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IoT-Cloud Assisted Botnet Detection Using Rat Swarm Optimizer with Deep Learning

computers, Materials & Continua 2023年第2期74卷 3085-3100页

作者： Saeed Masoud Alshahrani Fatma S.Alrayes Hamed Alqahtani Jaber S.Alzahrani Mohammed Maray Sana Alazwari Mohamed A.Shamseldin Mesfer Al Duhayyim Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Mechanical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Nowadays,Internet of Things(IoT)has penetrated all facets of human life while on the other hand,IoT devices are heavily prone to *** has become important to develop an accurate system that can detect malicious attacks on IoT environments in order to mitigate security *** is one of the dreadfulmalicious entities that has affected many users for the past few *** is challenging to recognize Botnet since it has excellent carrying and hidden *** approaches have been employed to identify the source of Botnet at earlier *** Learning(ML)and Deep Learning(DL)techniques are developed based on heavy influence from Botnet detection *** spite of this,it is still a challenging task to detect Botnet at early stages due to low number of features accessible from Botnet *** current study devises IoT with Cloud Assisted Botnet Detection and Classification utilizingRat SwarmOptimizer with Deep Learning(BDC-RSODL)*** presented BDC-RSODL model includes a series of processes like pre-processing,feature subset selection,classification,and parameter ***,the network data is pre-processed to make it compatible for further ***,RSO algorithm is exploited for effective selection of subset of ***,Long Short TermMemory(LSTM)algorithm is utilized for both identification and classification of ***,Sine Cosine Algorithm(SCA)is executed for fine-tuning the hyperparameters related to LSTM *** order to validate the promising 3086 CMC,2023,vol.74,no.2 performance of BDC-RSODL system,a comprehensive comparison analysis was *** obtained results confirmed the supremacy of BDCRSODL model over recent approaches.

关键词： Internet of things cloud computing long short termmemory deep learning sine cosine algorithm feature selection

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Secrecy Capacity Analysis with Imperfect Channel State Information and Varying Interference for 6G C-V2X Communication 10

Secrecy Capacity Analysis with Imperfect Channel State Infor...

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10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023

作者： Ayaz, Hina Abbas, Ghulam Abbas, Ziaul Haq Waqas, Muhammad Gik Institute of Engineering Sciences and Technology Facutly of Computer Science and Engineering Topi23460 Pakistan Research Center Topi23460 Pakistan University of Bahrain College of Information Technology Computer Engineering Department 32038 Bahrain

ISBN: (纸本)9798350329674

It has been observed that the use of radio-frequency fingerprinting (RF-FP) for location estimation (LE) of vehicles can significantly improve secrecy capacity (SC) for urban scenarios in 6th generation cellular vehicle-to-everything (6G C-V2X) communication. However, in most of the literature, interference is considered constant for simplicity. Thus, there is a need to investigate the impact of varying levels of interference and incomplete channel state information (CSI) on the performance of SC. This study examines the impact of shadowing and interference in the presence of heavy traffic and obstructions. We have proposed a technique that analyzes the effects of varying levels of interference for LE via RF-FP to improve SC with incomplete CSI. Simulation results demonstrate that interference has a significant impact on SC which depends on the distance and location of the eavesdropping vehicle. However, a decrease in SC is not solely caused by the increase in interference, since other factors, such as the speed and relative position of the illegitimate vehicles as well as incomplete CSI, can also significantly affect the SC performance, as demonstrated through simulations. © 2023 IEEE.

