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A comprehensive survey on 6G-security: physical connection and service layers

Discover Internet of Things 2025年第1期5卷 1-30页

作者： Saeed, Mamoon M. Saeed, Rashid A. Hasan, Mohammad Kamrul Ali, Elmustafa Sayed Mazha, Tehseen Shahzad, Tariq Khan, Sunawar Hamam, Habib Sana00967 Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electronics Engineering College of Electronics Engineering Sudan University of Science and Technology Omdurman Sudan Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Red Sea University Port Sudan33312 Sudan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Computer Science and Software Engineering International Islamic University Islamabad44000 Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa BP 1989 Av. Grandes Ecoles Libreville Gabon Bridges for Academic Excellence-Spectrum Tunis Tunisia Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations. © The Author(s) 2025.

关键词： 5G mobile communication systems

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Time-Division Online Speculative Inference for Cost-Effective Intelligent Internet of Things 10

Time-Division Online Speculative Inference for Cost-Effectiv...

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Du, Yao Wang, Zehua Leung, Cyril Leung, Victor C.M. The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

ISBN: (纸本)9798350373011

Intelligent Internet of Things (IIoT), a network paradigm, is an interconnection of intelligent edge devices, empowered by machine learning models. The recent emergence of large language models (LLMs) opens a new path towards IIoT. Although device models are generally lightweight and suitable for edge devices with limited processing power, their performance is less impressive compared to LLMs running on large servers. Server models offer superior performance with the cost of significant computational resources for model inference. To realize cost-effective IIoT, we introduce a novel collaborative inference framework: the online speculative inference enabled by device collaboration and time divisions. We aim to find the minimum number of servers required for the immediate processing of arrived inference requests. To solve the problem, we propose an evolving directed acyclic graph along with a Proof-of-Deletion mechanism for cost reduction and privacy protection. Based on computer simulations using heterogeneous LLMs, it is found that time-division online speculative inference is a promising approach towards cost-effective IIoT. © 2024 IEEE.

关键词： Adversarial machine learning

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A Novel Conditional Medical Image Generation GAN with Latent Space Optimal Transport 1

A Novel Conditional Medical Image Generation GAN with Latent...

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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Wang, Jun Lei, Bohan Xu, Xiaoyin Zhuang, Yueting Zhang, Min School of Software Technology Zhejiang University Ningbo China College of Computer Science & Technology Zhejiang University Hangzhou China College of Biomedical Engineering & Instrument Science Zhejiang University Hangzhou China

ISBN: (纸本)9798350358780

Generative adversarial network (GAN) is widely used to augment training set in medical imaging. However, training GANs can be challenging, as they are susceptible to mode collapse. These challenges stem from the fact that deep neural networks can only represent continuous mappings, while in GAN, the generator aims to compute discontinuous transportation maps between the noise distribution and the data distribution. We propose a novel approach that can overcome mode collapse, and in turn, lead to improved capability by GAN to generate specific classes of medical images. Our method starts by mapping the data manifold to the latent space using an autoencoder (AE). Subsequently, we encode the sample labels and integrate them with the latent representations. Next, we employ extended semi-discrete optimal transport (SDOT) mapping, which maps a Gaussian distribution to the empirical latent distribution, thereby generating new latent representations with known labels. Finally, we employ GAN to establish the mapping from the continuous latent distribution induced by the extended SDOT mapping to the real data distribution, generating high-quality images. We conducted extensive experiments on the DermaMNIST and BloodMNIST datasets. The experimental results highlight the exceptional performance of our model in generating images belonging to specified classes. © 2023 IEEE.

关键词： Generative adversarial networks

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Mask Wearing Detection System for Epidemic Control Based on STM32 6th

Mask Wearing Detection System for Epidemic Control Based on ...

