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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Srinivasan, Dhamodharan Premkumar, M. Deepa Nivethika, S. Dhilipkumar, P. Parameswari, S. Chowdary, M. Kalpana Centre for Blockchain and Cybersecurity Sri Eshwar College of Engineering Department of Computer and Communication Engineering Coimbatore India Ssm Institute of Engineering and Technology Department of Electronics and Communication Engineering Dindigul India Vit University School of Computer Science and Engineering Chennai India Sri Ranganathar Institute of Engineering and Technology Department of Ece Coimbatore India Sri Sairam Insitute of Technology Department of Ece Chennai India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9789380544519

In this article, the potential of low-terahertz (THz) technology is discussed to present high data rates in future biomedical systems, and also in the 6G mobile system. However, due to the loss, the design of high-gain antennas is crucial to overcome power limitations and compensate for the additional path loss. This article highlights recent developments in wideband and high-gain sub-mm-wave and low-THz antennas and their fabrication technologies. The advancements in recent technologies have enabled the manufacture of antennas with complicated structures with precise accuracy and less expensive. Overall, the paper emphasizes the importance of high-gain antennas in overcoming the challenges associated with low-THz technology and highlights the potential of AM technology in the development of low-cost, high-performance THz antennas. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Antennas high gain low-cost low-terahertz three-dimensional printing (3DP)

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Resource Allocation in 6G Network for High-Speed Train Using D2D Outband communication 3rd

Resource Allocation in 6G Network for High-Speed Train Using...

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3rd International Conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Garg, Aakansha Arya, Rajeev Singh, Maheshwari Prasad Wireless Sensor Network Lab Department of Electronics and Communication Engineering Patna India Department of Computer Science and Engineering National Institute of Technology Patna India

ISBN: (纸本)9789819743582

The growth of 6G results in rising data transmission rate in static scenario. To achieve fast communication and computation with quality service in high-speed train is a challenge. This is due to fast handover and Doppler shift. To effectively communicate in high-speed train, the placement of a mobile relay (MR) with small server at the rooftop of train coach is proposed. The base station sends channel state information to mobile relay which stores it in the stack. The resource assignment has been conducted by an improved grey wolf optimization algorithm. The focus is at improving throughput with reduction in latency and energy consumption. The simulation outcomes manifests that the presented algorithm carry-out finer in comparison of the Hungarian algorithm. The accomplished results are refined almost three times in respect of energy consumption, latency, and throughput. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Resource allocation

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Cybersecurity advancements for medical image transmission: a hybrid optical-based cryptosystem harnessing chaos, DNA sequences, and mandelbrot keys

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Multimedia Tools and Applications 2025年 1-41页

作者： Alalwan, Nasser El-Shafai, Walid Amoon, Mohammed Benjdira, Bilel Department of Computer and Communication Engineering King Saud University Riyadh Saudi Arabia Prince Sultan University Riyadh11586 Saudi Arabia Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh12435 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt

In today's advanced technological age, characterized by innovations like big data processing, cloud computing, and the Internet of Things (IoT), there is a rising utilization of medical multimedia data, especially medical images. These images, integral to the Internet of Healthcare Things (IoHT), necessitate secure transmission due to the increasing risks of unauthorized breaches and tampering. Current security methods, especially for cloud and mobile platforms, often struggle with challenges related to processing capacity, memory use, data size, and energy, making them ill-suited for extensive medical data or resource-limited environments. To address these challenges, this study introduces a novel hybrid cryptosystem, drawing on the unique qualities of the optical Arnold chaotic map, DNA (DeoxyriboNucleic Acid) sequences, and Mandelbrot keys, providing a fortified approach to the secure streaming of medical images. The proposed framework operates via a precise and structured procedure. It begins by applying the optical Arnold chaotic map cipher to each of the three-color channels (R, G, and B) within a medical image. This is followed by overlaying DNA encoding sequences on the resultant encrypted image from the earlier ciphering phase. Leveraging this groundwork, we incorporate an advanced Mandelbrot set-driven shift mechanism specifically designed to create complex confusion patterns within the R, G, and B segments of the encrypted medical imagery. The efficacy of the proposed cryptosystem is rigorously substantiated through an extensive array of simulations supported by a comprehensive security analysis. The results highlight its unparalleled resilience and security capabilities in the realm of medical image encryption, marking a significant leap over previous systems in the literature. Essentially, our work pioneers a solution to a pressing challenge in medical image security, ensuring enhanced protection of delicate health data among the rapidly evolving advanc

