Security Risks of the Metaverse World

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2022, Номер 16(13), С. 4 - 14

Опубликована: Июль 11, 2022

An interesting paradigm is a metaverse which represents the next generation of using internet to improve human lives and provide new way communicate by building system that let user represented their avatar work, socialize play virtually integrating multiple technologies such as blockchain, artificial intelligence well virtual augmented reality. However, this may preserve many problems related security privacy starting from data breaches identity theft, in paper an overview world architecture connects real discuss main risks within Metaverse

Язык: Английский

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Combining Artificial Intelligence and Image Processing for Diagnosing Diabetic Retinopathy in Retinal Fundus Images

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2022, Номер 18(13), С. 131 - 151

Опубликована: Окт. 19, 2022

Retinopathy is an eye disease caused by diabetes, and early detection treatment can potentially reduce the risk of blindness in diabetic retinopathy sufferers. Using retinal Fundus images, be diagnosed, recognized, treated. In current state art, sensitivity specificity are lacking. However, there still a number problems to solved state-of-the-art techniques like performance, accuracy, being able identify DR effectively with greater accuracy. this paper, we have developed new approach based on combination image processing artificial intelligence that will meet performance criteria for disease-causing diabetes images. Automatic has been proposed carried out several stages. The analysis was MATLAB using software-based simulation, results were then compared those expert ophthalmologists verify their Different types represented experimental evaluation, including exudates, micro-aneurysms, hemorrhages. accuracies shown experiments than 98.80 percent.

Язык: Английский

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Trends in using deep learning algorithms in biomedical prediction systems

Frontiers in Neuroscience, Год журнала: 2023, Номер 17

Опубликована: Ноя. 9, 2023

In the domain of using DL-based methods in medical and healthcare prediction systems, utilization state-of-the-art deep learning (DL) methodologies assumes paramount significance. DL has attained remarkable achievements across diverse domains, rendering its efficacy particularly noteworthy this context. The integration with health systems enables real-time analysis vast intricate datasets, yielding insights that significantly enhance outcomes operational efficiency industry. This comprehensive literature review systematically investigates latest solutions for challenges encountered healthcare, a specific emphasis on applications domain. By categorizing cutting-edge approaches into distinct categories, including convolutional neural networks (CNNs), recurrent (RNNs), generative adversarial (GANs), long short-term memory (LSTM) models, support vector machine (SVM), hybrid study delves their underlying principles, merits, limitations, methodologies, simulation environments, datasets. Notably, majority scrutinized articles were published 2022, underscoring contemporaneous nature research. Moreover, accentuates forefront advancements techniques practical within realm while simultaneously addressing hinder widespread implementation image segmentation domains. These discerned serve as compelling impetuses future studies aimed at progressive advancement systems. evaluation metrics employed reviewed encompass broad spectrum features, encompassing accuracy, precision, specificity, F-score, adoptability, adaptability, scalability.

Язык: Английский

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Secured Transfer and Storage Image Data for Cloud Communications

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2023, Номер 19(06), С. 4 - 17

Опубликована: Май 16, 2023

In cloud computing, resources are used to communicate instead of local servers or individual devices. However, sharing among several users is a difficult issue in communication. Cryptography and steganography techniques for storage address data security challenges. This paper presents novel method securely encrypting image transmission link exchange with service. There two phases accomplish the encryption process, first phase encrypts file by XORing it random key that generated new hybrid chaotic map. The second converts encrypted format audio add another layer improve secure transfer. using map has benefit having more than 10256 spaces necessary level security. Based on statistical analysis encryption, quality evaluated criteria, results demonstrate algorithm's ability resist

Язык: Английский

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Analysis of preprocessing for generative adversarial networks: A case study on color fundoscopy to fluorescein angiography image-to-image translation

Computer Methods and Programs in Biomedicine Update, Год журнала: 2025, Номер unknown, С. 100179 - 100179

Опубликована: Янв. 1, 2025

Язык: Английский

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Classification of diabetic retinopathy grades using CNN feature extraction to segment the lesion

International Journal of Computational and Experimental Science and Engineering, Год журнала: 2024, Номер 10(4)