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6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Luoli Yadav, Amit Khan, Asif Varish, Naushad Singh, Priyanka Thakkar, Hiren Kumar Department of Computer and Software Chengdu Neusoft University Chengdu China College of Engineering IT and Environment Charles Darwin University DarwinNT Australia Department of Computer Application Integral University Lucknow India Department of Computer Science and Engineering GITAM University Hyderabad502329 India Department of Computer Science and Engineering SRM University Andhra Pradesh Amravati522502 India Department of Computer Science and Engineering Pandit Deendayal Energy Univrsity Gujarat Gandhinagar382007 India

ISBN: (纸本)9789819940707

This paper designs an epidemic prevention and control mask wearing detection system based on STM32, which is used to monitor the situation of people wearing masks. Tiny-YOLO detection algorithm is adopted in the system, combined with image recognition technology, and two kinds of image data with and without masks are used for network training. Then, the trained model can be used to carry out real-time automatic supervision on the wearing of masks in the surveillance video. When the wrong wearing or not wearing masks are detected, the buzzer will send an alarm, so as to effectively monitor the wearing of masks and remind relevant personnel to wear masks correctly. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Image recognition

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NPBMT: A Novel and Proficient Buffer Management Technique for Internet of Vehicle-Based DTNs

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computers, Materials & Continua 2023年第10期77卷 1303-1323页

作者： Sikandar Khan Khalid Saeed Muhammad Faran Majeed Salman A.AlQahtani Khursheed Aurangzeb Muhammad Shahid Anwar Department of Computer Science Shaheed Benazir Bhutto University SheringalDir(U)Khyber Pakhtunkhwa18200Pakistan Department of Computer Science Kohsar University MurreePunjab47150Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of AI and Software Gachon UniversitySeongnam-si13120South Korea

Delay Tolerant Networks(DTNs)have the major problem of message delay in the network due to a lack of endto-end connectivity between the nodes,especially when the nodes are *** nodes in DTNs have limited buffer storage for storing delayed *** instantaneous sharing of data creates a low buffer/shortage ***,buffer congestion would occur and there would be no more space available in the buffer for the upcoming *** address this problem a buffer management policy is proposed named“A Novel and Proficient Buffer Management Technique(NPBMT)for the Internet of Vehicle-Based DTNs”.NPBMT combines appropriate-size messages with the lowest Time-to-Live(TTL)and then drops a combination of the appropriate messages to accommodate the newly arrived *** evaluate the performance of the proposed technique comparison is done with Drop Oldest(DOL),Size Aware Drop(SAD),and Drop Larges(DLA).The proposed technique is implemented in the Opportunistic Network Environment(ONE)*** shortest path mapbased movement model has been used as the movement path model for the nodes with the epidemic routing *** the simulation results,a significant change has been observed in the delivery probability as the proposed policy delivered 380 messages,DOL delivered 186 messages,SAD delivered 190 messages,and DLA delivered only 95 messages.A significant decrease has been observed in the overhead ratio,as the SAD overhead ratio is 324.37,DLA overhead ratio is 266.74,and DOL and NPBMT overhead ratios are 141.89 and 52.85,respectively,which reveals a significant reduction of overhead ratio in NPBMT as compared to existing *** network latency average of DOL is 7785.5,DLA is 5898.42,and SAD is 5789.43 whereas the NPBMT latency average is *** reveals that the proposed policy keeps the messages for a short time in the network,which reduces the overhead ratio.

关键词： Delay tolerant networks buffer management message drop policy ONE simulator NPBMT

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Cost-Effective Authenticated Solution (CAS) for 6G-Enabled Artificial Intelligence of Medical Things (AIoMT)

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IEEE Internet of Things Journal 2024年第13期11卷 23977-23984页

作者： Mahmood, Khalid Obaidat, Mohammad S. Shamshad, Salman Alenazi, Mohammed J. F. Kumar, Gulshan Anisi, Mohammad Hossein Conti, Mauro National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Jordan King Abdullah II School of Information Technology Amman11942 Jordan University of Science and Technology Beijing School of Communication and Computing Engineering Beijing100083 China Amity University Amity School of Engineering and Technology Noida201301 India University of Lahore Department of Software Engineering Lahore54590 Pakistan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh12311 Saudi Arabia University of Padua Department of Mathematics Padua35131 Italy Lovely Professional University Department of Computer Science and Engineering Phagwara144411 India University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

