strict custodial regulations. However, the traditional paper-based "sealed-transfer" model is characterized by significant inefficiencies, risk of data loss, and limited mechanisms for verifying the data integrity during cross-institutional transitions. Although blockchain technology offers potential advantages in auditability and immutability, existing solutions often fail to balance privacy protection with high-performance requirements for large-scale archival data. This study proposes a decentralized, privacy-preserving framework that integrates the FISCO BCOS consortium blockchain, the InterPlanetary File System (IPFS), and Zero-Knowledge Proofs (ZKP). The system employs a multi-group architecture, leveraging IPFS for encrypted off-chain storage and zk-SNARKs generated via Circom to enable integrity verification without exposing sensitive data. Empirical evaluation was conducted using 30 archival samples ranging from 82 KB to 3.1 MB. Results indicate that the Paillier cryptosystem introduces significant performance bottleneck, with encryption latency exceeding one hour for files large than 2.3 MB. In contrast, a hybrid RSA+AES encryption scheme combined with ZKP archives stable, size-agnostic proof generation latency of approximately 850 ms and end-to-end transfer times under 3 seconds. These findings demonstrates that the proposed framework effectively replicates the traditional “sealed-transfer” mechanism through cryptographic means, providing a scalable and regulatory-compliant solution that aligns with the Archives Law of the People’s Republic of China and the Personal Information Protection Law (PIPL). This study provides a visible technical pathway for the digital transformation of national-level educational archive systems.
Mark Gerald Ruiz, Ramona Maria Miral, John Paolo Rivera
This paper examines the fiscal impacts of climate-related events in the Philippines and proposes policy measures to build a climate-resilient economy. Through cross-sectional analysis, it finds that the fiscal resilience of local government units (LGUs) is influenced by their dependence on external revenues, the availability of preallocated funds, and the severity of disasters. The results underscore the need for region-specific fiscal strategies that diverge from conventional frameworks, given the country’s decentralized disaster management system and the pivotal role of local institutions. The study recommends establishing a dedicated climate resilience fund, adopting climate-responsive budgeting, strengthening risk transfer mechanisms, incentivizing green investments, and enhancing LGU capacity to manage adaptation financing. Additionally, investments in climate research, data-driven governance, and public awareness are essential. Aligning climate finance with long-term development goals and the 2030 Agenda for Sustainable Development would integrate resilience into national planning, enabling the Philippines to better withstand climate risk while promoting sustainable growth and fiscal stability.
Lei Yu, Jingyuan Zhang, Xin Wang, Li Yang · 6 authors
Smart contracts automate the management of high-value assets, where vulnerabilities can lead to catastrophic financial losses. In the task of automated smart contract generation using Large Language Models (LLMs), this challenge is amplified by two interconnected failures: first, they operate as unauditable "black boxes" by failing to produce a transparent reasoning process, and second, as a consequence, they generate code riddled with critical security vulnerabilities. To address both issues, we propose SmartCoder-R1 based on Qwen2.5-Coder-7B, a novel framework for secure and explainable smart contract generation. It begins with Continual Pre-training (CPT) to specialize the base model on the nuances of smart contract code. To construct the data for subsequent stages, we first prompt the DeepSeek model to generate reasoning-and-code samples from verified on-chain contracts, followed by a rigorous validation process where each sample is manually reviewed by security experts for compilability, functionality, security, and reasoning completeness. Based on this, we then apply Long Chain-of-Thought Supervised Fine-Tuning (L-CoT SFT) on 7,998 of these expert-validated samples to train the model to emulate human security analysis. Finally, to directly mitigate vulnerabilities, we employ Security-Aware Group Relative Policy Optimization (S-GRPO), a reinforcement learning phase that refines the generation policy using 1,691 samples by optimizing a weighted reward signal for compilation success, security compliance, and format correctness. Evaluated against 18 state-of-the-art baselines on a challenging benchmark of 756 real-world functions from 289 deployed contracts, SmartCoder-R1 establishes a new state of the art by achieving top performance across five key metrics: a ComPass of 87.70%, a VulRate of 8.60%, a SafeAval of 80.16%, a FuncRate of 53.84%, and a FullRate of 50.53%. This FullRate marks a 45.79% relative improvement over the strongest baseline, DeepSeek-R1. Crucially, its generated reasoning also excels in human evaluations, achieving high-quality ratings for Functionality (82.7%), Security (85.3%), and Clarity (90.7%).
