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Physical Layer Security for CR-NOMA Network with Cooperative Jamming

Tsinghua Science and Technology 2025年第2期30卷 708-720页

作者： Meiling Li Peng Xue Hu Yuan Yuxing Han School of Electronics Information Engineering Taiyuan University of Science and TechnologyTaiyuan 030024China School of Computer Science and Mathematics Kingston UniversityLondonKT12EEUK Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China

Cooperative jamming can effectively combat eavesdropping in physical layer security communication without affecting the legal receiver and improve the security performance of the *** paper introduces cooperative jamming to cognitive radio(CR)networks with non-orthogonal multiple access(NOMA)*** secure performance of the considered CR and NOMA(CR-NOMA)network is evaluated using two modes:non-cooperative jamming and cooperative *** particular,the secrecy outage probabilities(SOPs)of the primary user(PU)in the two modes are derived under Rician fading channels,based on which,the influences of the transmission signal-to-noise ratio(SNR)of secondary users(SUs),the number of SUs,the secrecy rate,and the power allocation coefficient on the SOPs of PU are analyzed *** analysis and simulation results show that cooperative jamming effectively prevents eavesdropping behaviour,which reduces the SOP of PU compared to non-cooperative *** also show that the transmission SNR,the number of SUs,the secrecy rate,and the power distribution coefficients greatly influence performance improvement.

关键词： cognitive radio non-orthogonal multiple access physical layer security cooperative jamming

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LIDAR:learning from imperfect demonstrations with advantage rectification

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Frontiers of computer Science 2022年第1期16卷 57-66页

作者： Xiaoqin ZHANG Huimin MA Xiong LUO Jian YUAN Department of EE Tsinghua UniversityBeijing100084China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China

In actor-critic reinforcement learning(RL)algorithms,function estimation errors are known to cause ineffective random exploration at the beginning of training,and lead to overestimated value estimates and suboptimal *** this paper,we address the problem by executing advantage rectification with imperfect demonstrations,thus reducing the function estimation *** with expert demonstrations has been widely adopted to accelerate the learning process of deep reinforcement learning when simulations are expensive to ***,existing methods,such as behavior cloning,often assume the demonstrations contain other information or labels with regard to performances,such as optimal assumption,which is usually incorrect and useless in the real *** this paper,we explicitly handle imperfect demonstrations within the actor-critic RL frameworks,and propose a new method called learning from imperfect demonstrations with advantage rectification(LIDAR).LIDAR utilizes a rectified loss function to merely learn from selective demonstrations,which is derived from a minimal assumption that the demonstrating policies have better performances than our current *** learns from contradictions caused by estimation errors,and in turn reduces estimation *** apply LIDAR to three popular actor-critic algorithms,DDPG,TD3 and SAC,and experiments show that our method can observably reduce the function estimation errors,effectively leverage demonstrations far from the optimal,and outperform state-of-the-art baselines consistently in all the scenarios.

关键词： learning from demonstrations actor-critic reinforcement learning advantage rectification

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An improved neural network model for battery smarter state-of-charge estimation of energy-transportation system

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Green Energy and Intelligent Transportation 2023年第2期2卷 56-65页

作者： Bingzhe Fu Wei Wang Yihuan Li Qiao Peng School of Control and Computer Engineering North China Electric Power UniversityBeijing102206China Group of Information Technology Analytics&OperationsQueen's University BelfastBelfastBT95EEUK

The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy *** achieve safe management and optimal control of batteries,the state of charge(SOC)is one of the important *** machine-learning based SOC estimation methods of lithium-ion batteries have attracted substantial interests in recent ***,a common problem with these models is that their estimation performances are not always stable,which makes them difficult to use in practical *** address this problem,an optimized radial basis function neural network(RBF-NN)that combines the concepts of Golden Section Method(GSM)and Sparrow Search Algorithm(SSA)is proposed in this ***,GSM is used to determine the optimum number of neurons in hidden layer of the RBF-NN model,and its parameters such as radial base center,connection weights and so on are optimized by SSA,which greatly improve the performance of RBF-NN in SOC *** the experiments,data collected from different working conditions are used to demonstrate the accuracy and generalization ability of the proposed model,and the results of the experiment indicate that the maximum error of the proposed model is less than 2%.

