Future Internet最新文献_第3页

Enabling End-User Development in Smart Homes: A Machine Learning-Powered Digital Twin for Energy Efficient Management 促进智能家居的最终用户开发：机器学习驱动的节能管理数字双胞胎

IF 3.4

Future Internet Pub Date : 2024-06-14 DOI: 10.3390/fi16060208

Luca Cotti, Davide Guizzardi, Barbara Rita Barricelli, Daniela Fogli

引用次数: 0

Towards a New Business Model for Streaming Platforms Using Blockchain Technology 利用区块链技术打造流媒体平台新商业模式

IF 3.4

Future Internet Pub Date : 2024-06-13 DOI: 10.3390/fi16060207

Rendrikson Soares, André Araújo

引用次数: 0

Visual Data and Pattern Analysis for Smart Education: A Robust DRL-Based Early Warning System for Student Performance Prediction 用于智能教育的可视化数据和模式分析：基于 DRL 的学生成绩预测预警系统

IF 3.4

Future Internet Pub Date : 2024-06-11 DOI: 10.3390/fi16060206

Wala Bagunaid, Naveen Chilamkurti, Ahmad Salehi Shahraki, Saeed Bamashmos

{"title":"Visual Data and Pattern Analysis for Smart Education: A Robust DRL-Based Early Warning System for Student Performance Prediction","authors":"Wala Bagunaid, Naveen Chilamkurti, Ahmad Salehi Shahraki, Saeed Bamashmos","doi":"10.3390/fi16060206","DOIUrl":"https://doi.org/10.3390/fi16060206","url":null,"abstract":"Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) have revolutionised e-learning by creating personalised, adaptive, and secure environments. However, challenges such as privacy, bias, and data limitations persist. E-FedCloud aims to address these issues by providing more agile, personalised, and secure e-learning experiences. This study introduces E-FedCloud, an AI-assisted, adaptive e-learning system that automates personalised recommendations and tracking, thereby enhancing student performance. It employs federated learning-based authentication to ensure secure and private access for both course instructors and students. Intelligent Software Agents (ISAs) evaluate weekly student engagement using the Shannon Entropy method, classifying students into either engaged or not-engaged clusters. E-FedCloud utilises weekly engagement status, demographic information, and an innovative DRL-based early warning system, specifically ID2QN, to predict the performance of not-engaged students. Based on these predictions, the system categorises students into three groups: risk of dropping out, risk of scoring lower in the final exam, and risk of failing the end exam. It employs a multi-disciplinary ontology graph and an attention-based capsule network for automated, personalised recommendations. The system also integrates performance tracking to enhance student engagement. Data are securely stored on a blockchain using the LWEA encryption method.","PeriodicalId":37982,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141357851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Efficiency and Security in Unbalanced PSI-CA Protocols through Cloud Computing and Homomorphic Encryption in Mobile Networks 通过移动网络中的云计算和同态加密提高非平衡 PSI-CA 协议的效率和安全性

IF 3.4

Future Internet Pub Date : 2024-06-07 DOI: 10.3390/fi16060205

Wuzheng Tan, Shenglong Du, Jian Weng

{"title":"Enhancing Efficiency and Security in Unbalanced PSI-CA Protocols through Cloud Computing and Homomorphic Encryption in Mobile Networks","authors":"Wuzheng Tan, Shenglong Du, Jian Weng","doi":"10.3390/fi16060205","DOIUrl":"https://doi.org/10.3390/fi16060205","url":null,"abstract":"Private Set Intersection Cardinality (PSI-CA) is a cryptographic method in secure multi-party computation that allows entities to identify the cardinality of the intersection without revealing their private data.Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances. In real-world applications, dataset sizes and computational capacities often vary, particularly in Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI-CA protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI-CA protocols to these imbalances is crucial. This paper explores unbalanced scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities.This paper, based on the concept of commutative encryption, introduces Cuckoo filter, cloud computing technology, and homomorphic encryption, among other technologies, to construct three novel solutions for unbalanced Private Set Intersection Cardinality (PSI-CA): an unbalanced PSI-CA protocol based on Cuckoo filter, an unbalanced PSI-CA protocol based on single-cloud assistance, and an unbalanced PSI-CA protocol based on dual-cloud assistance. Depending on performance and security requirements, different protocols can be employed for various applications.","PeriodicalId":37982,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141372124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of Radio Access Protocols for V2X in 6G Scenario-Based Models 评估基于 6G 场景模型的 V2X 无线接入协议