Although the legal status of digital assets has received attention in various previous studies, research that specifically discusses the authority and responsibility of notaries in preparing inheritance certificates related to digital assets within the framework of Western inheritance law in Indonesia remains limited. This study aims to analyze the legal position of digital assets, particularly cryptocurrency and Non-Fungible Tokens (NFTs), as objects of inheritance under inheritance law in Indonesia, and to examine the authority and limits of notarial responsibility in preparing inheritance certificates related to digital assets. This study used a normative legal research method with statutory, conceptual, and analytical approaches. Primary, secondary, and tertiary legal materials were collected through library research and analyzed qualitatively, supported by interviews with notarial practitioners. The results show that digital assets with economic value can be classified as intangible movable objects based on Articles 499, 503, and 504 of the Indonesian Civil Code, and therefore may form part of an estate. However, notarial authority is limited to formal aspects, namely the verification of identity, documents, and statements of the appearers, and does not include guaranteeing access to or the transfer of digital assets, which depend on private keys and digital platform policies. Notarial responsibility is limited to formal truth, not material truth regarding the existence, ownership, or accessibility of digital assets. The conclusion of this study emphasizes the importance of comprehensive regulations and standard operating procedures for notaries in handling the inheritance of digital assets. These findings contribute to the development of notarial law in addressing technological challenges and broaden the understanding of the adaptation of inheritance law to digital assets. The implications of this study include theoretical contributions to the literature on notarial law and inheritance law, as well as practical recommendations for the Indonesian Notary Association and policymakers to formulate clear guidelines on the inheritance of digital assets.
We present SmarTrim, a new symbolic execution technique for detecting vulnerabilities in smart contracts. Smart contracts require rigorous safety validation since flaws in them can cause significant financial loss. Numerous symbolic execution techniques, which generate vulnerable transaction sequences to trigger and help understand vulnerabilities, have been extensively studied to enhance the security and safety of smart contracts. However, their performance remains unsatisfactory due to the extremely large search space for transaction sequences. To mitigate this issue, SmarTrim introduces a novel technique that safely reduces the search space by detecting and pruning redundant transaction sequences. Experimental results show that SmarTrim greatly outperforms eleven state-of-the-art analyzers in detecting critical vulnerabilities in real-world smart contracts.
Inundating networks with traffic to cripple service availability defines a DDoS attack. Traditional defences, like firewalls and centralized scrubbing centers, can suffer from single points of failure during large-scale attacks. Enter new blockchain technology, with Ethereum probably leading the way in decentralized solutions. Since Ethereum smart contracts enable DDoS detection and enforcement of validation rules, events can be managed automatically, applying rewards or penalties without a central authority. In this way it leverages the positive aspects of crypto-economic mechanisms and reputation systems; giving people an incentive to honestly participate while making abusing the system unprofitable, creating a trustless, transparent, resilient decentralized defence against cyber threats. The architecture of a blockchain-validated system that gates access to services includes a back-end gateway responsible for verifying transactions on the blockchain before processing user queries. The off-chain detection algorithm identifies unexpected traffic spikes that exceed a predefined threshold. Attackers were deterred by cost, the system itself stayed up and running, and the smart contract worked autonomously. The suggested approach maintained 96% access success for authorized users, successfully blocked 92% of DDoS traffic, and guaranteed 98% uptime during simulated attacks. All validated access attempts were 100% immutably recorded on-chain, and attackers had to pay 300% more employs transparent on-chain rules and Ethereum smart contracts to manage access. Because every access attempt is permanently documented on the blockchain, it is difficult to alter logs or stop denial-of-service attacks without detection.
