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A Probabilistic Trust Model and Control Algorithm to Protect 6g networks against Malicious Data Injection Attacks in Edge Computing Environments

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 631-654页

作者： Borja Bordel Sánchez Ramón Alcarria Tomás Robles Department of Computer Systems Universidad Politécnica de MadridMadrid28031Spain Department of geospatial Engineering Universidad Politécnica de MadridMadrid28031Spain

Future 6g communications are envisioned to enable a large catalogue of pioneering *** will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential *** provision of extensive machine-type communications through 6g will render many of these innovative systems autonomous and *** full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and *** particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control ***,Denialof-Service attacks can be executed by inundating the network with valueless *** anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical *** based on an exhaustive data collection to detect anomalies are precise but extremely *** models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors *** paper introduces a probabilistic trust model and control algorithm designed to address this *** model determines the probability of any node to be *** channels are pruned for those nodes whose probability is below a given *** trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and ***,anomalous nodes are identified using gaussian mixture models and clustering ***,traffic patterns are studied using digital Bessel functions and the functional scalar ***,the in

关键词： 6g networks noise injection attacks gaussian mixture model Bessel function traffic filter Volterra filter

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Intelligent Modulation Recognition of Communication Signal for Next-generation 6g networks

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Computers, Materials & Continua 2023年第3期74卷 5723-5740页

作者： Mrim M.Alnfiai Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

In recent years,the need for a fast,efficient and a reliable wireless network has increased *** 5g networks have already been tested while a few are in the early stages of *** noncooperative communication scenarios,the recognition of digital signal modulations assists people in identifying the communication targets and ensures an effective management over *** recent advancements in both Machine Learning(ML)and Deep Learning(DL)models demand the development of effective modulation recognition models with self-learning *** this background,the current research article designs aDeep Learning enabled Intelligent Modulation Recognition of Communication Signal(DLIMR-CS)technique for next-generation *** aim of the proposed DLIMR-CS technique is to classify different kinds of digitally-modulated *** addition,the fractal feature extraction process is appliedwith the help of the Sevcik Fractal Dimension(SFD)***,the extracted features are fed into the Deep Variational Autoencoder(DVAE)model for the classification of the modulated *** order to improve the classification performance of the DVAE model,the Tunicate Swarm Algorithm(TSA)is used to finetune the hyperparameters involved in DVAE model.A wide range of simulations was conducted to establish the enhanced performance of the proposed DLIMR-CS *** experimental outcomes confirmed the superior recognition rate of the DLIMR-CS model over recent state-of-the-art methods under different evaluation parameters.

关键词： 6g networks communication signal modulation recognition deep learning machine learning parameter optimization

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An Efficient Scheme for Interference Mitigation in 6g-IoT Wireless networks

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Computers, Materials & Continua 2021年第12期69卷 3889-3902页

作者： Fahd N.Al-Wesabi Imran Khan Nadhem Nemri Mohammed A.Al-Hagery Huda g.Iskander Quang Ngoc Nguyen Babar Shah Ki-Il Kim Department of Computer Science King Khalid UniversityMuhayel AseerKSA Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Communications and Computer Engineering Faculty of Science and EngineeringWaseda UniversityShinjuku-kuTokyo169-0051Japan College of Technological Innovation Zayed UniversityAbu DhabiUAE Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

The Internet of Things(IoT)is the fourth technological revolution in the global information industry after computers,the Internet,and mobile communication *** combines radio-frequency identification devices,infrared sensors,global positioning systems,and various other *** sensing equipment is connected via the Internet,thus forming a vast *** these physical devices are connected to the Internet,the user terminal can be extended and expanded to exchange information,communicate with anything,and carry out identification,positioning,tracking,monitoring,and triggering of corresponding events on each device in the *** real life,the IoT has a wide range of applications,covering many fields,such as smart homes,smart logistics,fine agriculture and animal husbandry,national defense,and *** of the most significant factors in wireless channels is interference,which degrades the system *** the existing QR decomposition-based signal detection method is an emerging topic because of its low complexity,it does not solve the problem of poor detection ***,this study proposes a maximumlikelihood-based QR decomposition *** main idea is to estimate the initial level of detection using the maximum likelihood principle,and then the other layer is detected using a reliable *** optimal candidate is selected from the feedback by deploying the candidate points in an unreliable *** results show that the proposed algorithm effectively reduces the interference and propagation error compared with the algorithms reported in the literature.

关键词： 6g networks internet of things resource allocation optimization

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Analysis and Optimization on Partition-Based Caching and Delivery in Satellite-Terrestrial Edge Computing networks

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China Communications 2023年第3期20卷 252-285页

作者： Peng Wang Xing Zhang Jiaxin Zhang Shuang Zheng Wenhao Liu Wireless Signal Processing and Network Laboratory Key Laboratory of Universal Wireless CommunicationMinistry of EducationSchool of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China

As a viable component of 6g wireless communication architecture,satellite-terrestrial networks support efficient file delivery by leveraging the innate broadcast ability of satellite and the enhanced powerful file transmission approaches of multi-tier terrestrial *** the paper,we introduce edge computing technology into the satellite-terrestrial network and propose a partition-based cache and delivery strategy to make full use of the integrated resources and reducing the backhaul *** on the interference effect from varied nodes in different geographical distances,we derive the file successful transmission probability of the typical user and by utilizing the tool of stochastic *** the constraint of nodes cache space and file sets parameters,we propose a near-optimal partition-based cache and delivery strategy by optimizing the asymptotic successful transmission probability of the typical *** complex nonlinear programming problem is settled by jointly utilizing standard particle-based swarm optimization(PSO)method and greedy based multiple knapsack choice problem(MKCP)optimization *** results show that compared with the terrestrial only cache strategy,ground Popular Strategy,Satellite Popular Strategy,and Independent and identically distributed popularity strategy,the performance of the proposed scheme improve by 30.5%,9.3%,12.5%and 13.7%.

