Blockchain Papers

Xin Dong, Yong Yuan

No abstract is available for this record.

Agnes Nalini Vincent, Nassirah Laloo, Mohammad Sameer Sunhaloo, Uhoze Bagurubumwe

Digital elevation model (DEM)-based terrain analysis is an important geographic information system (GIS) methodology that serves as the core aspect for spatial analysis applications in geomorphological studies. These analyses can be performed using cloud-based platforms like Google Earth Engines or ArcGIS online, or using a local GIS platform called quantum GIS (QGIS). The resulting terrain data must be disseminated. Geospatial data sharing and dissemination are crucial for promoting cooperation, effectiveness, efficiency, and optimized decision-making in a variety of industries. Geospatial terrain data plays a crucial role in site selection and industrial planning, automated logistics, autonomous vehicle navigation, and infrastructure resilience in manufacturing ecosystems. However, existing literature states that traditional systems lack mechanisms to detect tampering in elevation models, land surveys, or hydrological data. Because of this, manufacturing systems face risks such as flawed factory site selection, disrupted supply routes, or unsafe autonomous vehicle navigation, data tampering in production logs, 278 counterfeit parts in supply chains, and a lack of real-time traceability. Hence, to manage the limitations of conventional terrain data storage and handling, this study proposes a blockchain-based framework to secure QGIS-processed terrain data, ensuring immutability and traceability for smart manufacturing applications. Blockchain distributed ledgers can permanently store high-resolution terrain data, minimize the chance of unintended alterations, and promote transparent, unrestricted collaboration. Using the country of the Republic of Mauritius as a case study toward tropical island states, this work demonstrated how elevation, slope, and aspect data extracted via QGIS can be securely stored and verified on a distributed ledger. Furthermore, this study incorporates an integration layer into the framework. The purpose of this integration layer is to enable real-time terrain alerts, smart contract-driven compliance checks, and to arrive at closed-loop feedback from IoT sensors. Thus, this proposed framework bridges blockchain-secured terrain data with manufacturing execution systems (MES) and IoT-enabled logistics networks.

Jiale Li, Leixiao Li, Hao Lin, Jinze Du

No abstract is available for this record.

Xuan Luo, Ye Lin, Huanchun Wei, Yuyu Zhong · 9 authors

No abstract is available for this record.

Shilpa Bhatia, Ramesh Chandra Sahoo, Arvind Kumar

Cloud computing infrastructures are facing serious risks from Distributed-Denial-of Service attacks, which include historically high attack volumes and ineffectiveness of conventional defensive strategies. The usefulness of blockchain based security measures in detecting and preventing DDoS attacks on cloud computing infrastructure is covered in this paper. Analyzed a hybrid approach that integrated distributed ledger technology with smart contracts for the identification of attack patterns across 50 enterprise cloud environments over a period of 18 months. Our results show a reduction of false positives by as much as 87% for blockchain-based validation compared to the conventional approach and a 94% success rate in the detection of advanced DDoS variants. The response time remained, on average, around 2.3 seconds during the high-volume attack in comparison to traditional centralized solutions. The results in the paper gives an idea that an immutable and distributed consensus characteristic based on blockchain provides robust defenses against modern DDoS threats. This work represents a growing body of evidence supporting the validity of incorporating blockchain into the architecture of the next generation of cloud-based security.

