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Encryption with Image Steganography Based Data Hiding Technique in IIoT Environment

computers, Materials & Continua 2022年第7期72卷 1323-1338页

作者： Mahmoud Ragab Samah Alshehri Hani A.Alhadrami Faris Kateb Ehab Bahaudien Ashary SAbdel-khalek Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Department of Pharmacy Practice Faculty of PharmacyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesKing Abdulaziz UniversityJeddah21589Saudi Arabia Molecular Diagnostic Lab King Abdulaziz University HospitalKing Abdulaziz UniversityJeddah21589Saudi Arabia Special Infectious Agent Unit King Fahd Medical Research CenterKing Abdulaziz UniversityJeddah21589Saudi Arabia Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of ScienceSohag UniversitySohag82524Egypt

Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret ***,security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real ***,AI techniques can be utilized to design image steganographic techniques in *** addition,encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized *** order to accomplish secure data transmission in IIoT environment,this study presents novel encryption with image steganography based data hiding technique(EISDHT)for IIoT *** proposed EIS-DHT technique involves a new quantum black widow optimization(QBWO)to competently choose the pixel values for hiding secrete data in the cover *** addition,the multi-level discrete wavelet transform(DWT)based transformation process takes ***,the secret image is divided into three R,G,and B bands which are then individually encrypted using Blowfish,Twofish,and Lorenz Hyperchaotic *** last,the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover *** order to validate the enhanced data hiding performance of the EIS-DHT technique,a set of simulation analyses take place and the results are inspected interms of different *** experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.

关键词： IIoT security data hiding technique image steganography encryption secure communication

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Two Birds With One Stone: Enhancing Communication and Sensing via Multi-Functional RIS

arXiv

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arXiv 2024年

作者： Ni, Wanli Wang, Wen Zheng, Ailing Wang, Peng You, Changsheng Eldar, Yonina C. Niyato, Dusit Schober, Robert The Department of Electronic Engineering Tsinghua University Beijing100084 China The Pervasive Communications Center Purple Mountain Laboratories Nanjing211111 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China The Faculty of Mathematics and Computer Science Weizmann Institute of Science Israel The College of Computing and Data Science Nanyang Technological University Singapore Erlangen91054 Germany

In this article, we propose new network architectures that integrate multi-functional reconfigurable intelligent surfaces (MF-RISs) into 6G networks to enhance both communication and sensing capabilities. Firstly, we elaborate how to leverage MF-RISs for improving communication performance in different communication modes including unicast, mulitcast, and broadcast and for different multi-access schemes. Next, we emphasize synergistic benefits of integrating MF-RISs with wireless sensing, enabling more accurate and efficient target detection in 6G networks. Furthermore, we present two schemes that utilize MF-RISs to enhance the performance of integrated sensing and communication (ISAC). We also study multi-objective optimization to achieve the optimal trade-off between communication and sensing performance. Finally, we present numerical results to show the performance improvements offered by MF-RISs compared to conventional RISs in ISAC. We also outline key research directions for MF-RIS under the ambition of 6G. Copyright © 2024, The Authors. All rights reserved.

关键词： Reconfigurable architectures

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Enhancing Visual Surveillance on Smart Ships Through Integrated Image Deblurring and Object Detection

SSRN

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SSRN 2024年

作者： Feng, Hui Guo, Jundong Xu, Haixiang Du, Zhe Zhang, Yingju He, Yijing Cao, Guilin Ge, Shuzhi Sam Key Laboratory of High-Performance Ship Technology Wuhan University of Technology Ministry of Education Wuhan China School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan430063 China Wuhan University of Technology China Key Laboratory of High Performance Ship Technology of Ministry of Education Wuhan University of Technology Wuhan430063 China Department of Electrical & Computer Engineering National University of Singapore Singapore117576 Singapore

Smart ships commonly utilize visual measurement units, such as cameras, for environmental perception in the maritime domain, aimed at achieving advanced navigation capabilities. Characterized by the influence of wind, wave, and ocean current, smart ships navigating on maritime environment frequently encounter sway and motion disturbances, which subsequently introduce uncertainties to visual sensors, notably leading to motion blur in captured images. In order to mitigate the detrimental impact of motion blur on the visual obstacle detection algorithm employed in smart ships, we introduce IDD-GAN. Unlike conventional approaches, which treat motion deblurring and object detection as separate tasks, IDD-GAN integrates both processes, enabling end-to-end training and prediction through the use of generative adversarial networks. To address varying scales of motion blur caused by different levels of sensor interference, we have developed a multi-scale deblurring discriminator. Empirical results demonstrate the capability to achieve high-performance objectdetection even under conditions of motion blur. © 2024, The Authors. All rights reserved.