IF 3.4

Future Internet Pub Date : 2024-06-06 DOI: 10.3390/fi16060203

Héctor Orrillo, André Sabino, M. Marques da Silva

{"title":"Evaluation of Radio Access Protocols for V2X in 6G Scenario-Based Models","authors":"Héctor Orrillo, André Sabino, M. Marques da Silva","doi":"10.3390/fi16060203","DOIUrl":"https://doi.org/10.3390/fi16060203","url":null,"abstract":"The expansion of mobile connectivity with the arrival of 6G paves the way for the new Internet of Verticals (6G-IoV), benefiting autonomous driving. This article highlights the importance of vehicle-to-everything (V2X) and vehicle-to-vehicle (V2V) communication in improving road safety. Current technologies such as IEEE 802.11p and LTE-V2X are being improved, while new radio access technologies promise more reliable, lower-latency communications. Moreover, 3GPP is developing NR-V2X to improve the performance of communications between vehicles, while IEEE proposes the 802.11bd protocol, aiming for the greater interoperability and detection of transmissions between vehicles. Both new protocols are being developed and improved to make autonomous driving more efficient. This study analyzes and compares the performance of the protocols mentioned, namely 802.11p, 802.11bd, LTE-V2X, and NR-V2X. The contribution of this study is to identify the most suitable protocol that meets the requirements of V2V communications in autonomous driving. The relevance of V2V communication has driven intense research in the scientific community. Among the various applications of V2V communication are Cooperative Awareness, V2V Unicast Exchange, and V2V Decentralized Environmental Notification, among others. To this end, the performance of the Link Layer of these protocols is evaluated and compared. Based on the analysis of the results, it can be concluded that NR-V2X outperforms IEEE 802.11bd in terms of transmission latency (L) and data rate (DR). In terms of the packet error rate (PER), it is shown that both LTE-V2X and NR-V2X exhibit a lower PER compared to IEEE protocols, especially as the distance between the vehicles increases. This advantage becomes even more significant in scenarios with greater congestion and network interference.","PeriodicalId":37982,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Metric Space Indices for Dynamic Optimization in a Peer to Peer-Based Image Classification Crowdsourcing Platform 基于点对点的图像分类众包平台中用于动态优化的度量空间指标

IF 3.4

Future Internet Pub Date : 2024-06-06 DOI: 10.3390/fi16060202

Fernando Loor, V. Gil-Costa, Mauricio Marín

引用次数: 0

Usability Evaluation of Wearable Smartwatches Using Customized Heuristics and System Usability Scale Score 使用定制启发式方法和系统可用性量表评分评估可穿戴智能手表的可用性

IF 3.4

Future Internet Pub Date : 2024-06-06 DOI: 10.3390/fi16060204

Majed A. Alshamari, Maha M. Althobaiti

引用次数: 0

Impact, Compliance, and Countermeasures in Relation to Data Breaches in Publicly Traded U.S. Companies 美国上市公司数据泄露事件的影响、合规性和应对措施

IF 3.4

Future Internet Pub Date : 2024-06-05 DOI: 10.3390/fi16060201

Gabriel Arquelau Pimenta Rodrigues, André Luiz Marques Serrano, Guilherme Fay Vergara, Robson de Oliveira Albuquerque, G. A. Nze

