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15th International Conference on information technology and Electrical Engineering, ICITEE 2023

作者： Bussabong, Naphat Anusas-Amornkul, Tanapat King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Computer and Information Science Bangkok Thailand

ISBN: (纸本)9798350304466

A keystroke dynamics is a simple example of a biometric authentication by using a typing rhythm on a keyboard without any special device. Previous research used Euclidean distance to distinguish between an authentic user and an imposter [1]. However, the Euclidean distance has a flaw in that a distance could be the same even though the keystroke rhythms are different. Therefore, this paper proposed to enhance the keystroke dynamics authentication by using a keystroke vector and calculating a standard deviation for each key to give different weights such that the variations of each keystroke is taking into account. A dataset is similar in [1] but some data is different. The performance was measured using Equal Error Rate (EER) and the result showed that the EER was 3.33%, compared to 4% in [1]. © 2023 IEEE.

关键词： Authentication

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Detection and Classification of Malignant Melanoma Using Deep Features of NASNet

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SN computer science 2023年第1期4卷 1-13页

作者： Abbas, Qaiser Gul, Anza Department of Computer Science University of Engineering and Technology (UET) Lahore Pakistan Department of Information Technology Lahore Leads University Lahore Pakistan

Skin cancer is one of the leading causes of death worldwide. Malignant melanoma is the most lethal form of skin cancer which can spread to other areas of the body. Although it is rare, still 75% of skin cancer deaths are caused due to malignant melanoma. Early detection can help to combat melanoma. However, early detection is very challenging due to various visual similarities between melanoma and non-melanoma. In this paper, we present an automated system for early melanoma detection. Our technique is based on deep transfer learning, in which we utilized a pre-trained neural network model named as NASNet. The features from the pre-trained model are transferred to the new dataset to detect melanoma. We modified the original architecture and added global average pooling and our classification layers. To overcome issues of a smaller dataset, we use carefully selected label and feature-preserving geometric transformations to increase images. The proposed model is trained on dermoscopic images from the International Skin Imaging Collaboration (ISIC 2020) dataset. As compared to the prior methods, our proposed model is efficient and shows state-of-the-art performance with an accuracy of more than 97% on the test dataset. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep learning Deep transfer learning Dermoscopic images Melanoma detection NASNet Skin cancer

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Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

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computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

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A Mobile-Based Fuzzy Expert system for Diagnosing COVID-19

A Mobile-Based Fuzzy Expert System for Diagnosing COVID-19

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2024 International Conference on science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Mustapha, Abiodun Muyideen Ogunbiyi, Temitope Elizabeth Aleburu, Deborah Dorcas Alonge, Christianah Yetunde Anchor University Department of Mathematical Sciences Lagos State Lagos Nigeria Bells University of Technology Department of Computer Science and Information Technology Ogun State Ota Nigeria Redeemer's College of Technology and Management Department of Computer Science Ogun State Nigeria

ISBN: (纸本)9798350358155

In 2020, COVID-19 was a great pandemic that affected the entire world. Millions of people across the world died and businesses were affected. Several individuals have had to spend very heavy medical bills or lose their lives as a result of late diagnosis. This is because the general diagnosis approach is based on medical practitioners' practical involvement. In this research, we present a mobile-based expert system for diagnosing COVID-19 using a Mamdani fuzzy symptom classifier that serve as an alternative to medical laboratory diagnosis. Three phases were involved in this development and they are: information elicitation and feature extraction (validation), knowledge base establishment, and information retrieval via the user interface. The mobile App was built using Flutter, Dart, and MySQL. The front end of the system, which is the mobile application, was built with Flutter. The system's front end was written in Dart, while the back end, which contained the COVID-19 data set, was written in MySQL. The identified inputs are the symptoms that were run through an inference engine and fuzzy inference rule to ascertain the severity of the disease in the patients. The result shows that the system was able to diagnose the disease through an interactive questions and responses from the user interface by the user. It becomes easy for medical doctors to recommend solutions to them. The evaluation performance of the system returned very high accuracy and was efficient in its diagnosis process. The result clearly indicates that the system is well accepted. Being a mobile-based system, accessing and engaging in its experience is faster. © 2024 IEEE.