The term sustainable has followed us since our school days, a word that once lived in textbooks, now echoes in daily conversations, product labels, and global forums. Sustainability often takes centre stage in discussions around climate change. As digital technology evolved, new innovations like NFTs (non-fungible tokens) sparked fresh debate. While creative in form, NFTs have also raised concerns about energy consumption and digital pollution, contributing to greenhouse gas emissions, as noted by Truby (2022). Shattered Dates is a traditional artwork that symbolically captures the fragile state of our climate. The use of bread tags, each imprinted with dates, months, and years, represents the passage of time and the layers of environmental challenges humanity has faced. The broken, colourful fragments reflect a world in crisis, one fractured by neglect, yet still filled with memory and meaning. This piece resonates deeply with the theme of SUSTAINAISSANCE, a call for a creative and conscious revival. It reminds us that we are living in a critical moment. The future depends not only on acknowledging the damage but also on reshaping the way we live, consume, and create. Through art, awareness, and innovation, we can begin to piece together a more sustainable existence before time runs out.
The article provides a scientific substantiation of conceptual proposals for shaping the architecture of a promising state air and missile defense (AMD) system based on the implementation of the Integrated Air and Missile Defense (IAMD) concept. The study addresses the urgent need to modernize existing air defense structures in response to the transformation of modern warfare. The subject of the research is the structural, organizational, and technical parameters of airspace defense systems. The topic encompasses the transition from isolated, traditional defense lines to a unified, network-centric "System of Systems". The primary purpose of the work is to develop a comprehensive theoretical model and practical guidelines for building an adaptive, multi-layered, and resilient national IAMD system capable of neutralizing current and emerging combined aerial threats. The research methodology is based on an integrated combination of several scientific approaches. The systems approach and system analysis were utilized to view the IAMD framework as a complex multi-level structure operates within a single information and communication space (including reconnaissance, command and control, engagement, and electronic warfare subsystems). The comparative-historical method was applied to analyze the evolution of AMD concepts and the practical experience of deploying defense tools during the full-scale Russian-Ukrainian war. The generalization method enabled a transition from assessing specific technical parameters of various weapons to formulating a holistic integration model. Military-strategic forecasting was used to identify global trends in aerial attack technologies. Additionally, Open-Source Intelligence (OSINT) methodologies were applied to gather empirical data on enemy tactics, strike consequences, and techno-tactical trends. The study provides a rigorous terminological analysis and establishes a unified conceptual apparatus detailing the operational logic of modern airspace defense. Key operational-tactical and technical requirements for the IAMD infrastructure have been formalized. The paper introduces the concept of an "Open IAMD Architecture", which relies on standardized APIs, unified protocols, and a centralized national software Command and Control (C2) core scalable from the battalion to the national level. The integration of the "Any Sensor, Best Shooter" principle is defined as a primary mechanism to merge diverse sensors, fire units, and hybrid systems (such as FrankenSAM) into a singular combat field. Furthermore, the study formalizes the necessity of shifting toward quantitative Key Performance Indicators (KPIs) and implementing Decision Support Systems (DSS) combined with regional digital twins for advanced scenario modeling. The authors conclude that the proposed theoretical framework successfully shifts the focus of airspace defense from passive monitoring to dynamic, high-precision threat liquidation. The system must maintain decentralized resilience, allowing individual air defense cells to operate autonomously even during network disruptions. The scope of application for these results includes military command and control bodies, defense industry planning agencies, state bodies responsible for critical infrastructure protection, and academic institutions engaged in designing promising military hardware, simulation environments, and strategic defense doctrines.