关键词： Ships

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Enhancing Resilience of Power Systems with Fuel Cell-Battery Hybrid Energy Storage System

Enhancing Resilience of Power Systems with Fuel Cell-Battery...

引用

Power science and Technology (ICPST), IEEE International Conference on

作者： Mingjian Tuo Muhoza Bertrand Cunzhi Zhao Mulan Zhang Hubei Key Laboratory of Energy Storage and Power Battery Hubei University of Automotive Technology Shiyan China College of Electrical & Information Hubei University of Automotive Technology Shiyan China Department of Engineering and Computer Science McNeese State University Lake Charles Louisiana USA Key Laboratory of Automotive Power Train and Electronics Hubei University of Automotive Technology Shiyan China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

The increasing penetration level of renewable energy resources (RES) has introduced a significant challenge on system frequency dynamics management. Batteries with fast dynamic response are widely used to regulate frequency fluctuation. Considering the degradation of batteries during constant charging and discharging process, it is practical to combine battery with other energy storage to support primary frequency. This paper investigates how hybrid energy storage system including fuel cell (FC) as main and battery as complementary power resources power source can be used to guarantee the frequency stability following the worst contingency while ensuring operational economy. A novel enhanced resilience constrained unit commitment (ER-SCUC) model is proposed to achieve efficient and coordinated utilization of battery energy storage system (BESS) and hydrogen energy storage system (HESS). The economic and low-carbon complementarity between green hydrogen and blue hydrogen are introduced. A case study of a modified IEEE-24 system demonstrates the effectiveness of the proposed ER-SCUC model.

关键词： Fluctuations Power system dynamics Fuel cells Power system stability Green hydrogen Hybrid power systems Stability analysis

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Exceeding Two Octave-Spanning Supercontinuum Generation in Integrated as2 S3 Waveguides Pumped by a 2 Μm Fiber Laser

SSRN

引用

SSRN 2024年

作者： Zhao, Peipei Yang, Lei Xia, Kai Yang, Peilong Wang, Rongping Xu, Peipeng Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Laboratory of Infrared Materials and Devices Advanced Technology Research Institute Ningbo University Zhejiang Ningbo315211 China Key Laboratory of Photoelectric Detection Materials and Devices of Zhejiang Province Ningbo315211 China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China Wuhan National Laboratory for Optoelectronics School of Physics Huazhong University of Science and Technology Wuhan China

In this work, we demonstrate over two octaves-spanning supercontinuum generation in integrated As2S3 chalcogenide glass waveguides pumped by a 2 μm femtosecond fiber laser. The pump laser provides 182 fs pulses at 50 MHz repetition rate. Through optimization of the waveguide dimensions, a broad supercontinuum spectrum spanning from 0.6 to 2.8 μm was achieved using a 4 μm wide, 5 mm long waveguide with 357 mW coupled pump power. The findings showcase the potential of dispersion engineered, integrated As2S3 photonics for realizing compact, efficient on-chip supercontinuum sources for mid-infrared applications. © 2024, The Authors. All rights reserved.

关键词： Pulse repetition rate

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Thermodynamic Energy Cost and Bit Error Rate of Imperfect Transmitters in Molecular Communication

Thermodynamic Energy Cost and Bit Error Rate of Imperfect Tr...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Dongliang Jing Lin Lin Andrew W. Eckford College of Mechanical and Electronic Engineering Northwest A&F University Yangling China Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs Yangling China College of Electronics and Information Engineering Tongji University Shanghai China Department of Electrical Engineering and Computer Science York University Toronto Ontario Canada

In some molecular communication (MC) designs, signaling molecules are held in reservoirs of different concentrations. This paper explores two thermodynamic implications of creating such a transmitter. First, it requires energy to generate reservoirs at different concentrations, since their chemical potential is different from the environment. Second, it requires an enormous energy cost to create a pure (or nearly pure) reservoir, so the transmitter is necessarily imperfect. Drawing from the Maxwell's Demon thought experiment, we consider the separation of an environmental mixture into reservoirs of differing concentrations, which requires free energy, but which allows information to be encoded in the difference of concentration. Both theoretical and simulation results indicate that the performance of the transmitter is positively correlated with the amount of consumed free energy. Furthermore, our simulation results indicate that there may be a fundamental thermodynamic tradeoff between energy per bit and bit error rate in MC.