The Internet of Things (IoT) is a network of interconnected objects, which congregate and exchange gigantic amounts of data. Usually, predeployed embedded sensors sense this massive data. Soon, several applications of IoT are anticipated to exploit emerging 6G technology. Healthcare is one of them, where the 6G-inspired paradigm may facilitate the users to exchange information through hundreds of sensors under the assumption of Artificial Intelligence of Things (AIoT). Integration of medical sensors with AIoT is known as Artificial Intelligence of Medical Things (AIoMT). The secure and seamless interactions among 6G-enabled AIoMT users should be the primary challenge. Furthermore, resource-constrained wearable sensing devices, with their inability to execute complex security solutions, provide an ideal attraction for malicious entities to launch diverse attacks. These challenges have motivated us to design a cost-effective authenticated solution (CAS) for 6G-enabled AIoMT healthcare applications. Our CAS protocol not only prevents cyber threats like impersonation session key secrecy but it can also prevent physical threats like hardware tampering. We observe formal and informal security validations to endorse its robustness and effectiveness. Performance comparison reveals that the CAS protocol offers maximum security enrichment. Moreover, CAS is cost-effective as it has achieved 33% and 60% reduction in computation and communication overheads, respectively, compared to contemporary competing related protocols. © 2014 IEEE.

关键词： Authentication

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Weber Law Based Approach for Multi-Class Image Forgery Detection

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computers, Materials & Continua 2024年第1期78卷 145-166页

作者： Arslan Akram Javed Rashid Arfan Jaffar Fahima Hajjej Waseem Iqbal Nadeem Sarwar Department of Computer Science Superior UniversityLahore54000Pakistan Information Technology Services University of OkaraOkara56300Pakistan Departmet of Computer Science MLC LabOkara56300Pakistan Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science Bahria UniversityLahore CampusLahore54600Pakistan

Today’s forensic science introduces a new research area for digital image analysis formultimedia ***,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered *** forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing ***,an image can contain one or more types of *** study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial ***,images are divided into equal blocks to get scale-invariant *** law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing *** proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and ***(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and *** average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

关键词： Copy-Move and splicing non-overlapping block division texture features weber law spatial domain xgboost

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Arithmetic Expression Evaluations with Membranes

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Chinese Journal of Electronics 2025年第1期23卷 55-60页

作者： Ping Guo Haizhu Chen Hui Zheng College of Computer Science Chongqing University Chongqing China Chongqing Key Laboratory of Software Theory and Technology Chongqing China Department of Software Engineering Chongqing College of Electronic Engineering Chongqing China

Arithmetic operations and expression evaluations are fundamental in computing models. This paper firstly designs arithmetic membranes without priority rules for basic arithmetic operations, and then proposes an algorithm to construct expression P systems based on several of such membranes after designing synchronous and asynchronous transmission strategies among the membranes. For any arithmetic expression, an expression P system can be built to evaluate it effectively. Finally, we discuss different parallelism strategies through which different expression P systems can be built for an arithmetic expression.

关键词： Computational modeling Biological system modeling Parallel processing Biomembranes Compounds Arithmetic

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Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

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computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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Optimizing Weighted Ensemble ML IDS Using Parallelization and Batch Learning in Healthcare Networks

Optimizing Weighted Ensemble ML IDS Using Parallelization an...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Ward, Blake Gonzalez, Daniel Alt, Jake Fang, Dongfeng Xu, Shengjie The Department of Computer Science and Software Engineering College of Engineering California Polytechnic State University San Luis ObispoCA93407 United States The Department of Cyber Intelligence and Information Operations College of Applied Science and Technology University of Arizona TucsonAZ85721 United States

ISBN: (纸本)9798350350548

The increasing adoption of IoT devices in healthcare necessitates the development of lightweight and fast intrusion detection systems (IDS). This paper proposes a weighted ensemble ML IDS with parallelized batch learning to optimize runtime while maintaining ML performance. The proposed method is compared to other solutions, evaluating ML performance and runtime across three different datasets. Experimental results demonstrate that although batch learning introduces feedback delay that slightly degrades ML performance, parallel computing significantly reduces runtime. © 2024 IEEE.

关键词： Network intrusion

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