关键词： Battery management SOC estimation Data science Neural network Golden section method Sparrow search algorithm

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Enhancing Agricultural Productivity: A Sensor Fusion, Spectroscopic Near Infrared, and AI-Based Framework for Monitoring Fruit Ripeness 21

Enhancing Agricultural Productivity: A Sensor Fusion, Spectr...

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21st International Bhurban Conference on Applied Sciences and Technology, IBCAST 2024

作者： Ambreen, Hira Imran, Muhammad Diyin, Tang Zhang, Chongsheng Sir Syed CASE Institute of Technology Islamabad Pakistan School of Automation Science and Electrical Engineering Beihang University Aeronautics and Astronautics China Henan Univerity Department of EE Kaifeng475001 China School of Automation Science and Electrical Engineering Beihang University Aeronautics and Astronautics Department of Detection and Automation Engineering China School of Computer & Information Engineering Henan University Kaifeng475001 China

ISBN: (纸本)9798331516680

Fruit ripeness evaluation is essential for harvest optimization and post-harvest loss prevention. Traditional visual inspection is inefficient. This study employs sensor fusion and AI algorithms to evaluate fruit maturity in real-time using gas sensors (i.e., MQ-3, MQ-6, MQ-8, MQ-135) and Near-Infrared spectral sensors (i.e., GY-AS7263). Primarily, data pro-cessing-sensor fusion, data preparation, and AI model application-is crucial to the proposed framework. Subsequently, sensor fusion approaches improve data accuracy by combining signals from various sensors. Secondly, data pretreatment techniques including noise reduction, normalization, and feature extraction prepare data for analysis. Thirdly, we use powerful machine learning algorithms such as Random Forest to judge maturity more accurately and reliably than conventional techniques. Lastly, integrating NIR spectroscopy with gas sensor data resolves cost and model transferability issues, enhancing accuracy and acces-sibility for agricultural use. Static image processing techniques provide challenges for real-time applications, including expensive computer costs and lower reliability. The proposed framework based on multi-sensor fusion system enhances agricultural applications' versatility, scalability, and reactivity, surpassing existing methodologies. © 2024 IeeE.

关键词： Fruits

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Unveiling Behavioral Transparency of Protocols Communicated by IoT Networked Assets

Unveiling Behavioral Transparency of Protocols Communicated ...

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IeeE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM)

作者： Savindu Wannigama Arunan Sivanathan Ayyoob Hamza Hassan Habibi Gharakheili Department of Computer Engineering University of Peradeniya Sri Lanka School of EE & T UNSW Sydney Australia

ISBN: (数字)9798350394665

ISBN: (纸本)9798350394672

Behavioral transparency for Internet-of-Things (IoT) networked assets involves two distinct yet interconnected tasks: (a) characterizing device types by discerning the patterns exhibited in their network traffic, and (b) assessing vulnerabilities they introduce to the network. While identifying communication protocols, particularly at the application layer, plays a vital role in effective network management, current methods are, at best, ad-hoc. Accurate protocol identification and attribute extraction from packet payloads are crucial for distinguishing devices and discovering vulnerabilities. This paper makes three contributions: (1) We process a public dataset to construct specific packet traces pertinent to six standard protocols (TLS, HTTP, DNS, NTP, DHCP, and SSDP) of ten commercial IoT devices. We manually analyze TLS and HTTP flows, highlighting their characteristics and parameters. We make our data publicly available; (2) We develop a common model to describe protocol signatures that help with the systematic analysis of protocols even when communicated through non-standard port numbers; and, (3) We evaluate the efficacy of our data models for the six protocols, which constitute approximately 97% of our dataset. Our data models, except for SSDP in 0.3% of Amazon Echo’s flows, produce no false positives for protocol detection. We draw insights into how various IoT devices behave, and adherence to best practices across those protocols by applying these models to our IoT traces.

