自主智能系统(英文) Pub Date : 2024-09-18 DOI: 10.1007/s43684-024-00075-9

Gang Huang, Liangzhu Lu, Yifan Zhang, Gangfu Cao, Zhe Zhou

引用次数: 0

Numerical simulations of a two-strain dengue model to investigate the efficacy of the deployment of Wolbachia-carrying mosquitoes and vaccination for reducing the incidence of dengue infections 对双菌株登革热模型进行数值模拟，研究部署携带沃尔巴克氏体的蚊子和接种疫苗对降低登革热感染率的功效

Journal of Biosafety and Biosecurity Pub Date : 2024-09-05 DOI: 10.1016/j.jobb.2024.08.003

Meksianis Z. Ndii , Nursanti Anggriani , Bertha S. Djahi , Sanubari Tansah Tresna , Fatuh Inayaturohmat

引用次数: 0

A stochastic epidemic model with time delays and unreported cases based on Markovian switching 基于马尔可夫转换的具有时间延迟和未报告病例的随机流行病模型

Journal of Biosafety and Biosecurity Pub Date : 2024-09-05 DOI: 10.1016/j.jobb.2024.08.002

H.J. Alsakaji , Y.A. El-Khatib , F.A. Rihan (PhD; DSc) , A. Hashish

引用次数: 0

Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT 基于双区块链的工业物联网异构数据多层分组联合学习方案

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100195

{"title":"Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT","authors":"","doi":"10.1016/j.bcra.2024.100195","DOIUrl":"10.1016/j.bcra.2024.100195","url":null,"abstract":"<div><p>Federated learning (FL) allows data owners to train neural networks together without sharing local data, allowing the industrial Internet of Things (IIoT) to share a variety of data. However, traditional FL frameworks suffer from data heterogeneity and outdated models. To address these issues, this paper proposes a dual-blockchain based multi-layer grouping federated learning (BMFL) architecture. BMFL divides the participant groups based on the training tasks, then realizes the model training by combining synchronous and asynchronous FL through the multi-layer grouping structure, and uses the model blockchain to record the characteristic tags of the global model, allowing group-manners to extract the model based on the feature requirements and solving the problem of data heterogeneity. In addition, to protect the privacy of the model gradient parameters and manage the key, the global model is stored in ciphertext, and the chameleon hash algorithm is used to perform the modification and management of the encrypted key on the key blockchain while keeping the block header hash unchanged. Finally, we evaluate the performance of BMFL on different public datasets and verify the practicality of the scheme with real fault datasets. The experimental results show that the proposed BMFL exhibits more stable and accurate convergence behavior than the classic FL algorithm, and the key revocation overhead time is reasonable.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100195"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000083/pdfft?md5=17c58876f9db0cb915d1b0b20cbe64c3&pid=1-s2.0-S2096720924000083-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140468200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An interpretable model for large-scale smart contract vulnerability detection 大规模智能合约漏洞检测的可解释模型

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100209

{"title":"An interpretable model for large-scale smart contract vulnerability detection","authors":"","doi":"10.1016/j.bcra.2024.100209","DOIUrl":"10.1016/j.bcra.2024.100209","url":null,"abstract":"<div><div>Smart contracts hold billions of dollars in digital currency, and their security vulnerabilities have drawn a lot of attention in recent years. Traditional methods for detecting smart contract vulnerabilities rely primarily on symbol execution, which makes them time-consuming with high false positive rates. Recently, deep learning approaches have alleviated these issues but still face several major limitations, such as lack of interpretability and susceptibility to evasion techniques. In this paper, we propose a feature selection method for uplifting modeling. The fundamental concept of this method is a feature selection algorithm, utilizing interpretation outcomes to select critical features, thereby reducing the scales of features. The learning process could be accelerated significantly because of the reduction of the feature size. The experiment shows that our proposed model performs well in six types of vulnerability detection. The accuracy of each type is higher than 93% and the average detection time of each smart contract is less than 1 ms. Notably, through our proposed feature selection algorithm, the training time of each type of vulnerability is reduced by nearly 80% compared with that of its original.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100209"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141390225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis 利用机器学习分类器和可解释性分析检测区块链交易中的异常情况