关键词： Vehicle to Everything

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An Immune-Inspired Approach with Interval Allocation in Solving Multimodal Multi-Objective Optimization Problems with Local Pareto Sets

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computers, Materials & Continua 2024年第6期79卷 4237-4257页

作者： Weiwei Zhang Jiaqiang Li Chao Wang Meng Li Zhi Rao College of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450001China Technology Research and Development Center Jilin Tobacco Industry Company LimitedChangchun130031China College of Tobacco Science and Engineering Zhengzhou University of Light IndustryZhengzhou450001China Raw Material Department Hongyun Honghe Tobacco(Group)CompanyKunming650202China

In practical engineering,multi-objective optimization often encounters situations where multiple Pareto sets(PS)in the decision space correspond to the same Pareto front(PF)in the objective space,known as Multi-Modal Multi-Objective Optimization Problems(MMOP).Locating multiple equivalent global PSs poses a significant challenge in real-world applications,especially considering the existence of local *** identifying and locating both global and local PSs is a major *** tackle this issue,we introduce an immune-inspired reproduction strategy designed to produce more offspring in less crowded,promising regions and regulate the number of offspring in areas that have been thoroughly *** approach achieves a balanced trade-off between exploration and ***,we present an interval allocation strategy that adaptively assigns fitness levels to each *** strategy ensures a broader survival margin for solutions in their initial stages and progressively amplifies the differences in individual fitness values as the population matures,thus fostering better population ***,we incorporate a multi-population mechanism that precisely manages each subpopulation through the interval allocation strategy,ensuring the preservation of both global and local *** results on 21 test problems,encompassing both global and local PSs,are compared with eight state-of-the-art multimodal multi-objective optimization *** results demonstrate the effectiveness of our proposed algorithm in simultaneously identifying global Pareto sets and locally high-quality PSs.

关键词： Multimodal multi-objective optimization problem local PSs immune-inspired reproduction

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Design and mechanism insight on SiC quantum dots sensitized inverse opal TiO_(2) with superior photocatalytic activities under sunlight

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Frontiers of Chemical science and engineering 2023年第12期17卷 1913-1924页

作者： Yingchao He Qiong Sun Likun Sun Zhixing Gan Liyan Yu Lifeng Dong College of Materials Science and Engineering Qingdao University of Science and TechnologyQingdao 266042China Center for Future Optoelectronic Functional Materials School of Computer and Electronic InformationNanjing Normal UniversityNanjing 210023China Department of Physics Hamline UniversitySt.PaulMN 55104USA

The combination of SiC quantum dots sensitized inverse opal TiO_(2) photocatalyst is designed in this work and then applied in wastewater purification under simulated *** various spectroscopic techniques,it is found that electrons transfer directionally from SiC quantum dots to inverse opal TiO_(2),and the energy difference between their conduction/valence bands can reduce the recombination rate of photogenerated carriers and provide a pathway with low interfacial resistance for charge transfer inside the *** a result,a typical type-II mechanism is proved to dominate the photoinduced charge transfer ***,the composite achieves excellent photocatalytic performances(the highest apparent kinetic constant of 0.037 min^(-1)),which is 6.2 times(0.006 min^(-1))and 2.1 times(0.018 min^(-1))of the bare inverse opal TiO_(2) and commercial P25 ***,the stability and non-toxicity of SiC quantum dots sensitized inverse opal TiO_(2) composite enables it with great potential in practical photocatalytic applications.

关键词： inverse opal TiO_(2) silicon carbide quantum dots quantum dot sensitized photocatalyst type-II charge transfer route

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Color image restoration by filtering methods: a review

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Soft Computing 2024年第13-14期28卷 7755-7782页

作者： Salamat, Nadeem Missen, Malik Muhammad Saad Akhtar, Nadeem Mustahsan, Muhammad Surya Prasath, V.B. Department of Mathematics Khawaja Fareed University of Engineering and Information Technology Rahim Yar Khan64200 Pakistan Department of Computer Science and IT The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Computer Science Pediatrics and Biomedical Informatics University of Cincinnati CincinnatiOH45221 United States

digital images are corrupted with noise, and image denoising is an important step in image processing modules. In this review, the latest developments in filtering methods for color image restoration are analyzed. These algorithms are compared in terms of objective image quality measures and divided into major classes, such as spatial domain, switching and wavelet filtering methods. These classes are based on the particular methodology used in image denoising algorithms and further subdivided to show their classification in terms of noise models utilized, application style, and stages the filters applied in images. In particular, we present a review of filtering methods in color image denoising, published over the past two decades. Our classification and succinct descriptions of color image restoration by these mathematical filtering techniques and their characterizations can help choose the appropriate ones for various downstream image processing tasks. © The Author(s) 2024.