关键词： COVID-19

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A Study on Cypher Assignment Based on Secrecy Capacity

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International Journal of Network Security 2024年第2期26卷 167-172页

作者： Yang, Cheng-Ying Chen, Jong-Shin Yao, Jenq-Foung J F Hwang, Min-Shiang Department of Computer Science University of Taipei Taipei Taiwan Department of Information and Communication Engineering Chaoyang University of Science and Technology Taiwan Computer Science Georgia College and State University Milledgeville United States Department of Computer Science & Information Engineering Asia University Taiwan Fintech and Blockchain Research Center Asia University Taiwan 500 Lioufeng Rd. Wufeng Taichung41354 Taiwan

Accessing wireless services is convenient but not secure. The issue of privacy and security is highly demanded on the internet. The information is sent with the undesired threats of eavesdroppers. Secure communication enables the desired receiver to correctly and successfully receive the information without interruption. In the meantime, a secure system protects the transmitted information from the eavesdroppers. Traditionally, encryption, authorization, and authentication schemes could be employed to protect from eavesdroppers. However, the unanticipated attacks have been developing. According to Shannon’s perfect communication, the undesired receivers, such as eavesdroppers, could receive an error-free cryptogram. Based on the physical-layer security, it could be expected that secure communication could be implemented without complex computing at the higher level. The physical-layer security coding scheme aims to achieve an extremely low decoding error probability and obtain a critical security level against attackers. The positive secrecy capacity (secrecy rate) could provide secure communication. Hence, a positive secrecy capacity is the primary concern in the system. Besides, physical-layer security coding is not only to help the system achieve a critical level of security but also to obtain an extremely low decoding error probability. However, it decreases the bandwidth efficiency and suffers the system performance. Hence, the tradeoff between the security level and the coding rate is important to lead a secure communication. © (2023), (Femto Technique Co.). All Rights Reserved.

关键词： Bandwidth

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Machine Learning-based Stable P2P IPTV Overlay

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computers, Materials & Continua 2022年第6期71卷 5381-5397页

作者： Muhammad Javid Iqbal Ihsan Ullah Muhammad Ali Atiq Ahmed Waheed Noor Abdul Basit Directorate of Information Technology Sardar Bahadur Khan Women’s UniversityQuettaPakistan Department of Computer Science and Information Technology University of BalochistanQuettaPakistan

Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service *** Internet was not designed for such services during its inception,such a service poses some serious challenges including cost and ***-to-Peer(P2P)Internet Protocol Television(IPTV)is an application-level distributed paradigm to offer live video *** terms of ease of deployment,it has emerged as a serious alternative to client server,Content Delivery Network(CDN)and IP multicast ***,P2P approach has struggled to provide the desired streaming quality due to a number of *** of peers in a network is one of themajor issues among *** of the existing approaches address this issue through older-stable *** paper first extensively investigates the older-stable principle to observe its validity in different *** is observed that the older-stable principle does not hold in several of ***,it utilizes machine learning approach to predict the stability of *** work evaluates the accuracy of severalmachine learning algorithms over the prediction of stability,where the Gradient Boosting Regressor(GBR)out-performs other ***,this work presents a proof-of-concept simulation to compare the effectiveness of older-stable rule and machine learning-based predictions for the stabilization of the *** results indicate that machine learning-based stability estimation significantly improves the system.

关键词： P2P IPTV live video streaming user behavior overlay networks stable peers machine learning

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Faba Bean Disease Detection Using Deep Learning Techniques

Faba Bean Disease Detection Using Deep Learning Techniques

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2023 International Conference on Cyber Management and Engineering, CyMaEn 2023

作者： Salau, Ayodeji Olalekan Abeje, Bekalu Tadele Faisal, Abeer Naser Asfaw, Tesfa Tegegne Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria Haramaya University College of Computing and Informatics Department of Information Technology Ethiopia Institute of Technology Faculty of Computing Bahir Dar University Department of Computer Science Ethiopia University of Sumer College of Computer Science and Information Technology Al-Rifai Iraq

ISBN: (纸本)9781665493291

Faba bean (Vicia faba L.) is an important cash crop for animal and human consumption in many countries, especially Ethiopia due to its high protein content and high rate of production. It also improves soil fertility with the help of bacteria, which forms nodules on its roots. Ethiopia is the second largest faba bean producer;however, according to research, the yield is generally low. Among the constraints contributing to low productivity of the crop, disease is the most important. Even though there are countermeasures such as the use of chemical sprays, which is used to reduce the damage or eliminate the disease, an effective disease identification technique is still required. Chocolate spot, faba bean gal, and rust are the most common diseases of faba beans. To effectively detect the disease, in this paper, we propose an end-to-end CNN model for training before and after the dataset is preprocessed. The CNN end-to-end model is trained with raw images and achieves 92.1% training accuracy. Also, the model is trained with preprocessed data and it achieves a training accuracy of 98.14% for the end-to-end CNN classifier. The results show that the proposed approach is suitable for faba bean disease detection and can be employed to detect diseases of other crops. © 2023 IEEE.

关键词： Convolutional neural networks

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Chiang Rai Phra That Nine Choms Attraction Promoting Mobile Application for Cultural Tourism 20

Chiang Rai Phra That Nine Choms Attraction Promoting Mobile ...