Bhoyi Gautami Ravi, Bhoomika K, Chandana R, Hruthishree R · 6 authors

Abstract - The rise of digital technology has led to an increase in cybercrime. This has made the management of digital forensic evidence more complicated. Traditional evidence management systems utilize manual methods and centralized databases. Methods like these are vulnerable to data tampering, unauthorized access, and human error. These issues threaten the integrity of the evidence and the chain of custody during the investigation process. In this paper, we introduce a system that utilizes blockchain technology, smart contracts, and a decentralized system for the tracking of forensic evidence. Security and transparency will be guaranteed. In our system, evidence records are stored as ERC-721 Non-Fungible Tokens. A private Ethereum blockchain was developed using Ganache and combined with wallet-based authentication and Role-Based Access Control to ensure that only authorized personnel have the ability to view and manage evidence. Smart contracts facilitate the registration, verification, transfer, and auditing of evidence, thus, considerably reducing the manual work and greatly increasing the trustworthiness of the system. We proposed a hybrid system of storage whereby evidence and its forensic files are stored off chain, and the evidence metadata and its forensic files are stored on chain. This paper presents the design and architecture of the system,implementation and evaluation are in progress.Our system will be a trusted, efficient, and effective system of evidence management.

Bruno Debaenst

No abstract is available for this record.

Adam Zahir, Vincent Lefebvre, Mark Angoustures, Milan Groshev · 5 authors

Multi-agent systems (MAS) comprise autonomous software agents that collaborate to perform complex tasks in critical cyber-physical domains, including multi-robot coordination and the Industrial Internet of Things (IIoT). In such distributed environments, a compromised agent may execute modified software while appearing trustworthy, causing other agents to act on false information and corrupting the mission. Agents must therefore establish and maintain mutual trust throughout operation. Remote attestation (RA) is a well-established technique for this purpose, enabling a remote verifier to assess the integrity of a potentially compromised prover device. However, conventional RA approaches face significant limitations in MAS: integrity guarantees are restricted to boot or application-load time, designs rely on centralized trusted verifiers or security hardware, and attestation records lack transparency and auditability. To address these limitations, this paper presents D-MUTRA, a blockchain-based framework that introduces a mutual RA protocol in which agents measure their runtime integrity while verifying that of their peers, acting as both prover and verifier. The framework operates entirely in software and relies on two components: a Security-as-a-Service that instruments agents with lightweight measurement and verification capabilities, and a smart contract that coordinates the attestation protocol in a decentralized and transparent manner. We implement a proof-of-concept on a private Ethereum blockchain using Hyperledger Besu and evaluate it in a swarm robotics scenario built with Robot Operating System (ROS) and the Gazebo simulator. Results show that D-MUTRA enables agents to continuously attest one another, detects malicious software modifications, and scales to large deployments with negligible overhead on protected applications.

Jinyin Song, Hongping Wang, Xiaoqi Li

As the blockchain and decentralized finance (DeFi) ecosystems continue to expand and mature, rug pull scams involving meme coins are occurring with increasing frequency, posing a threat to the security of investors' assets and the healthy development of the industry. Rug Pull scams are characterized by extremely low deployment costs, covert execution, rapid fund transfers, and high detection difficulty. Traditional manual reviews or fixed rules struggle to meet real-time early warning requirements, and existing detection methods generally suffer from issues such as a single feature dimension, inadequate handling of class imbalance, and weak model generalization and interpretability. To address these shortcomings, this paper focuses on the detection of Ethereum-based rug pull scams. First, we clarify their definitions, types, and harm mechanisms, and construct a multi-dimensional feature system based on dimensions such as malicious smart contract design, on-chain transaction anomalies, liquidity manipulation, and social media disclosures. Next, using the "Second Uncle Coin"(token symbol: BOBU) case as an example, we reconstruct the attack process and derive quantitative detection metrics. Subsequently, a risk detection model based on a Multi-Layer Perceptron (MLP) is designed. We employ a combined strategy of SMOTE oversampling and Focal Loss to address the issue of sample imbalance, dynamically search for optimal thresholds to balance precision and recall, and incorporate gradient pruning and early stopping to enhance training stability. Experiments show that the model achieves an accuracy of 0.927, an F1 score of 0.787, and an AUC-ROC of 0.952 on the test set, outperforming traditional methods. Finally, a visualizable web-based detection system is developed using the Flask framework, enabling batch risk assessment, high-risk ranking display, and result export functions.