Ігор Григорійович Дзеверін, Володимир Валерійович Коваль, Борис Степанович Москалик
The article provides a scientific substantiation of conceptual proposals for shaping the architecture of a promising state air and missile defense (AMD) system based on the implementation of the Integrated Air and Missile Defense (IAMD) concept. The study addresses the urgent need to modernize existing air defense structures in response to the transformation of modern warfare. The subject of the research is the structural, organizational, and technical parameters of airspace defense systems. The topic encompasses the transition from isolated, traditional defense lines to a unified, network-centric "System of Systems". The primary purpose of the work is to develop a comprehensive theoretical model and practical guidelines for building an adaptive, multi-layered, and resilient national IAMD system capable of neutralizing current and emerging combined aerial threats. The research methodology is based on an integrated combination of several scientific approaches. The systems approach and system analysis were utilized to view the IAMD framework as a complex multi-level structure operates within a single information and communication space (including reconnaissance, command and control, engagement, and electronic warfare subsystems). The comparative-historical method was applied to analyze the evolution of AMD concepts and the practical experience of deploying defense tools during the full-scale Russian-Ukrainian war. The generalization method enabled a transition from assessing specific technical parameters of various weapons to formulating a holistic integration model. Military-strategic forecasting was used to identify global trends in aerial attack technologies. Additionally, Open-Source Intelligence (OSINT) methodologies were applied to gather empirical data on enemy tactics, strike consequences, and techno-tactical trends. The study provides a rigorous terminological analysis and establishes a unified conceptual apparatus detailing the operational logic of modern airspace defense. Key operational-tactical and technical requirements for the IAMD infrastructure have been formalized. The paper introduces the concept of an "Open IAMD Architecture", which relies on standardized APIs, unified protocols, and a centralized national software Command and Control (C2) core scalable from the battalion to the national level. The integration of the "Any Sensor, Best Shooter" principle is defined as a primary mechanism to merge diverse sensors, fire units, and hybrid systems (such as FrankenSAM) into a singular combat field. Furthermore, the study formalizes the necessity of shifting toward quantitative Key Performance Indicators (KPIs) and implementing Decision Support Systems (DSS) combined with regional digital twins for advanced scenario modeling. The authors conclude that the proposed theoretical framework successfully shifts the focus of airspace defense from passive monitoring to dynamic, high-precision threat liquidation. The system must maintain decentralized resilience, allowing individual air defense cells to operate autonomously even during network disruptions. The scope of application for these results includes military command and control bodies, defense industry planning agencies, state bodies responsible for critical infrastructure protection, and academic institutions engaged in designing promising military hardware, simulation environments, and strategic defense doctrines.
The growth of the usage of decentralized applications on Ethereum has seen the rise of an increasing number of bad actors that are using it to commit fraud, phishing, money laundering and financial scams. Traditional detection methods are less effective to detect accounts with more complex and changing behaviours. The paper suggests a novel multi-level framework for detecting malicious Ethereum accounts based on supervised classification and adaptive anomalous account verification using a routing based on probabilities. To get the transaction behavior features, opcode features and time-interval features from the publicly available EtherShield data set, we use the entire data set to extract the entire features. The first is a Level-1 where an XGBoost machine learning model classifies Ethereum accounts into Fair, Likely Malicious and Malicious categories, and outputs calibrated probability scores for any account. Uncertainty about malicious accounts are escalated to level-2 where anomaly verification and behavioural re-assessment are carried out by using models such as Random Forest and Isolation Forest. The final classification is obtained by decision fusion process, which combines the results obtained from both levels. The Random Forest-based verification module is evaluated in the experiments and is found to be 95% accurate, 94% macro precision, 95% macro recall and 95% macro F1-score, which is significantly better than the Isolation Forest (baseline). Besides, stratified 5-Fold Cross Validation further demonstrates that the proposed framework is robust and generalizable with a mean accuracy of 94.96% ± 0.43, mean precision of 94.40% ± 0.42, mean recall of 94.84% ± 0.47 and mean F1-Score of 94.66% ± 0.42. The proposed framework proves to be an effective solution to minimize misclassification, enhance the reliability of detection and offer a scalable answer to safeguard Ethereum blockchain ecosystems from newly emerged malicious activities.