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100207

Mohammad Hasan , Mohammad Shahriar Rahman , Helge Janicke , Iqbal H. Sarker

{"title":"Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis","authors":"Mohammad Hasan , Mohammad Shahriar Rahman , Helge Janicke , Iqbal H. Sarker","doi":"10.1016/j.bcra.2024.100207","DOIUrl":"10.1016/j.bcra.2024.100207","url":null,"abstract":"<div><div>As the use of blockchain for digital payments continues to rise, it becomes susceptible to various malicious attacks. Successfully detecting anomalies within blockchain transactions is essential for bolstering trust in digital payments. However, the task of anomaly detection in blockchain transaction data is challenging due to the infrequent occurrence of illicit transactions. Although several studies have been conducted in the field, a limitation persists: the lack of explanations for the model's predictions. This study seeks to overcome this limitation by integrating explainable artificial intelligence (XAI) techniques and anomaly rules into tree-based ensemble classifiers for detecting anomalous Bitcoin transactions. The shapley additive explanation (SHAP) method is employed to measure the contribution of each feature, and it is compatible with ensemble models. Moreover, we present rules for interpreting whether a Bitcoin transaction is anomalous or not. Additionally, we introduce an under-sampling algorithm named XGBCLUS, designed to balance anomalous and non-anomalous transaction data. This algorithm is compared against other commonly used under-sampling and over-sampling techniques. Finally, the outcomes of various tree-based single classifiers are compared with those of stacking and voting ensemble classifiers. Our experimental results demonstrate that: (i) XGBCLUS enhances true positive rate (TPR) and receiver operating characteristic-area under curve (ROC-AUC) scores compared to state-of-the-art under-sampling and over-sampling techniques, and (ii) our proposed ensemble classifiers outperform traditional single tree-based machine learning classifiers in terms of accuracy, TPR, and false positive rate (FPR) scores.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100207"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How can the holder trust the verifier? A CP-ABPRE-based solution to control the access to claims in a Self-Sovereign-Identity scenario 持有人如何信任验证者？一种基于 CP-ABPRE 的解决方案，用于控制自我主权身份情况下对权利主张的访问

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100196

{"title":"How can the holder trust the verifier? A CP-ABPRE-based solution to control the access to claims in a Self-Sovereign-Identity scenario","authors":"","doi":"10.1016/j.bcra.2024.100196","DOIUrl":"10.1016/j.bcra.2024.100196","url":null,"abstract":"<div><p>The interest in Self-Sovereign Identity (SSI) in research, industry, and governments is rapidly increasing. SSI is a paradigm where users hold their identity and credentials issued by authorized entities. SSI is revolutionizing the concept of digital identity and enabling the definition of a trust framework wherein a service provider (verifier) validates the claims presented by a user (holder) for accessing services. However, current SSI solutions primarily focus on the presentation and verification of claims, overlooking a dual aspect: ensuring that the verifier is authorized to access the holder's claims. Addressing this gap, this paper introduces an innovative SSI-based solution that integrates decentralized wallets with Ciphertext-Policy Attribute-Based Proxy Re-Encryption (CP-ABPRE). This combination effectively addresses the challenge of verifier authorization. Our solution, implemented on the Ethereum platform, enhances accountability by notarizing key operations through a smart contract. This paper also offers a prototype demonstrating the practicality of the proposed approach. Furthermore, it provides an extensive evaluation of the solution's performance, emphasizing its feasibility and efficiency in real-world applications.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100196"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000095/pdfft?md5=670501a0e4d21da648399fb2a95be292&pid=1-s2.0-S2096720924000095-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140763959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy-aware proof-of-authority: Blockchain consensus for clustered wireless sensor network 能量感知的授权证明：集群无线传感器网络的区块链共识

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100211

{"title":"Energy-aware proof-of-authority: Blockchain consensus for clustered wireless sensor network","authors":"","doi":"10.1016/j.bcra.2024.100211","DOIUrl":"10.1016/j.bcra.2024.100211","url":null,"abstract":"<div><div>This study addresses integrating blockchain technology into lightweight devices, specifically clustered Wireless Sensor Networks (WSNs). Integrating blockchain into the WSNs solves the problems of heterogeneity, data integrity, and data confidentiality. However, no blockchain integration considers network lifetime in WSNs. This research focuses on developing a permissioned blockchain system that incorporates a consensus mechanism known as Proof-of-Authority (PoA) within clustered WSNs with two main features. The first feature is to enhance the network lifetime by introducing a rotational selection of block proposers using an Energy-Aware PoA (EA-PoA) weighting mechanism. Known as the Multi-Level Blockchain Model (MLBM), the subsequent feature is to create a hierarchical network model within a blockchain network. The MLBM network comprises both local and master blockchains. Each cluster inside a WSN possesses its local blockchain network. In the MLBM, the local blockchain creates a block on the main blockchain by proposing the headers of every 10 blocks to improve data integrity. Each local blockchain has its leader, which can increase block production. The results show that the proposed solution can overcome traditional PoA performance and is suitable for clustered WSNs. In terms of lifetime, the EA-PoA selection method can extend the network lifetime by up to 10%. In addition, the MLBM can increase block production by up to twice each additional cluster compared to a single blockchain network used in traditional PoA.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100211"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141397258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Expedition to the blockchain application potential for higher education institutions 探索高等教育机构的区块链应用潜力