关键词： Restoration

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Empowering Smart Homes with Fog Computing for IoT Connectivity

Empowering Smart Homes with Fog Computing for IoT Connectivi...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Mahdi, Ali Jafer Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq AI-Zahraa University for Women Department of Scientific Affairs Bangi43600 Malaysia College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Innovative grid technology leverages Information and Communication technology (ICT) to enhance energy efficiency and mitigate losses. This paper introduces a 'novel three-tier hierarchical framework for smart homes within the Internet of Things (IoT)' ecosystem, addressing the current shortage of intelligent solutions that underutilize IoT advantages. Our framework's primary objective is to elevate smart homes to the microgrid level, enabling the seamless integration from the microgrid's renewable distributed energy sources and attaining maximum energy efficiency. In addition to traditional data processing, we propose the application of fog computing in smart homes. Through a rigorous simulation using real smart meter datasets, our study demonstrates that fog computing, mainly when using predictive filtering, may drastically cut down on the amount of data being sent and the load on the home's network. This innovation holds immense potential for revolutionizing energy management and resource allocation in the context of smart homes, thus contributing to a sustainable and efficient future. This research represents a critical step towards harnessing the power of IoT and fog computing in smart grids and homes, offering a promising path towards more intelligent, eco-friendly, and energy-efficient living spaces. © 2024 IEEE.

关键词： Smart homes

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A Multilayered Process Framework for Predicting Students’ Academic Performance in Open and Distance Learning 3rd

A Multilayered Process Framework for Predicting Students’ A...

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3rd International Conference on Smart Technologies and Innovation Management, MTYMEX 2024

作者： Adewale, M.D. Azeta, A. Abayomi-Alli, A. Sambo-Magaji, A. Africa Centre of Excellence on Technology Enhanced Learning National Open University of Nigeria Abuja Nigeria Department of Software Engineering Namibia University of Science and Technology Windhoek Namibia Department of Computer Science Federal University of Agriculture Abeokuta Nigeria Digital Literacy & Capacity Development Department National Information Technology Development Agency Abuja Nigeria

ISBN: (纸本)9783031649561

As Artificial Intelligence (AI) becomes increasingly integral to education, particularly in Open and Distance Learning (ODL), educators, policymakers, and AI developers need to understand its extensive effects. Harnessing AI’s full potential in ODL requires an intricate understanding of its multi-faceted implications—a challenge taken up by this research. This research aims to introduce a Multilayered Process Framework for Predicting Students’ Academic Performance in Open and Distance Learning. The framework’s design progresses from theoretical modelling to advanced predictive analytics, with each layer building on the previous to ensure a cohesive analytical process. It incorporates rigorous validation checks to maintain predictive accuracy and reliability. The study culminates in a comparative analysis to identify the most effective predictive methodology, emphasising the framework’s dynamic adaptability and commitment to continuous improvement based on empirical evidence and theoretical insights. Aligned with UNESCO’s 2030 vision, it underscores the framework’s versatility across different educational landscapes and its commitment to inclusive education. It paves the way for future research focused on leveraging AI to universalise quality education, highlighting the potential of AI to transform educational technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive analytics

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LOPO: An Out-of-order Layer Pulling Orchestration Strategy for Fast Microservice Startup 42

LOPO: An Out-of-order Layer Pulling Orchestration Strategy f...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Gu, Lin Huang, Junhao Huang, Shaoxing Zeng, Deze Li, Bo Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan China China University of Geosciences School of Computer Science Wuhan China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350334142

