Internet Technology Letters最新文献_第3页

Optimizing medical visual question answering: Evaluating the impact of enhanced images, augmented training data, and model selection

IF 0.9

Internet Technology Letters Pub Date : 2025-02-26 DOI: 10.1002/itl2.588

Ali Jaber Almalki

引用次数: 0

Security Enhancement in 5G Networks by Identifying Attacks Using Optimized Cosine Convolutional Neural Network

IF 0.9

Internet Technology Letters Pub Date : 2025-02-26 DOI: 10.1002/itl2.70003

Premalatha Santhanamari, Vijayakumar Kathirgamam, Lakshmisridevi Subramanian, Thamaraikannan Panneerselvam, Rathish Chirakkal Radhakrishnan

{"title":"Security Enhancement in 5G Networks by Identifying Attacks Using Optimized Cosine Convolutional Neural Network","authors":"Premalatha Santhanamari, Vijayakumar Kathirgamam, Lakshmisridevi Subramanian, Thamaraikannan Panneerselvam, Rathish Chirakkal Radhakrishnan","doi":"10.1002/itl2.70003","DOIUrl":"https://doi.org/10.1002/itl2.70003","url":null,"abstract":"<div>\u0000 \u0000 <p>The exponential growth of 5G networks has introduced advanced capabilities but also heightened susceptibility to sophisticated cyberattacks. To address this, a robust and optimized security framework is proposed, leveraging a Cosine Convolutional Neural Network (CCNN) for attack detection. By emphasizing angular correlations in data, the CCNN improves feature extraction by substituting cosine similarity-based adjustments for conventional convolution processes. To maximize the CCNN's performance, the Exponential Distribution Optimizer (EDO) is employed optimize CCNN. The optimal configuration of CCNN is achieved using EDO's probabilistic search mechanism, which is inspired by exponential distribution and helps to maintain a balanced exploration-exploitation strategy. This integrated approach significantly improves detection accuracy, robustness, and scalability while maintaining low computational overhead. Comprehensive evaluations demonstrate the model's efficacy in identifying diverse attack patterns in 5G networks, outperforming conventional methods. The proposed framework establishes a new benchmark for secure, intelligent 5G infrastructures, contributing to the advancement of cybersecurity in next-generation networks. The introduced approach attains higher accuracy of 99%.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496937","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

Trust-Based Reliability Scheme for Secure Data Sharing With Internet of Vehicles Networks

IF 0.9

Internet Technology Letters Pub Date : 2025-02-26 DOI: 10.1002/itl2.70000

Arpit Jain, Ashok Kumar, Mahadev, Jitendra Kumar Chaudhary, Saurabh Singh

{"title":"Trust-Based Reliability Scheme for Secure Data Sharing With Internet of Vehicles Networks","authors":"Arpit Jain, Ashok Kumar,  Mahadev, Jitendra Kumar Chaudhary, Saurabh Singh","doi":"10.1002/itl2.70000","DOIUrl":"https://doi.org/10.1002/itl2.70000","url":null,"abstract":"<div>\u0000 \u0000 <p>With the Internet of Things (IoT) increasingly integrated into vehicles, drivers and passengers can access information anywhere, anytime. As the number of connected vehicles increases, new requirements for vehicular networks arise, including securing, robust, and scalable communication between vehicles and pedestrians. It encompasses the communication between vehicles and infrastructure, as well as the communication between vehicles and pedestrians. A real-time exchange of road condition information can be achieved through this method. An IoV network rogue node detection scheme is presented here using a combined trust model. Using a trust-based security algorithm, vehicles are assessed for trustworthiness and rogue vehicles are identified. Communication and data reliability are used to calculate direct Trust while neighboring vehicles' cooperation is used to calculate recommendation trust. According to simulation results, the proposed model is highly accurate and maintains a low detection delay while protecting evaluation data privacy. Trust updates are more efficient using this model, and malicious vehicles are detected more quickly than traditional schemes.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496935","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

Edge Computing Enables Assessment of Student Community Building: An Emotion Recognition Method Based on TinyML

IF 0.9

Internet Technology Letters Pub Date : 2025-02-24 DOI: 10.1002/itl2.645

Shuo Liu

引用次数: 0

AI-Driven Big Data Analytics for Mobile Healthcare

IF 0.9

Internet Technology Letters Pub Date : 2025-01-13 DOI: 10.1002/itl2.624

Dr. B. D. Parameshachari, Dr. Danilo Pelusi, Dr. Bhargavi Goswami

引用次数: 0

Hadamard and Riemann Matrix-Based SLM for PAPR Reduction in OTFS Signal 基于哈达玛矩阵和黎曼矩阵的 SLM，用于降低 OTFS 信号的 PAPR

