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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Garigipati, Nagababu Srithar, S. Reddy, V.Krishna Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering AP Vaddeswaram India Gitam School of Technology Gitam Deemed to Be University Department of Computer Science and Engineering Andhra Pradesh Visakhapatnam India

ISBN: (纸本)9798350347579

Cloud computing has emerged as significant and paradigm shift in outsourcing storage and computations. Data stored in public cloud without encryption is not safe due to many reasons such as insider attacks, flawed hardware, security vulnerabilities and service provider stealing or deleting data for monetary gains. Therefore, it is essential for data owner to outsource data to cloud after encryption. However, the existing encryption schemes such as RSA, DES and AES, though they provide strong security, may become victims to post-quantum securityscenarios. In this paper, a hybrid security algorithm is proposed for stronger encryption and decryption procedures. The algorithm is named Multi-Layer Hybrid Security Algorithm (ML-HSA) which has multiple data transformations using AES for encryption of given data, Information Dispersal Algorithm (IDA) for ensuring data integrity and hashing for data integrity verification. The proposed scheme is evaluated using Amazon EC2 (Elastic Compute Cloud) cloud platform and Amazon S3 (Simple Storage Service). The performance of ML-HSA is compared against state of the art security schemes such as RSA, DES andAES. Experimental results revealed that the proposed post-quantum security scheme provides stronger security with relatively less overhead due to multiple transformations involved. © 2023 IEEE.

关键词： Cloud security

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Implementation of ML Algorithm for Spyware Detection system Using SVM with KNN Algorithm for Comparison of Accuracy 9

Implementation of ML Algorithm for Spyware Detection System ...

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9th International Conference on Applying New Technology in Green Buildings, ATiGB 2024

作者： Inba Pranaou, I.V. Christy, S. Poovizhi, T. Saveetha Institution of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331505042

The research examines the Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) machine learning algorithms with the goal of using machine learning to detect malware and mitigate cybersecurity threats. Utilizing the malware dataset and the SVM and KNN methods, which consists of 500 rows and 6 attribute columns, the accuracy of spyware detection is determined. This dataset was collected from the well-known kaggle website. Python 3. 12 is the programming dialect used to run the code in IDLE shell. The clinical calculator is used for estimating the sample size. Groups 1 and 2 have a computed sample size of 500 with an alpha 80% power, a 95% confidence level, and a threshold value of 0.05. The Data Analytics lab is where research is done. Using the IBM SPSS statistical software, version 27, the accuracy of the SVM algorithm is compared to that of the KNN method. When comparing the Support vector machines' mean accuracy to the K-Nearest Neighbors algorithm, the results show a substantial improvement. © 2024 IEEE.

关键词： Cybersecurity

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Securing the Internet of Things with Block chain-based Network Security Protocols 15

Securing the Internet of Things with Block chain-based Netwo...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Marimuthu, T. Chattopadhyay, Saumitra Parveen, H. Summia Shukla, Rishi Prakash Manwal, Manika Nair, Vilas School of Computing Department of CSE Krishnankoil626126 India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun248002 India Sri Eshwar College of Engineering Department of Computer Science Engineering Tamil Nadu Coimbatore641202 India Jaipuriya Institute of Management Jaipur India Graphic Era Deemed to be University Computer Science and Engineering Uttarakhand Dehradun India SCMS School of Technology and Management Cochin India

ISBN: (纸本)9798350370249

The Iot refers back to the network of physical gadgets, cars, and home equipment, which might be embedded with sensors, software program, and connectivity, allowing them to accumulate and trade facts. With the growing adoption of these gadgets, there is a growing subject for the safety and privacy of the information being transmitted thru them. Conventional community safety protocols are insufficient to shield massive-scale Iota deployments due to their centralization and vulnerability to cyber-attacks. Block chain generation gives an ability technique to the protection stressful situations of Iota. It is a dispensed ledger device that lets in relaxed and transparent transactions without the need for a government. In this summary, we suggest using block chain-based network safety protocols to comfy the Iota. Those protocols make use of the cryptographic competencies of block chain to ensure cozy device authentication and records integrity, and decentralized consensus mechanisms to save you the single thing of failure. © 2024 IEEE.

关键词： Authentication Protocol

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A Dynamic Heuristic Set-based Particle Swarm Optimizer for the Multi-Objective Task Assigning Problem in Wireless Sensor Networks 11

A Dynamic Heuristic Set-based Particle Swarm Optimizer for t...