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Mixture of Experts for Intelligent Networks: A Large Language Model-enabled Approach

Mixture of Experts for Intelligent Networks: A Large Languag...

引用

International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Hongyang Du Guangyuan Liu Yijing Lin Dusit Niyato Jiawen Kang Zehui Xiong Dong In Kim School of Computer Science and Engineering Nanyang Technological University Singapore Singapore State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of Automation Guangdong University of Technology and Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Optimizing various wireless user tasks poses a significant challenge for networking systems because of the expanding range of user requirements. Despite advancements in Deep Reinforcement Learning (DRL), the need for customized optimization tasks for individual users complicates developing and applying numerous DRL models, leading to substantial computation resource and energy consumption and can lead to inconsistent outcomes. To address this issue, we propose a novel approach utilizing a Mixture of Experts (MoE) framework, augmented with Large Language Models (LLMs), to analyze user objectives and constraints effectively, select specialized DRL experts, and weigh each decision from the participating experts. Specifically, we develop a gate network to oversee the expert models, allowing a collective of experts to tackle a wide array of new tasks. Furthermore, we innovatively substitute the traditional gate network with an LLM, leveraging its advanced reasoning capabilities to manage expert model selection for joint decisions. Our proposed method reduces the need to train new DRL models for each unique optimization problem, decreasing energy consumption and AI model implementation costs. The LLMenabled MoE approach is validated through a general maze navigation task and a specific network service provider utility maximization task, demonstrating its effectiveness and practical applicability in optimizing complex networking systems.

关键词： Wireless communication Energy consumption Navigation Computational modeling Logic gates Probability Throughput

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Performance optimization of microbial electrolysis cell (MEC) for palm oil mill effluent (POME) wastewater treatment and sustainable Bio-H2 production using response surface methodology (RSM)

引用

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2022年第34期47卷 15464-15479页

作者： Chandrasekhar, Abudukeremu Kadier ab Junying Wang ab K. Wang, Junying Chandrasekhar, K. Abdeshahian, Peyman Islam, M. Amirul Ghanbari, Farshid Bajpai, Mukul Katoch, Surjit Singh Bhagawati, Prashant Basavaraj Li, Hui Kalil, Mohd Sahaid Hamid, Aidil Abdul Abu Hasan, Hassimi Ma, Peng-Cheng [a]Laboratory of Environmental Science and Technology The Xinjiang Technical Institute of Physics and Chemistry Key Laboratory of Functional Materials and Devices for Special Environments Chinese Academy of Sciences Urumqi 830011 China [b]Center of Material and Opto-electronic Research University of Chinese Academy of Sciences Beijing 100049 China [c]School of Civil and Environmental Engineering Yonsei University Seoul 03722 Republic of Korea [d]Department of Biotechnology Engineering School of Lorena University of São Paulo São Paulo 12602-810 Brazil [e]Laboratory for Quantum Semiconductors and Photon-based BioNanotechnology Department of Electrical and Computer Engineering Faculty of Engineering Université de Sherbrooke Sherbrooke Québec J1K 2R1 Canada [f]Research Center for Environmental Contaminants (RCEC) Abadan University of Medical Sciences Abadan Iran [g]Environmental Engineering Lab Civil Engineering Department National Institute of Technology Hamirpur Hamirpur Himachal Pradesh 177005 India [h]Faculty of Engineering Department of Civil Engineering Annasaheb Dange College of Engineering and Technology Ashta Maharashtra 416301 India [i]Department of Chemical and Process Engineering Faculty of Engineering and Built Environment National University of Malaysia (UKM) UKM Bangi 43600 Selangor Malaysia [j]School of Biosciences and Biotechnology Faculty of Science and Technology National University of Malaysia (UKM) UKM Bangi 43600 Selangor Malaysia [k]Research Centre for Sustainable Process Technology Faculty of Engineering and Built Environment National University of Malaysia (UKM) UKM Bangi 43600 Selangor Malaysia