Juan Li, Wei Cai, Yan Bai

Autonomous AI agents, increasingly empowered by large language models, are becoming important components of human-machine systems for high-stakes decision support in digital twin ecosystems. However, existing multi-agent systems often lack robust verification for identity, capability, and policy compliance, especially in decentralized environments spanning multiple institutions. This paper proposes a neuro-symbolic decentralized governance framework for verifiable agents in collaborative digital twin environments. By representing agents through multi-layer semantic profiles, the framework bridges probabilistic neural reasoning with deterministic institutional governance, thereby supporting trustworthy human-AI collaboration and meaningful human oversight. Capabilities are grounded in formal domain ontologies to enable machine-interpretable, policy-aware, and context-sensitive participation. These credentials, issued by organizational authorities, are validated via blockchain-based smart contracts, ensuring auditable participation without exposing sensitive data. We demonstrate the framework using a decision-support prototype with clinic, digital twin, and wearable provider agents effectively prevents unauthorized interaction and enforces institutional policies with manageable overhead. Our findings suggest that neuro-symbolic decentralized governance provides a scalable and trustworthy pathway for safe human-machine collaboration across institutional boundaries.

Sabbir Ahmed, Mohammad Shahadat Hossain, Latifur Khan

No abstract is available for this record.

Rashmi D M Rashmi D M

No abstract is available for this record.

Vinay G T Vinay G T

No abstract is available for this record.

Zhifan Ye, Jiachi Chen, Zhongxin Liu, Chong Chen · 8 authors

Solidity has undergone 116 version iterations between August 2015 and February 2026, during which compiler updates have introduced behavioral changes, including issues later fixed in subsequent releases. Contracts compiled under specific versions may exhibit version-dependent execution behaviors, particularly in low-level code. These differences are often difficult for developers and users to recognize, creating opportunities for adversaries to exploit legacy compiler behaviors and deploy contracts with potentially deceptive outcomes. We define this issue as the Compiler Version Discrepancy (CVD) risk , where attackers leverage compiler-version-dependent behaviors to produce misleading or unfair outcomes while contracts appear functionally benign. We summarize five representative CVD risk patterns from real compiler inconsistencies. To mitigate this risk, we develop the CompileGuard detection tool. It combines Abstract Syntax Tree (AST) analysis, taint analysis, and symbolic execution with Control Flow Graph (CFG) analysis to identify version-sensitive code patterns. Evaluation on 227 smart contracts shows CompileGuard achieves an overall F1 score of 95.22%. A user study with 21 blockchain practitioners shows contracts exploiting CVD risks can mislead users, while detection reports enable all participants to correctly identify risk-inducing behaviors. These results highlight the practical exploitability of CVD risks and the effectiveness of automated detection in preventing such deception.

Inge Grondman, Valerie A. C. M. Koeken, Tristan Couwenbergh, Athanasios Karageorgos · 13 authors

Abstract Background Sepsis is a highly heterogeneous syndrome characterized by variable immune dysregulation states, including hyperinflammation and immunosuppression. Previous immunotherapy attempts in sepsis have largely failed, likely due to a “one-size-fits-all” approach that ignores each patient’s immune status. The recent ImmunoSep randomized clinical trial demonstrated that precision immunotherapy guided by the presence of either macrophage activation–like syndrome (MALS) or immune paralysis can improve early organ dysfunction in sepsis patients. However, the molecular mechanisms underlying these immune endotypes remain unclear. Objectives To identify the immunological signatures that distinguish MALS and immune paralysis. Methods We used single-cell RNA sequencing to profile circulating leukocytes of 6 healthy controls and 16 sepsis patients classified as MALS, immune paralysis or unclassified (when criteria for neither of these two immune endotypes were applicable). Classification was based on surrogate biomarkers ferritin and HLA-DR expression on monocytes. Thereafter, the transcriptional programs of these groups were compared. Results Pronounced differences were detected mainly in the transcriptional signature of monocytes from these patients, with a clear distinction between MALS and immune paralysis. Unsupervised clustering analysis revealed the existence of MALS-specific monocyte clusters, as well as one sepsis-specific monocyte cluster that was linked to greater comorbidity burden and may reflect increased clinical vulnerability in sepsis. These findings were validated in two independent cohorts, in which urosepsis was characterized by heterogeneous MALS and immune paralysis monocyte signatures. Moreover, MALS-specific monocyte clusters showed overlapping transcriptional signatures with severe COVID-19. Conclusions Our findings shed light on the heterogeneous immune landscape underlying sepsis and provide opportunities for patient stratification for future therapeutic development.