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11th International Conference on Machine Intelligence Theory and Applications, MiTA 2024

作者： Wei, Feng-Feng Geng, Ming-Can Hu, Xiao-Min Jeon, Sang-Woon Chen, Wei-Neng South China University of Technology School of Computer Science and Engineering Guangzhou China Hanyang University Department of Electrical and Electronic Engineering Ansan Korea Republic of

ISBN: (纸本)9798350385670

The task assigning problem in wireless sensor networks is a challenging NP-hard combinatorial optimization problem that has caught much attention. Although binary particle swarm optimizers have been proven to be effective for this problem, the prematurity remains severe. To fix the prematurity, this paper proposes a set-based particle swarm optimizer with dynamic heuristic substitution techniques. Differing from the original binary particle swarm optimizer, the representation scheme is based on the concept of set. The position of each particle is a set whose elements are defined by the problem. A particle position element denotes the allocation of a task to a sensor node. The proposed algorithm tries to select an optimal subset from the universal set based on the particle swarm optimization framework. Moreover, the comprehensive learning strategy that utilizes beneficial information from the best-ever positions of all particles is employed, which helps keep the swarm away from local optima. Considering the constraints in real-world situations, the position updating adopts a substitution operation, guided by heuristic information that dynamically alters. To improve particle diversity, mutation operations are carried out after renewing the particle positions. Simulation results demonstrate the superiority of the proposed approach over others. © 2024 IEEE.

关键词： Combinatorial optimization

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A Study and Analysis of Energy Efficient Parameters and Protocols in Energy Efficiency in Wireless Sensor Networks

A Study and Analysis of Energy Efficient Parameters and Prot...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Swathi, B. Amanullah, M. Kalaiselvan, S.A. Department of Computer Science & Engineering Saveetha School of Engineering SIMATS Chennai India Department of Computer Science & Engineering Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Avadi Chennai India

ISBN: (纸本)9798350305708

WSNs, or wireless sensor networks, play a significant role in today's factories. Environmental tracking, preparedness, monitoring of health, intelligence tracking, and security recognition are just some of the possible areas of use for WSNs. It is challenging to replace sensor nodes (SNs) after they have been fully deployed in such applications because of the large number of SNs required for the deployment. Since most SNs are portable computers powered by batteries, it is crucial to keep an eye on each node's power usage to ensure the network lasts as long as possible. There have been several suggestions made in research throughout the years for cost-effective and energy-balanced routing strategies. The goal of the routing protocols designed to save energy inside an SN is to extend the life of the network as a whole. However, by distributing power between nodes in the network more evenly, energy-balanced routing approaches may keep the network operational for longer. Researchers have submitted many survey papers to investigate and document the different energy-efficient routing options for WSNs. While WSN load-balanced power routing methods are becoming more important, there does not seem to have a simple survey available to emphasize their importance, concepts, and principles. This research provides a comprehensive explanation of the energy-efficient along with energy-balanced routing algorithms for WSNs. © 2023 IEEE.

关键词： Communication Protocols Energy Efficient Protocols Hierarchical Protocols Routing Protocols Sensor Networks

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Enhancing Skin Cancer Detection Through Automated Classification Using Convolutional Neural Networks 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Hossain, Md Jakir Bhuiyan, M. D. Wahidul Islam Raisa, Sadia Afrin Tomal, Minhazul Amin Jennifer, Sanjeda Sara Reza, Ahmed Wasif Siddique, Nazmul Department of Computer Science and Engineering East West University Dhaka Bangladesh School of Computing Engineering and Intelligent Systems Ulster University Londonderry United Kingdom

ISBN: (数字)9783031733185

ISBN: (纸本)9783031733178

Skin cancer presents a significant public health concern, necessitating early detection and intervention to mitigate life-threatening consequences. Despite its prevalence, skin cancer is not always given the attention it deserves. In this paper, we propose an automated procedure for distinguishing skin cancers using several neural network algorithms. We used the MobileNet architecture whose accuracy is not very high and this is why we have also used other algorithms such as Sequential CNN (Convolution Neural Network), VGG16, and Xception to improve the accuracy of our model. By comparing these algorithms, we found that the Sequential CNN performed best with an accuracy of 94%. The proposed model utilizes the Sequential CNN algorithm to achieve a high level of accuracy, which is of utmost importance for the early detection of skin cancer. The high accuracy of the proposed model makes it a promising tool for detecting skin cancer early. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Lung cancer

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Deep Age Estimation Using Structural MRI: Unveiling Neurological Patterns 2