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20th International Conference on Electrical Engineering/Electronics, computer, Telecommunications and information technology, ECTI-CON 2023

作者： Chaidee, Kamonlak Boontasri, Kanchana Chaidee, Ekkachai Wongchai, Wiwat Phamon, Suphakorn Preedee, Suruswadee Rajamangala University of Technology Lanna Chiangrai Faculty of Business Administration and Liberal Arts Department of Computer Information System Chiang Rai Thailand

ISBN: (纸本)9798350310467

This study aimed to create a mobile application to promote and guide the cultural tourism attraction Phra That Nine Choms in Chiang Rai Province, Thailand. The critical information about Phra That Nine Choms is gathered and analyzed to identify the problem and user requirements. The operation of the mobile application is designed using a use case diagram, class diagram, and sequence diagram. The Java programming language creates the mobile application through the Eclipse program, Android SDK, and JAVA JDK development tools. 95 Thai and foreign tourists tested the resulting application. Their satisfaction was evaluated through a questionnaire and analyzed. The interpreting results showed that the mobile application is suitable for providing travel recommendations and can serve as a guide for future development to support tourism activities, particularly for cultural and local attractions. © 2023 IEEE.

关键词： Global positioning system

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Assessing Secure OpenID-Based EAAA Protocol to Prevent MITM and Phishing Attacks in Web Apps

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computers, Materials & Continua 2023年第6期75卷 4713-4733页

作者： Muhammad Bilal Sandile C.Showngwe Abid Bashir Yazeed Y.Ghadi College of Computer Science and Technology Zhejiang UniversityHangzhou310027China Department of Mathematical Statistics and Actuarial Science Faculty of Natural and Agricultural SciencesUniversity of the Free StateBloemfontein9301South Africa Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science/Software Engineering Al Ain UniversityAbu DhabiUAE

To secure web applications from Man-In-The-Middle(MITM)and phishing attacks is a challenging task *** this purpose,authen-tication protocol plays a vital role in web communication which securely transfers data from one party to *** authentication works via OpenID,Kerberos,password authentication protocols,***,there are still some limitations present in the reported security *** this paper,the presented anticipated strategy secures both Web-based attacks by leveraging encoded emails and a novel password form pattern *** proposed OpenID-based encrypted Email’s Authentication,Authorization,and Accounting(EAAA)protocol ensure security by relying on the email authenticity and a Special Secret Encrypted Alphanumeric String(SSEAS).This string is deployed on both the relying party and the email server,which is unique and *** first authentication,OpenID Uniform Resource Locator(URL)identity,is performed on the identity provider side.A second authentication is carried out by the hidden Email’s server side and receives a third authentication *** Email’s third SSEAS authentication link manages on the relying party(RP).Compared to existing cryptographic single sign-on protocols,the EAAA protocol ensures that an OpenID URL’s identity is secured from MITM and phishing *** study manages two attacks such as MITM and phishing attacks and gives 339 ms response time which is higher than the already reported methods,such as Single Sign-On(SSO)and *** experimental sites were examined by 72 information technology(IT)specialists,who found that 88.89%of respondents successfully validated the user authorization provided to them via *** proposed EAAA protocol minimizes the higher-level risk of MITM and phishing attacks in an OpenID-based atmosphere.

关键词： Secure user authentication SSO OpenID phishing attack MITM attack

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Broadband spin and angle co‑multiplexed waveguide‑based metasurface for six‑channel crosstalk‑free holographic projection

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eLight 2024年第1期4卷 223-237页

作者： Zeyang Liu Hao Gao Taigao Ma Vishva Ray Niu Liu Xinliang Zhang L.Jay Guo Cheng Zhang School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China Department of Physics University of MichiganAnn ArborMI 48109USA Lurie Nanofabrication Facility Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborMI 48109USA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA

Metasurface-based holograms,or metaholograms,offer unique advantages including enhanced imaging quality,expanded field of view,compact system size,and broad operational ***-channel metaholograms,capable of switching between multiple projected images based on the properties of illuminating light such as state of polarization and angle of incidence,have emerged as a promising solution for realizing switchable and dynamic holographic ***,existing designs typically grapple with challenges such as limited multiplexing channels and unwanted crosstalk,which severely constrain their practical ***,we present a new type of waveguidebased multi-channel metaholograms,which support six independent and fully crosstalk-free holographic display channels,simultaneously multiplexed by the spin and angle of guided incident light within the glass *** employ a k-space translation strategy that allows each of the six distinct target images to be selectively translated from evanescent-wave region to the center of propagation-wave region and projected into free space without crosstalk,when the metahologram is under illumination of a guided light with specific spin and azimuthal *** addition,by tailoring the encoded target images,we implement a three-channel polarization-independent metahologram and a two-channel full-color(RGB)***,the number of multiplexing channels can be further increased by expanding the k-space’s central-period region or combing the k-space translation strategy with other multiplexing techniques such as orbital angular momentum *** work provides a novel approach towards realization of high-performance and compact holographic optical elements with substantial information capacity,opening avenues for applications in AR/VR displays,image encryption,and information storage.

关键词： Metasurface Multi-channel metahologram Color metahologram Waveguide display

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