Shiqiang Chen

First systematic security study of the AI Agent x DeFi intersection. Contributions: (1) Five-layer attack surface model (user input, LLM reasoning, MCP tool layer, smart contracts, blockchain state); (2) 8-vector attack taxonomy (V1-V8) with 3 unique properties (Interpretation Gap, Automation Surface, Memory Persistence); (3) Empirical validation through audit of 5 protocols (108 contracts), finding 13 vulnerabilities across 7/8 vectors; (4) Three-level defense framework (protocol, agent, infrastructure). Includes Foundry-based attack sandbox.

P.Rupasri, Marka Sandhya

The increasing adoption of blockchain technology has transformed digital transaction systems by providing secure, decentralized, and transparent data management. The vehicle procurement process, however, still relies heavily on conventional procedures involving multiple intermediaries, manual documentation, and lengthy verification mechanisms that often increase operational costs and expose transactions to fraudulent activities. This paper presents a blockchain-enabled smart vehicle procurement framework that modernizes the complete purchasing lifecycle while preserving transaction integrity and user trust. The proposed system utilizes blockchain technology as an immutable distributed ledger for securely storing vehicle records, ownership history, buyer credentials, and transaction information. Smart contracts are employed to automate critical activities including buyer verification, ownership transfer, payment authorization, and regulatory validation without requiring manual intervention. The decentralized architecture minimizes dependency on third-party agencies while improving transparency, reducing processing delays, and enhancing security against data manipulation. Since every transaction is permanently recorded on the blockchain, both buyers and sellers can independently verify the authenticity of vehicle records before completing a purchase. The proposed framework maintains the same operational workflow and implementation strategy as the reference system while offering improved documentation quality and technical presentation. Experimental observations demonstrate that blockchain-assisted procurement significantly improves transaction efficiency, strengthens security, simplifies ownership transfer, and establishes a reliable digital marketplace for modern automotive commerce. The framework represents a scalable solution capable of supporting future intelligent transportation systems and smart mobility applications.

Xin Xu, Zhen Yang, Quanwei Cai, Jingqiang Lin · 7 authors

Version control systems (VCS), including central VCS (CVCS) and distributed VCS (DVCS), are widely adopted to manage changes to software code and various types of documents. Unlike CVCS, where entities obtain data from a central server, each entity in DVCS stores the entire repository and shares it independently. In VCS, existing access control schemes require the participation of a central server and cannot be deployed in a completely distributed scenario. Additionally, these schemes often fail to enforce fine-grained access control for write permissions, which is crucial for collaborative work in a distributed environment. In this paper, we propose a distributed version control system access control scheme (named DVAC), which enforces cryptographic access control on distributed user nodes based on attribute-based encryption (ABE) and attribute-based signature (ABS). DVAC is designed to enforce a cryptographic access control protocol for DVCS, which enables file granularity read and write separation access control without the support of a central server. To ensure the integrity of the core version control functions in DVCS while protecting data security, DVAC incorporates a version control adaptation protocol. Additionally, DVAC leverages Ethereum smart contracts to maintain access control policies, ensuring distributed storage and trusted management of access policies. The architecture of DVAC is designed to seamlessly integrate with existing mature DVCS, such as Git, with minimal modifications. We have implemented a prototype of DVAC and integrated it with Git. A comprehensive performance evaluation was conducted to assess the overhead introduced by DVAC, and it was demonstrated that the overhead is modest.