Deep Age Estimation Using Structural MRI: Unveiling Neurolog...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Subbarayudu, Jangam Michael, G. Kumari, V. Sheeja Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350365269

There is a lot of hope for understanding the neurological patterns associated with ageing in the relatively new field of deep age estimation using structural magnetic resonance imaging (MRI). The goal of this study is to extract and evaluate complex structural features from MRI data using advanced deep learning techniques, namely convolutional neural networks (CNNs). In this study, we train deep neural networks on large datasets of MRI images in the hopes of building reliable models that can accurately determine the ages of individuals. This method allows us to detect signs of ageing and subtle neurological patterns that could otherwise go undetected by more traditional methods. In addition, we evaluate the potential of using data augmentation and transfer learning techniques to enhance the model's performance and generalise it to different populations. Our ultimate goal in doing this research is to further our understanding of brain ageing and the effects it has on cognitive decline and age-related diseases. Deep age estimation via structural magnetic resonance imaging may, in the end, change the face of clinical diagnosis, individualised treatment, and age-related research. This is because it provides methods for assessing brain health and ageing trajectories that are both safe and non-invasive. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

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computers, Materials & Continua 2023年第5期75卷 3189-3201页

作者： Shakti Raj Chopra Parulpreet Singh Ahmed Alhussen Nitin Mittal MohdAnul Haq School of Electronics and Electrical Engineering Lovely Professional UniversityPhagwaraPunjab144411India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia University Centre for Research and Development Chandigarh UniversityMohaliPunjab140413India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Many extensive UAV communication networks have used UAV cooperative *** networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base *** only is coverage maximization,but also better connectivity,a fundamental design challenge that must be *** number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)*** bands,however,have become overcrowded as the number of systems that use them *** Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this *** a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV *** paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient *** maximization,power control,and enhanced connection quality are the three steps of the proposed *** satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).

关键词： UAV networks multi-UAV coverage energy-efficient FER SNR

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An Efficient Memory Management Method for Embedded Vector Processors 17th

An Efficient Memory Management Method for Embedded Vector Pr...

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17th International Conference on Communications and Networking, ChinaCom 2022

作者： Li, Shengxuan Ren, Haoqi Zhang, Zhifeng Tan, Bin Wu, Jun Department of Computer Science Tongji University Shanghai China School of Electronic and Information Engineering Jinggangshan University Ji’an China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9783031347894

For processors with vectorial computing units like DSP, it is very important to ensure vector load/store operations alignment of memory blocks, and minimize space wastage when making memory allocations. In this paper, we design and implement a memory management method, vector memory pool, suitable for embedded vector processors. By partitioning an entire block of memory space into many aligned vector objects and making efficiently use of vector processing units, the processing of memory manipulation library functions such as memset/memcpy is accelerated. The implementation and comparative verification of vector memory pool on RT-Thread Nano based on SWIFT DSP was completed, and the running efficiency reached a tens of times improvement compared to the original method. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Vectors

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Design of an RF-CMOS Switched-Capacitor Power Amplifier for NB-IoT RF Transceivers

Design of an RF-CMOS Switched-Capacitor Power Amplifier for ...

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2023 International Young Engineers Forum in Electrical and computer engineering, YEF-ECE 2023

作者： Santos, Ana Isabel Pedro Oliveira, Joao NOVA School of Science and Technology Department of Electrical and Computer Engineering Caparica Portugal Centre of Technology and Systems CTS-UNINOVA Department of Electrical and Computer Engineering Caparica Portugal

ISBN: (纸本)9798350300420

The paper presents the implementation of a Switched Capacitor Power Amplifier (SCPA) to be integrated into a Narrowband Internet of Things (NB-IoT) Transceiver. The SCPA is designed to operate at a frequency of 0.9GHz and aiming the maximum output power allowed by the standard of 23dBm. All the blocks within the SCPA were developed using RF components of a standard 130nm CMOS process, with a 1.2V/2.4V supply voltage. Results show that the SCPA is able to produce a maximum output power of 15.61dBm with a maximum Power-Added Efficiency (PAE) of 26.52% and a Total Harmonic Distortion (THD) of 0.68%. The measured HD2 and HD3 are-70.23dBc and-43.41dBc, respectively. Additional Process, Voltage and Temperature (PVT) corners and Monte Carlo simulations indicate the SCPA operates properly when subject to different conditions and mismatches. Besides the SCPA, a 16 QAM modulation stage is designed in VerilogA in order to evaluate the performance of the RF PA when a sequence of symbols is transmitted. © 2023 IEEE.

关键词： Power amplifiers

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