检索结果-南通市图书馆

Multi-Attack Intrusion Detection System for software-defined Internet of Things Network

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第6期75卷 4985-5007页

作者： Tarcizio Ferrao Franklin Manene Adeyemi Abel Ajibesin Pan African University Institute for Basic Sciences Technology and InnovationNairobi6200-00200Kenya Department of Electrical and Control Engineering Egerton UniversityNakuru536-20115Kenya School of Engineering American University of NigeriaPMB 2250 YolaNigeria

Currently,the Internet of Things(IoT)is revolutionizing communi-cation technology by facilitating the sharing of information between different physical devices connected to a *** improve control,customization,flexibility,and reduce network maintenance costs,a new software-defined Network(SDN)technology must be used in this *** the various advantages of combining SDN and IoT,this environment is more vulnerable to various attacks due to the centralization of *** methods to ensure IoT security are designed to detect Distributed Denial-of-Service(DDoS)attacks,but they often lack mechanisms to mitigate their *** paper proposes a Multi-Attack Intrusion Detection System(MAIDS)for software-defined IoT networks(SDN-IoT).The proposed scheme uses two machine-learning algorithms to improve detection efficiency and provide a mechanism to prevent false ***,a comparative analysis of the most commonly used machine-learning algorithms to secure the SDN was performed on two datasets:the Network Security Laboratory Knowledge Discovery in Databases(NSL-KDD)and the Canadian Institute for Cyberse-curity Intrusion Detection Systems(CICIDS2017),to select the most suitable algorithms for the proposed scheme and for securing SDN-IoT *** algorithms evaluated include Extreme Gradient Boosting(XGBoost),K-Nearest Neighbor(KNN),Random Forest(RF),Support Vector Machine(SVM),and Logistic Regression(LR).Second,an algorithm for selecting the best dataset for machine learning in Intrusion Detection Systems(IDS)was developed to enable effective comparison between the datasets used in the development of the security *** results showed that XGBoost and RF are the best algorithms to ensure the security of SDN-IoT and to be applied in the proposed security system,with average accuracies of 99.88%and 99.89%,***,the proposed security scheme reduced the false alarm rate by 33.23%,which is a significant improvement over p

关键词： Dataset selection false alarm intrusion detection systems IoT security machine learning SDN-IoT security software-defined networks

Optimized Load Balancing Technique for software defined Network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第7期72卷 1409-1426页

作者： Aashish Kumar Darpan Anand Sudan Jha Gyanendra Prasad Joshi Woong Cho Department of Computer Science and Engineering Chandigarh UniversityMohaliPunjab140413India School of Computational Sciences CHRIST(Deemed to be University)Ghaziabad201003India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Automotive ICT Convergence Engineering Daegu Catholic UniversityGyeongsan38430Korea

software-defined networking is one of the progressive and prominent innovations in Information and Communications *** mitigates the issues that our conventional network was ***,traffic data generated by various applications is increasing day by *** addition,as an organization’s digital transformation is accelerated,the amount of information to be processed inside the organization has increased *** might be possible that a software-defined Network becomes a bottleneck and *** models have been proposed in the literature to balance the ***,most of the works consider only limited parameters and do not consider controller and transmission media *** loads also contribute to decreasing the performance of software-defined *** work illustrates how a software-defined network can tackle the load at its software layer and give excellent results to distribute the *** proposed a deep learning-dependent convolutional neural networkbased load balancing technique to handle a software-defined network *** simulation results show that the proposed model requires fewer resources as compared to existing machine learning-based load balancing techniques.

关键词： SDN software-defined networks load balancing performance enhancement

An IoT Environment Based Framework for Intelligent Intrusion Detection

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第5期75卷 2365-2381页

作者： Hamza Safwan Zeshan Iqbal Rashid Amin Muhammad Attique Khan Majed Alhaisoni Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Deparment of Computer Science UET TaxilaTaxila47080Pakistan Department of Computer Science HITEC UniversityTaxila47080Pakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

software-defined networking(SDN)represents a paradigm shift in network traffic *** distinguishes between the data and control *** are then used to communicate between these *** controller is central to the management of an SDN network and is subject to security *** research shows how a deep learning algorithm can detect intrusions in SDN-based IoT ***,low accuracy,and efficient feature selection is all *** propose a hybrid machine learning-based approach based on Random Forest and Long Short-Term Memory(LSTM).In this study,a new dataset based specifically on software defined networks is used in *** obtain the best and most relevant features,a feature selection technique is *** experiments have revealed that the proposed solution is a superior method for detecting flow-based *** performance of our proposed model is also measured in terms of accuracy,recall,and precision.F1 rating and detection time Furthermore,a lightweight model for training is proposed,which selects fewer features while maintaining the model’s *** show that the adopted methodology outperforms existing models.