Synchronization and swarming are canonical manifestations of self-organization, observable across scales from cellular processes to animal flocks. This study investigates the collective dynamics of a novel agent-based model where individuals exhibit both spatial mobility and internal, two-mode stochastic oscillatory states. By introducing a local, distance-dependent coupling between the agents' spatial configuration and their internal state transitions, we establish a mutual feedback loop that drives complex pattern formation. Through large-scale numerical simulations, we identify seven distinct morphological configurations, ranging from stationary \textit{Filled-disk} states to highly disordered \textit{Intense-motion} regimes. By performing a rigorous quantitative analysis of the rotational energy and radial dispersion, we transcend simple morphological classification and demonstrate that the system organizes into discrete, quantized topological attractors. We derive a macroscopic scaling law, $Ω\propto r^{-1/2}$, which proves that the emerging rotating states are not rigid-body rotations, but rather composite differential vortex structures characterized by spontaneous chiral symmetry breaking. Our results suggest that these stable, quantized dynamical states are fundamental features of systems governed by bidirectional spatial-phase feedback, offering a robust framework for designing autonomous, decentralized robotic swarms.
Since the 1980s, decentralization has improved local development adaption in a number of sub-Saharan African nations. However, in recent decades, this approach of autonomous local administration has encountered challenges, such as a decline in funding. However, Côte d'Ivoire's Law No. 2003-208 of July 7, 2003, on the transfer and distribution of state competencies to local authorities, permits local elected officials to mobilise funds locally by establishing revenue-generating ventures in a number of industries, including tourism. How can local tourism support local development in Côte d'Ivoire's decentralized villages given the country's diminishing financial resources? The goal is to demonstrate how local tourist marketing may serve as a lever for funding local development in the dynamic of enhancing living standards. 200 household heads in neighbourhoods chosen by reasoned choice participated in a questionnaire survey, field observation, direct and semi-direct interviews, and documentary research as part of an empirical method. The municipality of Seguela seems to be brimming with a variety of tourism opportunities. To highlight these potentialities, local officials have undertaken to boost local tourism through the opening of roads, the improvement of potable water supply and electrification, the creation of public spaces for tourist attraction, the cleaning of gutters and street sweeping, and especially the establishment of the "Worodougou Lôgôba" festival, etc. These municipal investments have resulted in: the commercialisation of agricultural products and local cultural craftworks, the emergence of various means of mobility, the attraction of customers to restaurants, maquis, and hotels; thus creating direct and indirect jobs. Due to the increased foreign cash earned by tourist taxes, this has made it easier to optimise local budgetary resources.
Mingxi Ye, Yuhong Nan, Zhijie Zhong, Jianzhong Su · 7 authors
Given the critical nature of Ethereum, exploiting 1-day vulnerabilities that are patched but not yet widely deployed is essential. Meanwhile, Automatic Patch-based Exploit Generation (APEG) is a promising technique for this, as it helps developers understand root causes, verify fixes in downstream forks, and detect incomplete patches. However, existing exploit generation tools can not work well for vulnerabilities on Ethereum due to three key unique challenges: (1) navigating complex and cross-language exploit paths hidden within patches, (2) synthesizing complicated and stateful environment configurations, and (3) handling non-deterministic inconsistencies between blockchain nodes that lead to false alarms. To address these challenges, we introduce ChainDelta , a novel fuzzing agent framework driven by Large Language Models to automatically generate exploits based on Ethereum security patches. ChainDelta consists of three core modules: a directed fuzzer utilizes call graph analysis to guide testing towards vulnerable code based on the patch information; an agent-based environment fuzzer acts as an expert to automatically set up the necessary blockchain states to trigger vulnerabilities; and finally, a state-aware sanitizer performs differential analysis while monitoring the blockchain transient state to distinguish true inconsistencies from benign non-determinism. We evaluate ChainDelta on a diverse benchmark with real-world patches, covering a wide range of types such as data racing and denial-of-service. ChainDelta successfully generated exploits with a 64% success rate and only a 15.8% false positive rate. An ablation study confirms the contribution of each module to the overall performance. To demonstrate its practical impacts, we conducted a real-world auditing campaign on top of ChainDelta , leading to the discovery of four previously undisclosed vulnerabilities with bug bounties.