关键词： Cybersecurity

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Vehicle Connectivity Analysis in Delay Tolerant Network for Different Antenna Ranges 4

Vehicle Connectivity Analysis in Delay Tolerant Network for ...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Sharma, Mayank Kumar, Pradeep Tomar, Ranjeet Singh University of KwaZulu-Natal Discipline of Electrical Electronic and Computer Engineering Durban South Africa ITM University Department of Electronics and Communication Engineering Gwalior India

ISBN: (纸本)9798350395914

Vehicular Adhoc Networks (VANETs) are the op-portunistic networks (OppNets) which use connectivity issues as a chance. A VANET, categorized by connectivity disruptions, is well suited because of rapid vagaries in network scenario, variable vehicle density, and high vehicle speeds. In this paper, the vehicle connectivity in Delay Tolerant Networking (DTN), a connection less data transmission model that utilizes intermittent connections and OppNet to transfer information, for different antenna ranges is analysed. A variety of simulations were performed to determine the connectivity with different DTN protocols and vehicle conditions for various antenna ranges. As a result of the simulations, the source spray and wait (SSNW), binary spray and wait (BSNW) and First Contact (FC) protocol give better performance metrics for different vehicle antenna ranges in low and high-density scenarios. © 2024 IEEE.

关键词： Delay tolerant networks

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AI-Enhanced Farming: A Real-Time Monitoring App powered by IoT 5

AI-Enhanced Farming: A Real-Time Monitoring App powered by I...

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5th International Conference on Smart electronics and communication, ICOSEC 2024

作者： Gayathri, R. Raaj, R. Sathesh Balaanand, M. Kumar, J. Arun Sasikala, N. Rajesh, K. Psna College of Engineering and Technology Department of Computer Science and Engineering Dindigul India Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Tagore Institute of Engineering & Technology Department of Computer Science and Engineering Salem India Dayananda Sagar University Department of Computer Science and Engineering Karnataka Harohalli India Ssm Institute of Science and Technology Department of Electronics and Communication Engineering Dindigul India

ISBN: (纸本)9798331504403

The Constant challenge faced by the farmers is to maintain their crops and enhance productivity. Despite various methods and solution evolving, still farmers can't upgrade to it. Farmers are not aware of the modern agricultural methods. The major cause is that the software and solution developed are of higher complexity. To upgrade them, technology is the foremost important tool to stand up in this modern world. To help them with their problem and adapt to the modern world, the development of software with inbuilt AI and user-friendly features (in agriculture) is needed. This study proposes a novel Agri-tech app, which is a IoT based app used by the farmers for weather forecasting, soil moisture and nutrient content analysis. The developed application also recommends the crop type that can be cultivated in the soil by using the database of soil moisture and nutrient content. IoT sensors fixed in the field are used to detect the moisture level in the soil and notify the farmers to irrigate the land. It recommends the farmer to add manures and fertilizers to soil by calculating the amount of nitrogen, phosphorous, and oxygen contents present in the soil. Using these technical innovation farmers can monitor their fields over a system or smart phone. Moreover, the proposed approach can promote crop diversity and rotation for healthier soil, encourage sustainable practices like organic farming. © 2024 IEEE.