Microbial electrolysis cells (MECs) are a new bio-electrochemical method for converting organic matter to hydrogen gas (H-2). Palm oil mill effluent (POME) is hazardous wastewater that is mostly formed during the crude oil extraction process in the palm oil industry. In the present study, POME was used in the MEC system for hydrogen generation as a feasible treatment technology. To enhance biohydrogen generation from POME in the MEC, an empirical model was generated using response surface methodology (RSM). A central composite design (CCD) was utilized to perform twenty experimental runs of MEC given three important variables, namely incubation temperature, initial pH, and influent dilution rate. Experimental results from CCD showed that an average value of 1.16 m(3) H-2/m(3) d for maximum hydrogen production rate (HPR) was produced. A second-order polynomial model was adjusted to the experimental results from CCD. The regression model showed that the quadratic term of all variables tested had a highly significant effect (P < 0.01) on maximum HPR as a defined response. The analysis of the empirical model revealed that the optimal conditions for maximum HPR were incubation temperature, initial pH, and influent dilution rate of 30.23 ?, 6.63, and 50.71%, respectively. Generated regression model predicted a maximum HPR of 1.1659 m(3) H-2/m(3) d could be generated under optimum conditions. Confirmation experimentation was conducted in the optimal conditions determined. Experimental results of the validation test showed that a maximum HPR of 1.1747 m(3) H-2/m(3) d was produced. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Microbial electrolysis cell (MEC) Hydrogen production Palm oil mill effluent (POME) Wastewater Optimization Response surface methodology (RSM)

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Diffusion-Driven Semantic Communication for Generative Models with Bandwidth Constraints

arXiv

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arXiv 2024年

作者： Guo, Lei Chen, Wei Sun, Yuxuan Ai, Bo Pappas, Nikolaos Quek, Tony State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Department of Computer and Information Science Linköping University Linköping Sweden Information Systems Technology and Design Singapore University of Technology and Design Singapore Singapore

Diffusion models have been extensively utilized in AI-generated content (AIGC) in recent years, thanks to the superior generation capabilities. Combining with semantic communications, diffusion models are used for tasks such as denoising, data reconstruction, and content generation. However, existing diffusion-based generative models do not consider the stringent bandwidth limitation, which limits its application in wireless communication. This paper introduces a diffusion-driven semantic communication framework with advanced VAE-based compression for bandwidth-constrained generative model. Our designed architecture utilizes the diffusion model, where the signal transmission process through the wireless channel acts as the forward process in diffusion. To reduce bandwidth requirements, we incorporate a downsampling module and a paired upsampling module based on a variational auto-encoder with reparameterization at the receiver to ensure that the recovered features conform to the Gaussian distribution. Furthermore, we derive the loss function for our proposed system and evaluate its performance through comprehensive experiments. Our experimental results demonstrate significant improvements in pixel-level metrics such as peak signal to noise ratio (PSNR) and semantic metrics like learned perceptual image patch similarity (LPIPS). These enhancements are more profound regarding the compression rates and SNR compared to deep joint source-channel coding (DJSCC). Copyright © 2024, The Authors. All rights reserved.

关键词： Bandwidth

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Cooperative Deep $Q$-learning Framework for Environments Providing Image Feedback

arXiv

引用

arXiv 2021年

作者： Raghavan, Krishnan Narayanan, Vignesh Jagannathan, Sarangapani Mathematics and Computer Science Division Argonne National Laboratory United States AIISC The Department of Computer Science and Engineering University of South Carolina Columbia United States Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO United States

In this paper, we address two key challenges in deep reinforcement learning setting, sample inefficiency and slow learning, with a dual NN-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the error-driven learning (EDL) regime is an approximation of the empirical cost and the approximation error reduces as learning progresses, irrespective of the size of the network. Using simulation analysis, we show that the proposed methods enables faster learning and convergence and requires reduced buffer size (thereby increasing the sample efficiency). © 2021, CC0.

关键词： Reinforcement learning

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