关键词： Wireless communication Systematics Telecommunication traffic HTTP Data models Internet of Things Object recognition

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Outage Performance Analysis in Cognitive RIS-NOMA System under Imperfect CSI 3

Outage Performance Analysis in Cognitive RIS-NOMA System und...

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3rd IeeE International Mediterranean Conference on Communications and Networking, MeditCom 2023

作者： Xue, K. Li, M. Chen, W. Han, Z. Yuan, H. Taiyuan University of Science and Technology School of Electronics Information Engineering China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing China University of Houston Department of Electrical and Computer Engineering United States Kyung Hee University Department of Computer Science and Engineering Korea Republic of Kingston University School of Computer Science and Mathematics KT1 2EE United Kingdom

ISBN: (纸本)9798350333732

Cognitive non-orthogonal multiple access (NOMA) and reconfigurable intelligent surface (RIS) have been envisioned as two promising technologies for vehicle to everything (V2X) networks. This paper considers an RIS-aided V2X network with cognitive NOMA while considering the imperfect channel state information (CSI) due to the mobility of the vehicles. The new approximate outage probability (OP) expressions of the supposed system are derived over double Rayleigh fading channels. Numerical and Monte Carlo simulation results are presented to corroborate the analysis. The results demonstrated that imperfect CSI has a significant but different impact on the outage performance of the far and near users, which are also different under different numbers of reflecting units. © 2023 IeeE.

关键词： Monte Carlo methods

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Unveiling Behavioral Transparency of Protocols Communicated by IoT Networked Assets (Full Version)

arXiv

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arXiv 2024年

作者： Wannigama, Savindu Sivanathan, Arunan Hamza, Ayyoob Gharakheili, Hassan Habibi Department of Computer Engineering University of Peradeniya Sri Lanka School of EE&T UNSW Sydney Australia

Behavioral transparency for Internet-of-Things (IoT) networked assets involves two distinct yet interconnected tasks: (a) characterizing device types by discerning the patterns exhibited in their network traffic, and (b) assessing vulnerabilities they introduce to the network. While identifying communication protocols, particularly at the application layer, plays a vital role in effective network management, current methods are, at best, ad-hoc. Accurate protocol identification and attribute extraction from packet payloads are crucial for distinguishing devices and discovering vulnerabilities. This paper makes three contributions: (1) We process a public dataset to construct specific packet traces pertinent to six standard protocols (TLS, HTTP, DNS, NTP, DHCP, and SSDP) of ten commercial IoT devices. We manually analyze TLS and HTTP flows, highlighting their characteristics, parameters, and adherence to best practices-we make our data publicly available;(2) We develop a common model to describe protocol signatures that help with the systematic analysis of protocols even when communicated through non-standard port numbers;and, (3) We evaluate the efficacy of our data models for the six protocols, which constitute approximately 97% of our dataset. Our data models, except for SSDP in 0.3% of Amazon Echo's flows, produce no false positives for protocol detection. We draw insights into how various IoT devices behave across those protocols by applying these models to our IoT traces. Copyright © 2024, The Authors. All rights reserved.

关键词： Internet of things

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Calculation of The Firefly Method's Parameters for PID Parameters in Applications Involving Solar Panels

Calculation of The Firefly Method's Parameters for PID Param...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Kavitha, M.S. Verma, Pradeep Kumar Prasath, S. Ram Bhatt, Rahul Amudha, A. Marathe, Vijay University R.M.K. Engineering College Kavaraipettai Chennai India Department of EE TMU India Department of Electronics and Communication Engineering Karpagam College of Engineering Coimbatore India School of Engineering and Computer Dev Bhoomi Uttarakhand University India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore India Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350355338

To generate the most electrical power, the sections panels must operate at their best. A sunlight tracker may assist with the panels function at their best. details solar cell tracker operates by tracing the path of sunlight. The efficiency the sunlight energy tracker was optimized using some Proportional, Integral, It (PID) centered command. To obtain their PID variable, an ideal adjusting is required. A clever technique for optimizing PID settings involves the Fireflies technique. The system makes use of the following three Fireflies An algorithm (FA) variables: Firefly accelerate is determined by beta, motion flexibility by alpha, while more intricate limitations or limitations are determined by gamma. issues. details beta appreciate drive is used for this multifaceted center solar power monitoring study, altering their beta appreciate about 0.1 to 0.9. subsequently was discovered about the outcomes of ten models how their PID unchanged remained varied. The ideal outcomes on known as horizon occur when their beta has been set during 0.4, while the most adverse outcomes occur when their beta is provided at 0.8. details Beta value of 0.3 produces the ideal results upon known as vertical plane, while 0.8 produces lowest results. © 2024 IeeE.

