IET Communications最新文献_第9页

Efficient provable dual receiver hybrid and light weight public key schemes based on the discrete logarithm problem without pairings 基于无配对的离散对数问题的高效可证明双接收机混合轻量级公钥方案

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-18 DOI: 10.1049/cmu2.12836

Eman Abouelkheir

{"title":"Efficient provable dual receiver hybrid and light weight public key schemes based on the discrete logarithm problem without pairings","authors":"Eman Abouelkheir","doi":"10.1049/cmu2.12836","DOIUrl":"https://doi.org/10.1049/cmu2.12836","url":null,"abstract":"Dual-receiver proxy re-encryption is a cryptographic technique that enables secure data sharing among multiple authorized users or entities. It has gained significant attention for its ability to manage access permissions, data confidentiality, and streamline communication channels. These schemes have been widely used in various applications, including healthcare systems, cloud computing, Internet of Things (IoT) systems, collaborative environments, and secure communication channels. This paper aims to propose two proxy re-encryption schemes for dual receivers without pairings. The first is dual receiver lightweight proxy re-encryption without pairings (DR-LWPRE-WP), which uses a public key scheme to reduce computational complexity. The second is dual receiver hybrid proxy re-encryption without pairings (DR-HPRE-WP), which incorporates public key and symmetric key schemes. Both schemes offer protection against selected plaintext attacks based on the decisional Diffie-Hellman principle. The DR-LWPRE-WP scheme reduces computation by approximately 53% compared to pairing-based schemes, making it suitable for lightweight applications like the Internet of Things. The computational efficacy of these schemes offers significant benefits for resource-constrained environments and practical implementations.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 19","pages":"1417-1427"},"PeriodicalIF":1.5,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12836","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

A cloud-based hybrid intrusion detection framework using XGBoost and ADASYN-Augmented random forest for IoMT 基于XGBoost和ad异步增强随机森林的基于云的混合入侵检测框架

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-17 DOI: 10.1049/cmu2.12833

Arash Salehpour, Monire Norouzi, Mohammad Ali Balafar, Karim SamadZamini

{"title":"A cloud-based hybrid intrusion detection framework using XGBoost and ADASYN-Augmented random forest for IoMT","authors":"Arash Salehpour, Monire Norouzi, Mohammad Ali Balafar, Karim SamadZamini","doi":"10.1049/cmu2.12833","DOIUrl":"https://doi.org/10.1049/cmu2.12833","url":null,"abstract":"Internet of Medical Things have vastly increased the potential for remote patient monitoring, data-driven care, and networked healthcare delivery. However, the connectedness lays sensitive patient data and fragile medical devices open to security threats that need robust intrusion detection solutions within cloud-edge services. Current approaches need modification to be able to handle the practical challenges that result from problems with data quality. This paper presents a hybrid intrusion detection framework that enhances the security of IoMT networks. There are three modules in the design. First, an XGBoost-based noise detection model is used to identify data anomalies. Second, adaptive resampling with ADASYN is done to fine-tune the class distribution to address class imbalance. Third, ensemble learning performs intrusion detection through a Random Forest classifier. This stacked model coordinates techniques that filter noise and preprocess imbalanced data, identifying threats with high accuracy and reliability. These results are then experimentally validated on the UNSW-NB15 benchmark to demonstrate effective detection under realistically noisy conditions. The novel contributions of the work are a new hybrid structural paradigm coupled with integrated noise filtering, and ensemble learning. The proposed advanced oversampling with ADASYN gives a performance that surpasses all others with a reported 92.23% accuracy.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 19","pages":"1371-1390"},"PeriodicalIF":1.5,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12833","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 innovative model for an enhanced dual intrusion detection system using LZ-JC-DBSCAN, EPRC-RPOA and EG-GELU-GRU 使用 LZ-JC-DBSCAN、EPRC-RPOA 和 EG-GELU-GRU 的增强型双重入侵检测系统的创新模型

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-12 DOI: 10.1049/cmu2.12831

Jeyavim Sherin R. C., Parkavi K.