Purpose: The rapid evolution of spatial computing has initiated a paradigm shift from traditional, two-dimensional e-commerce to immersive, three-dimensional virtual commerce (v-commerce). This paper conceptualizes the foundational drivers, structural mechanics, and strategic implications of consumer behavior within the emerging metaverse marketplace.Methodology/Approach: Synthesizing Social Presence Theory and the Technology Acceptance Model (TAM), this study provides a comprehensive conceptual framework analyzing how multi-sensory immersion, avatar-mediated identity expression, and decentralized economic frameworks alter consumer decision-making. Findings: The paper establishes that the metaverse fundamentally redefines digital consumer behavior by transforming standard transactions into identity-driven social expressions. It outlines how immersive experiential marketing stimuli (e.g., gamified storefronts, virtual try-ons) drive high emotional arousal and hedonic consumption patterns. Furthermore, the analysis maps the collapse of the traditional boundary between buyers and sellers via Play-to-Earn (P2E) and Create-to-Earn (C2E) models, re-contextualizing virtual consumers as active entrepreneurial producers within blockchain-secured economies. Research Implications: While presenting a robust conceptual blueprint for v-commerce engagement, the study highlights critical consumer inhibitors, including biometric data harvesting risks, infrastructural access barriers, and psychological virtual fatigue. Originality: This paper bridges the gap between conventional digital marketing theories and spatial mechanics. It provides actionable strategic imperatives for contemporary brands specifically detailing hybrid "phygital" retail systems, spatial analytics optimization, and community-centric governance via Decentralized Autonomous Organizations (DAOs) to effectively future-proof enterprise models.
Andika Pratama, Dewi Nur Lestari, Bambang Hartono, Sri Wahyuni · 5 authors
Modern bioinformatics has entered a multi-omics era in which genomic, transcriptomic, proteomic, and metabolomic datasets accumulate at unprecedented velocity, volume, and variety. Conventional centralized governance — institutional databases protected by role-based access control — struggles with single points of failure, opaque consent enforcement, weak provenance, and brittle interoperability across jurisdictions. Blockchain technology has been proposed as an alternative substrate for trustworthy multi-omics data sharing, but the literature remains fragmented across isolated mechanisms (immutability, smart contracts, on-chain storage) without a coherent system view. This article systematically reviews 82 peer-reviewed studies published between 2017 and 2025, indexed in Scopus, IEEE Xplore, ScienceDirect, SpringerLink, and the ACM Digital Library, using a five-stage screening protocol and a five-question quality assessment rubric. Building on the synthesis, we propose a six-layer architectural framework that combines a permissioned blockchain ledger, smart-contract-based consent and access control, privacy-preserving cryptography (zero-knowledge proofs, homomorphic encryption, differential privacy), decentralized identity, off-chain storage on the InterPlanetary File System, and native interoperability with HL7 FHIR-compliant electronic health records. A multi-criterion comparison shows that Practical Byzantine Fault Tolerance is best suited to the latency, throughput, and energy constraints of multi-omics workflows, outperforming Proof-of-Work and Proof-of-Stake on five of six evaluation dimensions. Compared with traditional security baselines, blockchain delivers measurable advantages in tamper-resistance, provenance, and patient-centric consent, but does not universally dominate on confidentiality and scalability. The framework offers a practical roadmap for big-data governance in life-science research while highlighting open problems in standardization, regulatory alignment, and energy efficiency.