Container based microservices have been widely applied to promote the cloud elasticity. The mainstream Docker containers are structured in layers, which are organized in stack with bottom-up dependency. To start a microservice, the required layers are pulled from a remote registry and stored on its host server, following the layer dependency order. This incurs long microservice startup time and hinders the performance efficiency. In this paper, we discover that, for the first time, the layer pulling order can be adjusted to accelerate the microservice startup. Specifically, we address the problem on microservice layer pulling orchestration for startup time minimization and prove it as NP-hard. We propose a Longest-chain based Out-of-order layer Pulling Orchestration (LOPO) strategy with low computational complexity and guaranteed approximation ratio. Through extensive real-world trace driven experiments, we verify the efficiency of our LOPO and demonstrate that it reduces the microservice startup time by 22.71% on average in comparison with state-of-the-art solutions. © 2023 IEEE.

关键词： Containers

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Automatic recognition of depression based on audio and video:A review

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World Journal of Psychiatry 2024年第2期14卷 225-233页

作者： Meng-Meng Han Xing-Yun Li Xin-Yu Yi Yun-Shao Zheng Wei-Li Xia Ya-Fei Liu Qing-Xiang Wang Shandong Mental Health Center Shandong UniversityJinan 250014Shandong ProvinceChina Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353Shandong ProvinceChina Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and TechnologyQilu University of Technology(Shandong Academy of Sciences)Jinan 250353Shandong ProvinceChina Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer ScienceJinan 250353Shandong ProvinceChina Department of Ward Two Shandong Mental Health CenterShandong UniversityJinan 250014Shandong ProvinceChina

Depression is a common mental health *** current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression ***-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively *** physicians usually require extensive training and experience to capture changes in these *** in deep learning technology have provided technical support for capturing non-biological *** researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression *** article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.

关键词： Depression recognition Deep learning Automatic depression estimation System Audio processing Image processing Feature fusion Future development

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Performance Creativity Enhancement Method Based on Emotional Analysis and Concentration

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第3期8卷 1019-1048页

作者： Liu, Chang Zhang, Longfei Huang, Tianyu Wu, Yufeng Zhang, Fuquan Lin, Qi Department of Computer Science and Technology Beijing Institute of Technology 100081 China Beijing Key Laboratory of Digital Performance and Simulation Technology 100081 China College of Computer and Control Engineering Minjiang University Fuzhou350108 China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu610021 China Informatics King’s College London LondonWC2R 2LS United Kingdom

Intelligent performance creativity is a new research direction of the intersection of technology and art. At present, the cutting-edge technologies such as computer simulation, emotional computing and machine learning have been applied to the evaluation and enhancement of intelligent performance creativity. The application of these technologies has greatly increased the diversity of performance forms and the complexity of performance content. For the traditional stage performance, due to the lack of timely feedback from the audience, it is difficult for the director to enhance the creativity effec-tively. In order to solve this problem, this paper proposes concentration level enhancement method (CLEM). The CLEM extracts and analyzes the physiological and emotional characteristics of the audience by collecting the multimodal physiological signal data of the audience. Through the analysis of the features, the concentration information of the audience is obtained and the concentration level (CL) is defined. Based on the physiological and emotional induction mechanism, a performance creativity enhancement strategy is proposed, which enhances the performance creativity in two aspects: " Visual-based" and " Content-based". Through the concentration level enhancement method, compare the audience’s performance attention changes before and after the performance creativity enhancement, select the effective strategies to enhance the performance creativity, and provide the director with quantifiable performance creativity enhancement feedback results. The experimental results show that the CLEM proposed in this paper can effectively induce significant changes in the audience’s emotion, and the selected creative enhancement strategy can significantly improve the audience’s concentration and achieve the purpose of enhancing the creativity of the performance. © 2023, Journal of Network Intelligence.

关键词： Physiology

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