Опубликована: Дек. 18, 2024

Diabetes's microvascular aftereffect, diabetic retinopathy (DR), is the primary cause of eyesight loss in globe. In order to prevent vision impairment and intervene promptly, early detection precise classification DR severity are essential. Using standard methods for diagnosing requires ophthalmologists grade cases by hand, a process that can be laborious, subjective, subject observer error. supervised learning task classification, data instances classified into predefined classes based on features. The relation between traits found from labelled data. After training completed, unseen frequent reason (DR) diabetes. Visual damage prevented identifying degree at right time. For grading DR, deep techniques very effective with maximum possible accuracy. proposed model useful accurately classifying images using feature extraction lesion segmentation, implementing patterns images. ReLU activation function used model. CNN important applying Convolution layers, edges, textures, forms identified. As proceeds layer layer, complicated photos learned model, analysed better. features were extracted segmentation classification. helpful improving convergence also patterns. Among other functions, has higher computational efficiency therefore which suits well application. A strong framework grade, extraction. categorization evaluated visualization calculated metrics effective.

Язык: Английский

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Reliable Fuzzy-Based Multi-Path Routing Protocol Based on Whale Optimization Algorithm to Improve QOS in 5G Networks for IOMT Applications

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2023, Номер 17(06), С. 139 - 155

Опубликована: Март 21, 2023

The Internet of Medical Things (IoMT) faces stiff competition from the 5th Generation (5G) communication standard, which includes attributes like short and long transmission ranges, Device to (D2D) connectivity, low latency, high node density. To function in linked ecosystem, IoMT based on 5G is anticipated have a diversity energy mobility. It currently difficult create an routing system that maximizes efficiency, lowers increases network lifespan. "Quality Services (QoS)" 5G-based improved by Reliable Fuzzy-based Multi-path shown this study. Whale Optimization Algorithm (WOA) enhances protocol performance. residual energy-based Cluster Head (CH) selection strategy rotates CH location among nodes with greater levels than others. method chooses following set CHs for suitable applications considering initial energy, ideal value CHs. According simulation results, our suggested technique QoS comparison current approaches.

Язык: Английский

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Cyber Security for Medical Image Encryption using Circular Blockchain Technology Based on Modify DES Algorithm

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2023, Номер 19(03), С. 99 - 112

Опубликована: Март 14, 2023

Recently, with the requirement for protecting privacy of images transferred over internet and media networks. The need to protect these from hacking by unauthorized persons manipulation has become very important in this research, Block chain technology was used its importance cybersecurity. To maintain confidentiality patient's medical data, as a result, solve problem requires increasing strength key encryption process, which is responsible ensuring security image .In paper, it proposed use block Data Encryption Standard (DES) algorithm purpose degree transmitted enhancing during process encrypting well authentication between sender receiver. Experimental outcomes manifested that gained via suggested higher, performing goal information image, presented results obtained Entropy, MSE, PSNR.

Язык: Английский

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A Novel Approach for Electronic Medical Records Based on NFT-EMR

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2023, Номер 19(05), С. 93 - 104

Опубликована: Апрель 27, 2023

saving the patient medical record electronically is done via electronic records (EMRs) where all patient-related information that consider private and sensitive usually related to treatment process, as well diagnoses process of a specific this needs be shared re-submit by many peers doctors with each, In paper, propose novel approach for system using non-fungible token (NFT) based on customized permission blockchain built secret sharing technology reduce key management overhead provide readable extension ledger ensure it easy read access from any type computer. The uses NFT (NFT-EMR) ensures guarantees availability, privacy, security providing authority over his data proof ownership which shares consistency can used in real-world between hospitals centers within metaverse world. NFT-ERM was evaluated main evaluation factors evaluate compared standard ERM system.

Язык: Английский

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Hybrid Cyber-Security Model for Attacks Detection Based on Deep and Machine Learning

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2022, Номер 18(11), С. 17 - 30

Опубликована: Авг. 31, 2022

Nowadays, numerous attacks can be considered high risks in terms of the security Wireless Sensor Networks (WSN). As a result, different applications are introduced to manage data and information exchange related sides save transmission data. Recently, most classified as cyber ones. These interest system halting destroying rather than stealing In this paper, cyber-attacks detection is proposed based on an intelligent hybrid model that uses deep machine learning technologies. The improves cyber-attack speed. addition, feature reduction using methods (PCA SVD) select features adopted classes attacks. This positively affect deep-learning complexity. obtained results demonstrate superiority model-based comparison traditional ones reaching accuracy 99.98%, 100%, 100% for precision, recall, F1-measure respectively, reducing time 23s datasets Message Queuing Telemetry Transport-Dataset (MQTT-DS) Dataset (WSN-DS).

Язык: Английский

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