关键词： Solar power generation

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A Case Study of the Implementation Difficulties in the Pilot Low Cost Concentrating Solar Power Systems Deployment in Sub-Saharan Africa 6

A Case Study of the Implementation Difficulties in the Pilot...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Babu Potluri, Sankar Goswami, Garima Yadav, Annu Ravivarman, P.G. Gajendran, P. Tiwaskar, S.A. S v R Engineering College Department of EEE Nandyal India Teerthankar Mahaveer University Department of EE Moradabad India School of COMPUTER Science and Applications IIMT University Meerut India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Vishwakarma Institute of Information Technology Computer Engineering Maharashtra Pune India

ISBN: (纸本)9798350304480

Among those most important resources for a particular country's expansion and expansion was electrical power. According to the most recent sustainability the growth paper, the continent continues to have a significant electrical power deficit. sunlight concentration appears to be a viable solution to make up the difference. This is due to the fact the majority of focusing solar energy plant elements are easily accessible and reasonably priced on their African marketplace, and authorized locals can construct the structures. Within Africa south of the Sahara, steer 50 nm-concentrating solar energy plants are being put into operation with promising outcomes that might be grew and utilized to generate large amounts of electrical power. One notable challenge was identified during an evaluation of a prototype focusing photovoltaic plant within the channel-region: the monitoring system's inability to lower the daily costs required to operate the monitoring control structure and enhance the numerous special machines focusing conduct. This essay emphasizes the current energy landscape and African study of concentrated sunlight is currently progressing. To demonstrate current study strategy about the development of inexpensive monitoring devices in regards to mathematical difficulty, energy use, and special machine alignment precision, the article also provides an in-depth examination of the most recent solar monitoring structures for essential receiver networks. © 2023 IeeE.

关键词： central receiver system CSP (Concentrated Solar Power) development electricity generation Low-Cost tracking algorithms

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Destination Scheduling for Secure Pinhole-Based Power-Line Communication

IEEE Open Journal of the Communications Society

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IeeE Open Journal of the Communications Society 2023年 4卷 2245-2260页

作者： Kundu, Chinmoy Dubey, Ankit Tonello, Andrea M. Nallanathan, Arumugam Flanagan, Mark F. University College Dublin School of Electrical and Electronic Engineering Dublin 4D04 V1W8 Ireland Indian Institute of Technology Jammu Department of Ee Jammu181221 India Institute of Networked and Embedded Systems University of Klagenfurt Klagenfurt9020 Austria Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom

We propose an optimal destination scheduling scheme to improve the physical layer security (PLS) of a power-line communication (PLC) based Internet-of-Things system in the presence of an eavesdropper. We consider a pinhole (PH) architecture for a multi-node PLC network to capture the keyhole effect in PLC. The transmitter-to-PH link is shared between the destinations and an eavesdropper which correlates all end-to-end links. The individual channel gains are assumed to follow independent log-normal statistics. Furthermore, the additive impulsive noise at each node is modeled by an independent Bernoulli-Gaussian process. Exact computable expressions for the average secrecy capacity (ASC) and the probability of intercept (POI) performance over many different networks are derived. Approximate closed-form expressions for the asymptotic ASC and POI are also provided. We find that the asymptotic ASC saturates to a constant level as transmit power increases. We observe that the PH has an adverse effect on the ASC. Although the shared link affects the ASC, it has no effect on the POI. We show that by artificially controlling the impulsive to background noise power ratio and its arrival rate at the receivers, the secrecy performance can be improved. © 2020 IeeE.

关键词： Impulse noise

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