{"title":"An innovative model for an enhanced dual intrusion detection system using LZ-JC-DBSCAN, EPRC-RPOA and EG-GELU-GRU","authors":"Jeyavim Sherin R. C., Parkavi K.","doi":"10.1049/cmu2.12831","DOIUrl":"https://doi.org/10.1049/cmu2.12831","url":null,"abstract":"The rise of suspicious activities in network communication, driven by increased internet accessibility, necessitates the development of advanced intrusion detection systems (IDS). Existing IDS solutions often exhibit poor performance in detecting suspicious activity and fail to identify various attack types within packet capture (PCAP) files, which monitor network traffic. This paper proposes a deep learning-based dual IDS model designed to address these issues. The process begins with utilizing the CSE-CIC-IDS2019 dataset to extract features from PCAP files. Suspicious activities are detected using the Exponential Geometric-Gaussian Error Linear Units-Gated Recurrent Unit (EG-GELU-GRU) method. Normal data undergoes further feature extraction and preprocessing through Log ZScore-Jacosine Density-Based Spatial Clustering of Applications with Noise (LZ-JC-DBSCAN). Feature selection is optimized using the Entropy Pearson R Correlation-Red Panda optimization algorithm. Suspicious files are flagged, while load balancing is performed on normal data. Attack detection is achieved through word embedding with the Glorot Kaufman-bidirectional encoder representations from transformers technique and classification via the EG-GELU-GRU model. Attacked packets are blocked, and the method is reapplied for attack-type classification. Experimental results using Python demonstrate the model’s superior performance, achieving 98.18% accuracy and 98.73% precision, surpassing existing approaches and significantly enhancing intrusion detection capabilities.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 18","pages":"1300-1318"},"PeriodicalIF":1.5,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12831","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

A high-precision timing and frequency synchronization algorithm for multi-h CPM signals 多小时 CPM 信号的高精度定时和频率同步算法

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-10 DOI: 10.1049/cmu2.12809

Yukai Liu, Rongke Liu, Qizhi Chen, Ling Zhao

{"title":"A high-precision timing and frequency synchronization algorithm for multi-h CPM signals","authors":"Yukai Liu, Rongke Liu, Qizhi Chen, Ling Zhao","doi":"10.1049/cmu2.12809","DOIUrl":"https://doi.org/10.1049/cmu2.12809","url":null,"abstract":"In the context of certain specific digital communication systems, where there are limitations such as spectral resources and energy availability, continuous phase modulation (CPM) emerges as an appealing choice among various modulation methods. Among CPM signals, multi-h CPM is particularly noteworthy for its ability to address these constraints within the realm of single-carrier and constant-envelope waveforms. At the physical layer, the design of a multi-h CPM receiver necessitates the efficient implementation of timing and frequency synchronization algorithm within a high dynamic environment. So this paper presents an innovative approach for achieving timing and frequency synchronization. To rectify timing offset and mitigate the adverse effects of noise in received signals, a re-configurable local filter generation method is integrated into the timing synchronization algorithm. Simultaneously, an enhanced least mean square adaptive filter algorithm is applied to address frequency synchronization. A comprehensive series of simulations rigorously evaluates the outcomes of proposed novel synchronization methodology. These analyses demonstrate a notable proximity between the synchronization errors of proposed algorithm in this paper and the performance benchmark set by the modified Cramer–Rao bound. The proposed synchronization technology also exhibits the capability to substantially reduce the bit error rate, thereby effectively enhancing demodulation performance in multi-h CPM receivers.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 17","pages":"1049-1061"},"PeriodicalIF":1.5,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12809","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Capacity analysis over fractional order Rayleigh fading channel under additive white generalized Gaussian noise 加性广义高斯白噪声下分数阶瑞利衰落信道的容量分析

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-10 DOI: 10.1049/cmu2.12834

Mehran Kakavand, Mohammadreza Hassannejad Bibalan, Mina Baghani

{"title":"Capacity analysis over fractional order Rayleigh fading channel under additive white generalized Gaussian noise","authors":"Mehran Kakavand, Mohammadreza Hassannejad Bibalan, Mina Baghani","doi":"10.1049/cmu2.12834","DOIUrl":"https://doi.org/10.1049/cmu2.12834","url":null,"abstract":"This study presents an innovative fractional order Rayleigh fading model that can be used for channel capacity estimation in the presence of additive white generalized Gaussian noise. The proposed model assumes that the real and imaginary parts of channel gains are generalized Gaussian random variables, which makes it possible to consider the traditional Rayleigh fading model as a special case of fractional order Rayleigh fading. Compared to the Rayleigh model, the fractional order Rayleigh fading model offers a more precise representation of new real-world communication, such as integrating terrestrial and underwater networks in sixth-generation communications channels. The probability density function of the channel gain with additive white generalized Gaussian noise is analyzed here. Furthermore, the ergodic and outage capacities of the channel are determined, taking into account the assumption that the channel state information is only available at the receiver. The ergodic capacity is calculated using Meijer's G-functions, resulting in a closed-form expression. Numerical simulations demonstrate the superiority of the fractional order Rayleigh fading model over the Rayleigh channel. Moreover, the impact of ergodic and outage capacities under diverse channel characteristics is assessed.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 19","pages":"1391-1402"},"PeriodicalIF":1.5,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12834","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Dual-user joint sensing and communications with time-divisioned bi-static radar 采用时分双静态雷达的双用户联合传感与通信技术