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100203

Matthias Gottlieb , Christina Deutsch , Felix Hoops , Hans Pongratz , Helmut Krcmar

{"title":"Expedition to the blockchain application potential for higher education institutions","authors":"Matthias Gottlieb , Christina Deutsch , Felix Hoops , Hans Pongratz , Helmut Krcmar","doi":"10.1016/j.bcra.2024.100203","DOIUrl":"10.1016/j.bcra.2024.100203","url":null,"abstract":"<div><div>In the education sector, blockchain is currently at the end of the peak of inflated expectations in Gartner’s Hype Cycle. Thus, it is crucial to understand whether this technology meets the expectations of Higher Education Institutions (HEIs). We go on an expedition to identify blockchain application scenarios and its potential for HEI administration—the universities are digitalized to just 23.3%.</div><div>Current information systems research addresses classifications of blockchain-based projects (application level) rather than their technical realization (protocol level). Thus, when evaluating blockchain application scenarios in HEI administration, we intensively consider the technical side of blockchain-based projects. We perform a three-step approach: (1) systematic literature review, (2) qualitative exploratory semi-structured interviews to supplement information on market-ready solutions, and (3) an evaluation of the potential of the blockchain-based projects identified, based on HEI administration requirements.</div><div>We find that the leading blockchain application scenarios are credential verification and record-sharing. At the protocol level, we obtain equivocal results regarding the technical realization of projects, e.g., their underlying blockchain types and storage models. At the application level, when discussing the potential of different projects, we find that most of them address adaptability, complexity decomposition, and cost reduction requirements between HEIs; interest diversity and stakeholder collaboration between HEIs and business actors; privacy and trust between HEIs and students.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100203"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000162/pdfft?md5=8e0b84cecf19054cf2bb2d432145337e&pid=1-s2.0-S2096720924000162-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142316282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Partial pre-image attack on Proof-of-Work based blockchains 对基于工作证明的区块链的部分预映像攻击

IF 6.9 3区计算机科学

Blockchain-Research and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.bcra.2024.100194

{"title":"Partial pre-image attack on Proof-of-Work based blockchains","authors":"","doi":"10.1016/j.bcra.2024.100194","DOIUrl":"10.1016/j.bcra.2024.100194","url":null,"abstract":"<div><p>Blockchain is a type of distributed ledger technology that consists of a growing list of records, called blocks, that are securely linked together using cryptography. Each blockchain-based solution deploys a specific consensus algorithm that guarantees the consistency of the ledger over time. The most famous, and yet claimed to be the most secure, is the Proof-of-Work (PoW) consensus algorithm. In this paper, we revisit the fundamental calculations and assumptions of this algorithm, originally presented in the Bitcoin white paper. We break down its claimed calculations in order to better understand the underlying assumptions of the proposal. We also propose a novel formalization model of the PoW mining problem using the Birthday paradox. We utilize this model to formalize and analyze partial pre-image attacks on PoW-based blockchains, with formal analysis that confirms the experimental results and the previously proposed implications. We build on those analyses and propose new concepts for benchmarking the security of PoW-based systems, including Critical Difficulty and Critical Difficulty per given portion. Our calculations result in several important findings, including the profitability of launching partial pre-image attacks on PoW-based blockchains, once the mining puzzle difficulty reaches a given threshold. Specifically, for any compromised portion of the network (<span><math><mi>q</mi><mo><</mo><mn>0.5</mn></math></span>; honest majority assumption still holds), the attack is formally proven profitable once the PoW mining puzzle difficulty reaches 56 leading zeros.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100194"},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000071/pdfft?md5=f39562da38a21729770c2b928c68923e&pid=1-s2.0-S2096720924000071-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140268941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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