Hung Tan Nguyen, Anh-Kiet Ly-Ngo

The construction sector is increasingly exploring smart contracts (SCs) to resolve persistent operational challenges, such as payment delays and disputes. This study systematically analyzes SC and Distributed Ledger Technology (DLT) deployments globally and in Vietnam, identifying key legal, technical, and organizational constraints hindering domestic adoption. To bridge these gaps, a five-step implementation framework tailored to Vietnam's institutional and market conditions is proposed. The framework emphasizes incremental adaptation using regulatory sandboxes, a hybrid architecture integrated with Building Information Modeling (BIM), and fiat-based payment mechanisms. The findings highlight that successful adoption depends primarily on institutional readiness and regulatory alignment rather than the technology itself, advocating a phased approach aligned with local industry capabilities.

Md Mehedi Hasan Emon, Ratul Islam

This chapter explores the transformative role of Financial Technology (FinTech) in advancing green finance, a crucial component in addressing global sustainability challenges. By integrating technologies such as blockchain, artificial intelligence (AI), big data analytics, and smart contracts, FinTech facilitates the efficient allocation of capital towards sustainable projects. The chapter examines how these innovations enhance transparency, optimize risk assessment, and enable decentralized financing models like peer-to-peer energy trading and tokenization. Additionally, it addresses the challenges posed by greenwashing, market volatility, and regulatory uncertainty, while highlighting the future opportunities for growth in green finance. Ultimately, the chapter underscores the potential of FinTech to drive systemic change and promote a low-carbon, sustainable economy.

Md Mehedi Hasan Emon, Ratul Islam

This chapter explores the transformative potential of blockchain and artificial intelligence (AI) in revolutionizing green finance. It begins by examining the role of digital transformation in driving sustainable financial practices, highlighting the integration of blockchain and AI. The chapter delves into blockchain's applications in enhancing transparency, traceability, and security within green finance, particularly through smart contracts and decentralized finance solutions. It further discusses AI's contributions to improving risk assessment, ESG evaluation, and combating greenwashing. The synergies between blockchain and AI are explored, showing how their combined use optimizes sustainability-focused investments. Additionally, the chapter addresses regulatory and ethical considerations surrounding these technologies. Finally, it discusses emerging trends and opportunities in green finance, providing insights into the future of sustainable financial systems driven by technological innovation.

Famira Racy

Contract Role: Software Developer PKP is seeking a mid-career or senior software developer to join the software development team in coding the future of PKP's software applications, particularly Open Journal Systems (OJS), Open Monograph Press (OMP), and Open Preprint Systems (OPS). These applications are written in PHP and VueJS. There will be many opportunities for related work such as

Oscar M. Bedoya, Jeferson Arango‐López, Jorge Hochstetter

The management of intellectual property (IP) agreements in universities continues to rely on static legal documents that are signed, archived, and consulted when necessary, but whose content is rarely formalized to facilitate their operation and verification. Consequently, obligations, permissions, restrictions, deadlines, scopes, and exceptions often remain scattered across clauses drafted in natural language, annexes, emails, and different document versions, which hinders their monitoring and makes compliance review dependent on intensive legal and administrative work. In response to this limitation, this article proposes an ontology to formalize non-disclosure agreements (NDAs) at the University of Caldas, Colombia, understood as a specific case within the broader management of IP agreements. The proposal adopts a modular Semantic Web architecture composed of a reusable ontological core and a specialized profile for NDAs. Its construction followed the METHONTOLOGY methodology, and its specification was supported by Competency Questions (CQs), which were subsequently translated into SHACL constraints and SPARQL queries. In addition, a SKOS vocabulary is incorporated to normalize synonyms and terminological variants typical of legal drafting in Spanish, together with a lightweight weak supervision layer based on regular expressions, SKOS, and structural signals to support clause labeling and the batch generation of RDF instances. Thus, the proposal enables querying, traceability, and verification over NDA content, while offering a formal basis for progressing toward automatable controls and their eventual articulation with smart contracts.

Nattawat Songsom

No abstract is available for this record.