{"title":"Impact, Compliance, and Countermeasures in Relation to Data Breaches in Publicly Traded U.S. Companies","authors":"Gabriel Arquelau Pimenta Rodrigues, André Luiz Marques Serrano, Guilherme Fay Vergara, Robson de Oliveira Albuquerque, G. A. Nze","doi":"10.3390/fi16060201","DOIUrl":"https://doi.org/10.3390/fi16060201","url":null,"abstract":"A data breach is the unauthorized disclosure of sensitive personal data, and it impacts millions of individuals annually in the United States, as reported by Privacy Rights Clearinghouse. These breaches jeopardize the physical safety of the individuals whose data are exposed and result in substantial economic losses for the affected companies. To diminish the frequency and severity of data breaches in the future, it is imperative to research their causes and explore preventive measures. In pursuit of this goal, this study considers a dataset of data breach incidents affecting companies listed on the New York Stock Exchange and NASDAQ. This dataset has been augmented with additional information regarding the targeted company. This paper employs statistical visualizations of the data to clarify these incidents and assess their consequences on the affected companies and individuals whose data were compromised. We then propose mitigation controls based on established frameworks such as the NIST Cybersecurity Framework. Additionally, this paper reviews the compliance scenario by examining the relevant laws and regulations applicable to each case, including SOX, HIPAA, GLBA, and PCI-DSS, and evaluates the impacts of data breaches on stock market prices. We also review guidelines for appropriately responding to data leaks in the U.S., for compliance achievement and cost reduction. By conducting this analysis, this work aims to contribute to a comprehensive understanding of data breaches and empower organizations to safeguard against them proactively, improving the technical quality of their basic services. To our knowledge, this is the first paper to address compliance with data protection regulations, security controls as countermeasures, financial impacts on stock prices, and incident response strategies. Although the discussion is focused on publicly traded companies in the United States, it may also apply to public and private companies worldwide.","PeriodicalId":37982,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141383159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes 在智能家居物联网设备上实现基于机器学习的轻量级入侵检测系统

IF 3.4

Future Internet Pub Date : 2024-06-05 DOI: 10.3390/fi16060200

Abbas Javed, Amna Ehtsham, Muhammad Jawad, Muhammad Naeem Awais, Ayyaz-Ul-Haq Qureshi, Hadi Larijani

{"title":"Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes","authors":"Abbas Javed, Amna Ehtsham, Muhammad Jawad, Muhammad Naeem Awais, Ayyaz-Ul-Haq Qureshi, Hadi Larijani","doi":"10.3390/fi16060200","DOIUrl":"https://doi.org/10.3390/fi16060200","url":null,"abstract":"Smart home devices, also known as IoT devices, provide significant convenience; however, they also present opportunities for attackers to jeopardize homeowners’ security and privacy. Securing these IoT devices is a formidable challenge because of their limited computational resources. Machine learning-based intrusion detection systems (IDSs) have been implemented on the edge and the cloud; however, IDSs have not been embedded in IoT devices. To address this, we propose a novel machine learning-based two-layered IDS for smart home IoT devices, enhancing accuracy and computational efficiency. The first layer of the proposed IDS is deployed on a microcontroller-based smart thermostat, which uploads the data to a website hosted on a cloud server. The second layer of the IDS is deployed on the cloud side for classification of attacks. The proposed IDS can detect the threats with an accuracy of 99.50% at cloud level (multiclassification). For real-time testing, we implemented the Raspberry Pi 4-based adversary to generate a dataset for man-in-the-middle (MITM) and denial of service (DoS) attacks on smart thermostats. The results show that the XGBoost-based IDS detects MITM and DoS attacks in 3.51 ms on a smart thermostat with an accuracy of 97.59%.","PeriodicalId":37982,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141386379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Metaverse and Fashion: An Analysis of Consumer Online Interest 元宇宙与时尚：消费者在线兴趣分析

IF 3.4

Future Internet Pub Date : 2024-06-04 DOI: 10.3390/fi16060199

Carmen Ruiz Viñals, Marta Gil Ibáñez, José Luis del Olmo Arriaga

引用次数: 0