关键词： software-defined networks prediction modeling machine learning deep learning

Towards a Dynamic Virtual IoT Network Based on User Requirements

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第11期69卷 2231-2244页

作者： Faisal Mehmood Shabir Ahmad Israr Ullah Faisal Jamil DoHyeun Kim Department of Computer Engineering Jeju National UniversityJeju63243Korea Department of I.T.Convergence Engineering Gachon UniversitySeongnam-Si461-701Korea Department of software Engineering University of Engineering&Technology MardanMardan23200Pakistan

The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource *** defined Networking has been extensively utilized to address issues such as heterogeneity and ***,for small-scale IoT application,sometimes it is considered an inefficient *** paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user *** key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at *** throughput of the communication flow depends on the data traffic load and optimal *** can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic *** virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual *** proposed network is applicable for all systems that lie in the Internet of Things *** conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime.

关键词： Internet of things software-defined networks virtual network inter-process communication cloud of things

基于边缘计算的软件定义云制造和柔性资源调度研究

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Engineering 2023年第3期22卷 60-70页

作者：杨晨廖方茵兰舒琳王力翚沈卫明黄国全 School of Cyberspace Science and Technology Beijing Institute of TechnologyBeijing 100081China School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China School of Mathematics and Computer Science Yan'an UniversityYan'an 716000China School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Department of Production Engineering KTH Royal Institute of TechnologyStockholm 10044Sweden State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Industrial and Manufacturing Systems Engineering The University of Hong KongHong Kong 999077China

本研究的重点是在云制造环境中实现快速重构、实现灵活的资源调度、开发资源潜力以应对各种变化。因此,本文首先提出了一种新的基于云和软件定义网络(SDN)的制造模型——软件定义云制造(SDCM),该模型将控制逻辑从自动化硬件转移到软件... 详细信息

本研究的重点是在云制造环境中实现快速重构、实现灵活的资源调度、开发资源潜力以应对各种变化。因此,本文首先提出了一种新的基于云和软件定义网络(SDN)的制造模型——软件定义云制造(SDCM),该模型将控制逻辑从自动化硬件转移到软件上。这种转变意义重大,因为软件可以充当制造系统的“大脑”,并且可以轻松更改或更新以支持快速系统重新配置、运营和演进。随后,边缘计算被引入,以接近终端的计算和存储能力来补充云。另一个关键问题是管理由不同服务质量(QoS)要求的大量物联网(IoT)数据传输而导致的严重网络拥塞。基于SDCM的虚拟化和灵活的网络能力,本研究形式化了面向复杂制造任务集的时间敏感性数据流量控制问题,并考虑了子任务分配和数据路由路径选择。为了解决这一优化问题,提出了一种将遗传算法(GA)、Dijkstra最短路径算法和排队算法相结合的方法。实验结果表明,该方法能有效地防止网络拥塞,减少SDCM中的总通信延迟。

关键词： Cloud manufacturing Edge computing software-defined networks Industrial Internet of Things Industry 4.0

Artificial Intelligence Self-Organising (AI-SON) Frameworks for 5G-Enabled networks: A Review

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Computer and Communications 2023年第4期11卷 33-62页

作者： Delali Kwasi Dake Department of ICT Education University of Education Winneba Ghana

The fifth generation (5G) networks will support the rapid emergence of Internet of Things (IoT) devices operating in a heterogeneous network (HetNet) system. These 5G-enabled IoT devices will result in a surge in data traffic for Mobile Network Operators (MNOs) to handle. At the same time, MNOs are preparing for a paradigm shift to decouple the control and forwarding plane in a software-defined Networking (SDN) architecture. Artificial Intelligence powered Self-Organising networks (AI-SON) can fit into the SDN architecture by providing prediction and recommender systems to minimise costs in supporting the MNO’s infrastructure. This paper presents a review report on AI-SON frameworks in 5G and SDN. The review considers the dynamic deployment and functions of the AI-SON frameworks, especially for SDN support and applications. Each module in the frameworks was discussed to ascertain its relevance based on the context of AI-SON and SDN integration. After examining each framework, the identified gaps are summarised as open issues for future works.

关键词： Self-Organising networks Artificial Intelligence software-defined networks 5G networks Big Data

Decoupled delay and bandwidth centralized queue-based QoS scheme in OpenFlow networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Decoupled delay and bandwidth centralized queue-based QoS sc...