关键词： edge computing satellite terrestrial net-works caching deployment stochastic geometry 6g networks

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Intelligent Deep Learning Model for Privacy Preserving IIoT on 6g Environment

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Computers, Materials & Continua 2022年第7期72卷 333-348页

作者： Anwer Mustafa Hilal Jaber SAlzahrani Ibrahim Abunadi Nadhem Nemri Fahd NAl-Wesabi Abdelwahed Motwakel Ishfaq Yaseen Abu Sarwar Zamani Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Systems Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Systems King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer Science King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen

In recent times,Industrial Internet of Things(IIoT)experiences a high risk of cyber attacks which needs to be *** technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber *** blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network,the performance arrived at,in existing studies still needs *** this scenario,the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT(PPBDL-IIoT)on 6g *** proposed PPBDLIIoT technique aims at identifying the existence of intrusions in ***,PPBDL-IIoT technique also involves the design of Chaos game Optimization(CgO)with Bidirectional gated Recurrent Neural Network(BigRNN)technique for both detection and classification of intrusions in the ***,CgO technique is applied to fine tune the hyperparameters in BigRNN *** algorithm is applied to optimally adjust the learning rate,epoch count,and weight decay so as to considerably improve the intrusion detection performance of BigRNN ***,Blockchain enabled Integrity Check(BEIC)scheme is also introduced to avoid the misrouting attacks that tamper the OpenFlow rules of SDN-based IIoT *** performance of the proposed PPBDL-IIoT methodology was validated using Industrial Control System Cyber-attack(ICSCA)dataset and the outcomes were analysed under various *** experimental results highlight the supremacy of the presented PPBDL-IIoT technique than the recent state-of-the-art techniques with the higher accuracy of 91.50%.

关键词： 6g networks industrial iot blockchain security intrusion detection artificial intelligence

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Energy Aware Data Collection with Route Planning for 6g Enabled UAV Communication

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Computers, Materials & Continua 2022年第4期71卷 825-842页

作者： Mesfer Al Duhayyim Marwa Obayya Fahd N.Al-Wesabi Anwer Mustafa Hilal Mohammed Rizwanullah Majdy M.Eltahir Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Systems King Khalid UniversityMuhayel AseerSaudi Arabia

With technological advancements in 6g and Internet of Things(IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellularnetworks has become a hot research topic. At present, the proficient evolution of 6g networks allows the UAVs to offer cost-effective and timelysolutions for real-time applications such as medicine, tracking, surveillance,etc. Energy efficiency, data collection, and route planning are crucial processesto improve the network communication. These processes are highly difficultowing to high mobility, presence of non-stationary links, dynamic topology,and energy-restricted UAVs. With this motivation, the current research paperpresents a novel Energy Aware Data Collection with Routing Planning for6g-enabled UAV communication (EADCRP-6g) technique. The goal of theproposed EADCRP-6g technique is to conduct energy-efficient cluster-baseddata collection and optimal route planning for 6g-enabled UAV ***-6g technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) andorganize these clusters. Besides, Artificial Fish Swarm-based Route Planning(AFSRP) technique is applied to choose an optimum set of routes for UAVcommunication in 6g networks. In order to validated whether the proposedEADCRP-6g technique enhances the performance, a series of simulationswas performed and the outcomes were investigated under different *** experimental results showcase that the proposed model outperformed allother existing models under different evaluation parameters.

关键词： Unmanned aerial vehicle 6g networks artificial intelligence energy efficiency clustering route planning data collection metaheuristics

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Double-Edge Intelligent Integrated Satellite Terrestrial networks

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China Communications 2020年第9期17卷 128-146页

作者： Jiaxin Zhang Xing Zhang Peng Wang Liangjingrong Liu Yuanjun Wang Key Laboratory of Universal Wireless Communication Ministry of EducationSchool of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China

The efficient integration of satellite and terrestrial networks has become an important component for 6 g wireless architectures to provide highly reliable and secure connectivity over a wide geographical *** the satellite and cellular networks are developed separately these years,the integrated network should synergize the communication,storage,computation capabilities of both sides towards an intelligent system more than mere consideration of *** has motivated us to develop double-edge intelligent integrated satellite and terrestrial networks(DILIgENT).Leveraging the boost development of multi-access edge computing(MEC)technology and artificial intelligence(AI),the framework is entitled with the systematic learning and adaptive network management of satellite and cellular *** this article,we provide a brief review of the state-of-art contributions from the perspective of academic research and *** we present the overall design of the proposed DILIgENT architecture,where the advantages are discussed and *** of task offloading,content caching and distribution are *** results show that the proposed network architecture outperforms the existing integrated networks.

关键词： non-terrestrial networks edge intelligence integrated satellite and terrestrial networks task offloading content caching and distribution 6g networks

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