关键词： Soil moisture

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A Hybrid Framework for Data Loss Prevention and Detection

A Hybrid Framework for Data Loss Prevention and Detection

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Srivastava, Atul Srivastava, Priyam Pillai, Anuradha Sharma, Vijay Shankar AUUP Amity School of Engineering and Technology Lucknow India Symbiosis Institute of Technology Department of Computer Science and Engineering Pune India Manipal University Department of Computer and Communication Engineering Jaipur India

ISBN: (纸本)9798350385199

Modern enterprises face a serious threat from data loss, or the unintentional or undesired disclosure of data. Modern Data Loss Protection (DLP) systems either discover anomalies in regular behavior (anomaly-based) or use signatures of known attack patterns. Though signature-based solutions are effective in accurately identifying known attacks and may thus be used to block them, they are unable to handle unexpected attacks or attackers who choose atypical attack vectors (such as those that are only known to insiders) to execute their attack. However, because they frequently produce a high false positive rate, anomaly-based solutions are not as useful for identifying suspicious activity. In contrast, they can identify undiscovered attacks. Our research presents a hybrid DLP system that integrates anomaly-based and signature-based approaches to facilitate both prevention and detection. Using an anomaly-based engine, the framework automatically builds a model of typical user behavior, enabling it to detect unusual transactions carried out by insiders. This is usually where anomaly-based solutions end. To prevent unwanted transactions from causing harm, our framework goes one step further by using an operator's feedback on alarms to automatically create and update attack signatures. We manage to improve time to detect a data breach was reduced by 67%, improving response efficiency. © 2024 IEEE.

关键词： Information leakage

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Enhanced Fraud Detection in Ethereum Transactions: Fusion of Modified Genetic Algorithms and Deep Learning with Limited Attributes

Enhanced Fraud Detection in Ethereum Transactions: Fusion of...

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Srivastava, Atul Kumar, Alok Pillai, Anuradha Sharma, Vijay Shankar AUUP Amity School of Engineering and Technology Lucknow India Symbiosis Institute of Technology Department of Computer Science and Engineering Pune India Manipal University Department of Computer and Communication Engineering Jaipur India

ISBN: (纸本)9798350385199

Ethereum smart contracts, the new way of transactions and a popular name in the world of cryptocurrencies, have gathered a huge base of research and scientific attention. They are so helpful that they allow us to eliminate the need for a separate third-party library to allow unknown parties to see contract details on a computer. But since we can all see that online commerce is growing day by day and will continue to grow, it can never be fully free from scams and unethical operations. So, to correctly detect all such unethical and malicious transactions, this paper used a deep learning model. And to further enhance the model, this study used metaheuristic optimization as well. It employs an algorithm called Genetic Algorithm and to provide better optimization in the explorations phase of Cuckoo Search (CS) to achieve its goal of detecting fraudulent transactions. The algorithm covers the loopholes in the CS strategy. Furthermore, to provide strong grounds for research in our paper, this proposed model was compared with various types of approaches such as Light Gradient Boosting Machine, Support Vector Classification, Multi-Layer Perceptron, XGBoost, Logistic Regression, and Random Forest. The proposed model outperforms other significant models like SVC, KNN, LGBM Classifier, RF etc. with the accuracy of 98.6%. © 2024 IEEE.

关键词： Genetic algorithms

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Fine classification of rice paddy using multitemporal compact polarimetric SAR C band data based on machine learning methods

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Frontiers of Earth Science 2024年第1期18卷 30-43页

作者： Xianyu GUO Junjun YIN Kun LI Jian YANG Huimin ZOU Fukun YANG School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China College of Global Change and Earth System Science Beijing Normal UniversityBeijing 100875China

Rice is an important food crop for human *** distinguishing different varieties and sowing methods of rice on a large scale can provide more accurate information for rice growth monitoring,yield estimation,and phenological monitoring,which has significance for the development of modern *** polarimetric(CP)synthetic aperture radar(SAR)provides multichannel information and shows great potential for rice monitoring and ***,the use of machine learning methods to build classification models is a controversial *** this paper,the advantages of CP SAR data,the powerful learning ability of machine learning,and the important factors of the rice growth cycle were taken into account to achieve high-precision and fine classification of rice ***,CP SAR data were simulated by using the seven temporal RADARSAT-2 C-band data ***,20-two CP SAR parameters were extracted from each of the seven temporal CP SAR data *** addition,we fully considered the change degree of CP SAR parameters on a time scale(ΔCP_(DoY)).Six machine learning methods were employed to carry out the fine classification of rice *** results show that the classification methods of machine learning based on multitemporal CP SAR data can obtain better results in the fine classification of rice paddies by considering the parameters ofΔCP_(DoY).The overall accuracy is greater than 95.05%,and the Kappa coefficient is greater than *** them,the random forest(RF)and support vector machine(SVM)achieve the best results,with an overall accuracy reaching 97.32%and 97.37%,respectively,and Kappa coefficient values reaching 0.965 and 0.966,*** the two types of rice paddies,the average accuracy of the transplant hybrid(T-H)rice paddy is greater than 90.64%,and the highest accuracy is 95.95%.The average accuracy of direct-sown japonica(D-J)rice paddy is greater than 92.57%,and the highest accuracy is 96.13%.