IF 0.9

Internet Technology Letters Pub Date : 2024-10-27 DOI: 10.1002/itl2.591

Aare Gopal, Desireddy Krishna Reddy

{"title":"Hadamard and Riemann Matrix-Based SLM for PAPR Reduction in OTFS Signal","authors":"Aare Gopal, Desireddy Krishna Reddy","doi":"10.1002/itl2.591","DOIUrl":"https://doi.org/10.1002/itl2.591","url":null,"abstract":"<div>\u0000 \u0000 <p>In this letter, we study the peak-to-average power ratio (PAPR) reduction and bit error rate (BER) performances of the Hadamard and Riemann matrix-based selected mapping (SLM) technique for Orthogonal Time Frequency Space (OTFS) signals. Unlike the conventional phase sequence based on <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mrow>\u0000 <mo>{</mo>\u0000 <mrow>\u0000 <mo>±</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <mo>,</mo>\u0000 <mrow>\u0000 <mo>±</mo>\u0000 <mi>j</mi>\u0000 </mrow>\u0000 <mo>}</mo>\u0000 </mrow>\u0000 </mrow>\u0000 <annotation>$$ left{pm 1,pm jright} $$</annotation>\u0000 </semantics></math>, which requires the entire sequence to extract the original signal at the receiver, the Hadamard and Riemann matrix-based SLM techniques require only the row index of the matrix, reducing the additional information necessary to extract the signal. Simulation results are presented to verify the PAPR and BER performance. The results are also compared with the existing normalized <i>μ</i>-law, rooting <i>μ</i>-law, and conventional SLM methods. The results demonstrate that the Riemann-based SLM technique shows significant performance improvement.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"7 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143187192","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

NB-IoT: Analytical Perspective of IP Data Delivery Variants

IF 0.9

Internet Technology Letters Pub Date : 2024-10-21 DOI: 10.1002/itl2.594

Priyatosh Mandal

引用次数: 0

Enhancing Cross-Domain Book Classification Through Caching-Enabled Networks and Transformer Technology

IF 0.9

Internet Technology Letters Pub Date : 2024-10-10 DOI: 10.1002/itl2.590

Qiang Li, Huaiyuan Zheng, Yulai Bao, Side Liu

{"title":"Enhancing Cross-Domain Book Classification Through Caching-Enabled Networks and Transformer Technology","authors":"Qiang Li, Huaiyuan Zheng, Yulai Bao, Side Liu","doi":"10.1002/itl2.590","DOIUrl":"https://doi.org/10.1002/itl2.590","url":null,"abstract":"<div>\u0000 \u0000 <p>Book classification is a crucial task for libraries and a fundamental aspect of their service offerings. Cross-domain book classification, in particular, presents significant challenges due to the diversity and complexity of content across different genres and subjects. To tackle these challenges, a user-oriented strategy employing Transformer network (TN) is developed to fulfill the need for superior content quality and classification. Our proposed method leverages the self-attention mechanism of TN for precise feature extraction and classification, combining it with principal component analysis to ensure a comprehensive understanding of book content. This integration represents a technical innovation that enhances the model's ability to handle diverse datasets with improved accuracy and robustness. Our approach merges TN with caching-enabled networks (CEN) to enhance accuracy and robustness. Driven by the necessity for improved cross-domain classification, our strategy aims to standardize book classifications, thus improving user satisfaction. The primary actions encompass improved classification management, feedback systems, and evaluation frameworks. This work highlights the innovative fusion of TN and CEN, showcasing how these advanced techniques can significantly elevate the performance of library classification systems. Our work demonstrates that high-quality book classification can significantly improve library services and user experience. Furthermore, it aligns with the broader applications of CEN in emerging networking technologies, showing the potential for cutting-edge techniques to revolutionize library services.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688755","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

PIoT-oriented multi-target recognition of substation infrared images driven by deep learning

IF 0.9

Internet Technology Letters Pub Date : 2024-10-03 DOI: 10.1002/itl2.573

Min Li, Tou Li, Xuan Zhang, Wei Zhang

引用次数: 0

IQL-OCDA: An intelligent Q-learning-based for optimal clustering and data-aggregation for wireless sensor networks

IF 0.9

Internet Technology Letters Pub Date : 2024-10-03 DOI: 10.1002/itl2.572

Arwa N. Aledaily

引用次数: 0