Simulation of the Lightweight Blockchain Technique Based on Privacy and Security for Healthcare Data for the Cloud System

Rani, Preeti; Verma, Sonia; Yadav, Satya Prakash; Kumar, B. Vinoth; Naruka, Mahaveer Singh; Kumar, Devendra

doi:10.4018/ijehmc.309436

Cited by 54 publications

(8 citation statements)

References 22 publications

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“…As shown in Figures 10-11, normal is a situation where data of a specific size is written directly to or read from the database in the form of LOBs. SDD is a situation where a database is written or read after the data has been processed using the network-based data self-destruction described here [22]. As you can see, the time cost of reading and writing is proportional to the amount of data required.…”

Section: Prototype System Implementationmentioning

confidence: 99%

Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

Tao Liu, Lihong Hao, Jiwei Tang

2024

jes

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The data self-destruct method based on privacy cloud proposed in this paper can realize the automatic destruction of cloud data after expiration, and based on this method, a self-destruct image protection system is implemented. This project intends to combine the adaptive scale invariant Feature conversion (SIFT) extraction of ciphertext images with binary SIFT to ensure the confidentiality of the images uploaded to the server in the ciphertext space. The security protection of data is realized using Paillier homomorphic encryption technology. The feature of SIFT is extracted from the encrypted region, and it is expressed in binary form to reduce the amount of computation and memory overhead. The experimental results show that this method can effectively prevent the automatic destruction of images after expiration, so as to ensure that the user's personal information is not leaked.

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Section: Prototype System Implementationmentioning

confidence: 99%

Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

Tao Liu, Lihong Hao, Jiwei Tang

2024

jes

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“…This system additionally empowers direct control of the major part of the outcome voltage. The Newton-Rapson technique acquired APWM exchanging designs at the predetermined phase angle [6,7].…”

Section: Related Workmentioning

confidence: 99%

Comparative Analysis of PWM AC Choppers with Different Loads with and Without Neural Network Application

Mariem Bounabi,

Guma Ali

2023

WJCMS

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In this paper, we focus on the "Artificial Neural Network (ANN) based PWM-AC chopper". This system is based on the PWM AC chopper-encouraged single-phase induction motor. The main purpose of this paper is to design and implement an ideal technique regarding speed control. Here analyzed PWM-based AC-AC converter with resistive load, R-L load and finally, the PWM AC chopper is fed to single phase induction for speed control. Using other soft computing and optimization techniques such as Artificial Neural Networks, Fuzzy Logic, Convolution algorithm, PSO, and Neuro Fuzzy can control the Speed. We used Artificial Neural Network to control the Speed of the PWM-AC Single phase induction motor drive. The Neural Network toolbox has been further used for getting desired responses. Neural system computer programs are executed in MATLAB. The performance of the proposed method of ANN system of PWM AC Chopper fed single phase induction motor drive is better than other traditional and base methods for controlling the Speed, based on the MOSFET.

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“…The most recent works in this field focus on hand-engineered features, but various techniques have been developed [12][13][14][15]. In today's image processing and computer vision applications, deep neural networks are the best choice due to the variety and size of datasets [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Facial Expression Recognition System Using a Hybrid Deep Convolutional Neural Network for Multimedia Applications

Obaid,

Alrammahi

2023

Applied Sciences

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Recognizing facial expressions plays a crucial role in various multimedia applications, such as human–computer interactions and the functioning of autonomous vehicles. This paper introduces a hybrid feature extraction network model to bolster the discriminative capacity of emotional features for multimedia applications. The proposed model comprises a convolutional neural network (CNN) and deep belief network (DBN) series. First, a spatial CNN network processed static facial images, followed by a temporal CNN network. The CNNs were fine-tuned based on facial expression recognition (FER) datasets. A deep belief network (DBN) model was then applied to integrate the segment-level spatial and temporal features. Deep fusion networks were jointly used to learn spatiotemporal features for discrimination purposes. Due to its generalization capabilities, we used a multi-class support vector machine classifier to classify the seven basic emotions in the proposed model. The proposed model exhibited 98.14% recognition performance for the JaFFE database, 95.29% for the KDEF database, and 98.86% for the RaFD database. It is shown that the proposed method is effective for all three databases, compared with the previous schemes for JAFFE, KDEF, and RaFD databases.

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Simulation of the Lightweight Blockchain Technique Based on Privacy and Security for Healthcare Data for the Cloud System

Cited by 54 publications

References 22 publications

Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

Comparative Analysis of PWM AC Choppers with Different Loads with and Without Neural Network Application

An Intelligent Facial Expression Recognition System Using a Hybrid Deep Convolutional Neural Network for Multimedia Applications

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