关键词： compact polarimetric(CP)SAR rice paddy machine learning fine classification multitemporal

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Demand-Aware Beam Hopping and Power Allocation for Load Balancing in Digital Twin empowered LEO Satellite Networks

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IEEE Transactions on Wireless communications 2025年第6期24卷 5084-5098页

作者： Zhao, Ruili Cai, Jun Luo, Jiangtao Gao, Junpeng Ran, Yongyi Chongqing University of Posts and Telecommunications School of Communication and Information Engineering Chongqing400065 China Department of Electrical and Computer Engineering MontrealQCH3G 1M8 Canada Chongqing University of Posts and Telecommunications Electronic Information and Networking Research Institute Chongqing400065 China

Low-Earth orbit (LEO) satellites utilizing beam hopping (BH) technology offer extensive coverage, low latency, high bandwidth, and significant flexibility. However, the uneven geographical distribution and temporal variability of ground traffic demands, combined with the high mobility of LEO satellites, present significant challenges for efficient beam resource utilization. Traditional BH methods based on GEO satellites fail to address issues such as satellite interference, overlapping coverage, and mobility. This paper explores a Digital Twin (DT)-based collaborative resource allocation network for multiple LEO satellites with overlapping coverage areas. A two-tier optimization problem, focusing on load balancing and cell service fairness, is proposed to maximize throughput and minimize inter-cell service delay. The DT layer optimizes the allocation of overlapping coverage cells by designing BH patterns for each satellite, while the LEO layer optimizes power allocation for each selected service cell. At the DT layer, an Actor-Critic network is deployed on each agent, with a global critic network in the cloud center. The A3C algorithm is employed to optimize the DT layer. Concurrently, the LEO layer optimization is performed using a Multi-Agent Reinforcement Learning algorithm, where each beam functions as an independent agent. The simulation results show that this method reduces satellite load disparity by about 72.5% and decreases the average delay to 12ms. Additionally, our approach outperforms other benchmarks in terms of throughput, ensuring a better alignment between offered and requested data. © 2025 IEEE. All rights reserved.

关键词： Satellite communication systems

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Area Efficient 0.009-mm2 28.1-ppm/°C 11.3-MHz ALL-MOS Relaxation Oscillator

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IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2024年第10期32卷 1900-1907页

作者： Wijaya, Joshua Adiel Chen, Poki Kumar Pradhan, Lucky Shahid Bhatti, Ahmad Kajihara, Seiji National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei106 Taiwan Kyushu Institute of Technology Fukuoka804-0015 Japan

This article presents an ultrasmall area on-chip relaxation oscillator with low-temperature sensitivity. In this design, a virtual resistor mainly composed of a complementary to absolute temperature (CTAT) voltage reference circuit is implemented to replace the real resistor for efficient temperature compensation, which counterbalances the inherent proportional to absolute temperature (PTAT) property of the original relaxation circuit of the oscillator. The conventional capacitor is also replaced with a MOS capacitor to complete the ALL-MOS oscillator circuit with two prime advantages, one of which is larger capacitance to area density, and the other is better matching with critical MOSFETs. Implemented in a 0.18-μm TSMC standard CMOS process, the proposed relaxation oscillator has achieved a temperature coefficient of 28.17 ppm/°C over the temperature range from -25°C to + 125°C at 11.39-MHz oscillation frequency. This circuit consumes 243.1μW under 1.3-V power supply. Along with the abovementioned excellent performance, the oscillator achieves an ultrasmall core chip area of 0.009 mm2, which is almost one order less than most of the prior arts' in the same process. © 1993-2012 IEEE.

关键词： Temperature

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