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-08 DOI: 10.1049/cmu2.12820

Enhao Wang, Yunfei Chen, Aissa Ikhlef, Hongjian Sun

引用次数: 0

Dynamic environment UAV deployment algorithm based on potential game theory

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-07 DOI: 10.1049/cmu2.12776

Chuan Gu, Binbin Wu, Daoxing Guo, Hao Jiang

引用次数: 0

Resource allocation scheduling scheme for task migration and offloading in 6G Cybertwin internet of vehicles based on DRL 基于 DRL 的 6G 车联网中任务迁移和卸载的资源分配调度方案

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-06 DOI: 10.1049/cmu2.12826

Rui Wei, Tuanfa Qin, Jinbao Huang, Ying Yang, Junyu Ren, Lei Yang

{"title":"Resource allocation scheduling scheme for task migration and offloading in 6G Cybertwin internet of vehicles based on DRL","authors":"Rui Wei, Tuanfa Qin, Jinbao Huang, Ying Yang, Junyu Ren, Lei Yang","doi":"10.1049/cmu2.12826","DOIUrl":"https://doi.org/10.1049/cmu2.12826","url":null,"abstract":"As vehicular technology advances, intelligent vehicles generate numerous computation-intensive tasks, challenging the computational resources of both the vehicles and the Internet of Vehicles (IoV). Traditional IoV struggles with fixed network structures and limited scalability, unable to meet the growing computational demands and next-generation mobile communication technologies. In congested areas, near-end Mobile Edge Computing (MEC) resources are often overtaxed, while far-end MEC servers are underused, resulting in poor service quality. A novel network framework utilizing sixth-generation mobile communication (6G) and digital twin technologies, combined with task migration, promises to alleviate these inefficiencies. To address these challenges, a task migration and re-offloading model based on task attribute classification is introduced, employing a hybrid deep reinforcement learning (DRL) algorithm—Dueling Double Q Network DDPG (QDPG). This algorithm merges the strengths of the Deep Deterministic Policy Gradient (DDPG) and the Dueling Double Deep Q-Network (D3QN), effectively handling continuous and discrete action domains to optimize task migration and re-offloading in IoV. The inclusion of the Mini Batch K-Means algorithm enhances learning efficiency and optimization in the DRL algorithm. Experimental results show that QDPG significantly boosts task efficiency and computational performance, providing a robust solution for resource allocation in IoV.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 18","pages":"1244-1265"},"PeriodicalIF":1.5,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12826","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

A lightweight deep learning architecture for automatic modulation classification of wireless internet of things 用于无线物联网自动调制分类的轻量级深度学习架构

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-05 DOI: 10.1049/cmu2.12823

Jia Han, Zhiyong Yu, Jian Yang

{"title":"A lightweight deep learning architecture for automatic modulation classification of wireless internet of things","authors":"Jia Han, Zhiyong Yu, Jian Yang","doi":"10.1049/cmu2.12823","DOIUrl":"https://doi.org/10.1049/cmu2.12823","url":null,"abstract":"The wireless Internet of Things (IoT) is widely used for data transmission in power systems. Wireless communication is an important part of the IoT. The existing modulation classification algorithms have low classification accuracy when facing strong electromagnetic interference, which causes decoding error link interruption and wastes wireless channel resources. Therefore, it is necessary to study signal modulation classification methods in a low signal-to-noise ratio (SNR) environment. In this paper, a lightweight Deep Neural Networks (DNNs) modulation classification method based on the Informer architecture classifier and two-dimensional (2-D) curves input of the spectral correlation function (SCF) is proposed, which uses in-phase and quadrature (I/Q) signals to generate 2-D cross-section SCF curve first and then feeds the feature curve into the Informer network to classify the modulation method. This model can better learn the robustness characteristics in a long sequence. Through testing, the classification accuracy of the modulation signal is not much lower than that of the current good classification method when the SNR is 10 dB, and this method can still show higher accuracy when hardware resources are limited. It is a compact design of a modulation classification model and easy to deploy on low-cost embedded platforms.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 18","pages":"1220-1230"},"PeriodicalIF":1.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12823","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Empirical modelling and analysis of phase noise in OFDM systems OFDM系统中相位噪声的实证建模与分析

IF 1.5 4区计算机科学

IET Communications Pub Date : 2024-09-04 DOI: 10.1049/cmu2.12832

Qihong Duan, Heng Du, Jiang Xue, Feng Li

引用次数: 0