IJCI. International Journal of Computers and Information最新文献_第3页

Arabic Language Sentiment Analysis using Bidirectional Long Short Term Memory 基于双向长短期记忆的阿拉伯语情感分析

IJCI. International Journal of Computers and Information Pub Date : 2022-11-07 DOI: 10.21608/ijci.2022.157244.1084

Osama Elsamadony, A. Keshk, Amira Abdelatey

引用次数: 0

Assessment Reliability for Open-Source Software using Probabilistic Models and Marine Predators Algorithm 基于概率模型和海洋捕食者算法的开源软件可靠性评估

IJCI. International Journal of Computers and Information Pub Date : 2022-11-04 DOI: 10.21608/ijci.2022.151916.1080

Islam A Ramadan, Hany Harb, Hamdy M. Mousa, M. Malhat

引用次数: 1

Keystroke dynamics based user authentication using Histogram Gradient Boosting 基于直方图梯度增强的按键动力学用户认证

IJCI. International Journal of Computers and Information Pub Date : 2022-09-28 DOI: 10.21608/ijci.2022.155605.1081

Mina I. S. Ibrahim, Hussien AbdelRaouf, Khalid Amin, N. Semary

{"title":"Keystroke dynamics based user authentication using Histogram Gradient Boosting","authors":"Mina I. S. Ibrahim, Hussien AbdelRaouf, Khalid Amin, N. Semary","doi":"10.21608/ijci.2022.155605.1081","DOIUrl":"https://doi.org/10.21608/ijci.2022.155605.1081","url":null,"abstract":"User authentication is a vital part of securing digital services and preventing unauthorized users from gaining access to the system. Nowadays, organizations use Multi-Factor Authentication (MFA) to provide robust protection by utilizing two or more identity procedures instead of using Single Factor Authentication (SFA) which became less secure. Keystroke dynamics is a behavioral biometric that examines a user’s typing rhythm to determine the subject’s legitimacy using the system. Keystroke dynamics have a minimal implementation cost and do not need special hardware in the authentication process since the gathering of typing data is reasonably straightforward and does not involve additional effort from the user. In this work, we present an efficient approach that uses the quantile transformation that transforms data distribution into uniform distribution which significantly reduces the impact of outlier and extreme values. Histogram Gradient Boosting is employed as the primary classifier for the training and testing phase. Our proposed approach is evaluated on Carnegie Mellon University (CMU) keystroke benchmark dataset which has achieved 97.96% of average accuracy and 0.014 of average equal error rate (EER) across all subjects which outperforms all the previous advances in both machine and deep learning approaches.","PeriodicalId":137729,"journal":{"name":"IJCI. International Journal of Computers and Information","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128612730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Comparative Analysis of COVID-19 Diagnosis Using Lung Ultrasound Based on Convolutional Neural Networks 基于卷积神经网络的肺部超声诊断COVID-19的对比分析

IJCI. International Journal of Computers and Information Pub Date : 2022-09-10 DOI: 10.21608/ijci.2022.151629.1079

Ola Elkhuoly, M. Malhat, A. Keshk, M. Elsabaawy

引用次数: 0

Editorial: Introduction, IJCI Editorial Board, Sample paper and Table of contents 编辑:引言，IJCI编辑委员会，样本论文和目录表

IJCI. International Journal of Computers and Information Pub Date : 2022-09-01 DOI: 10.21608/ijci.2022.259000

引用次数: 0

A blind fragile watermarking for 3D triangular model based on curvature features and chaos sequence 基于曲率特征和混沌序列的三维三角形模型脆弱盲水印

IJCI. International Journal of Computers and Information Pub Date : 2022-09-01 DOI: 10.21608/ijci.2022.120581.1068

kariman mamdouh, N. Semary, Hatem Ahmed

{"title":"A blind fragile watermarking for 3D triangular model based on curvature features and chaos sequence","authors":"kariman mamdouh, N. Semary, Hatem Ahmed","doi":"10.21608/ijci.2022.120581.1068","DOIUrl":"https://doi.org/10.21608/ijci.2022.120581.1068","url":null,"abstract":"Noura A.Semarya,Kariman M.Mabrouka,, Hatem Abdul-Kaderb a Information Technology dept., Faculty of Computers and Information, Menoufia University, Menoufia 32511, Egypt b Information system dept., Faculty of Computers and Information, Menoufia University, Menoufia 32511, Egypt kariman.mamdouh@ci.menofia.edu.eg Abstract 3D models unauthorized modification is an attractive research problem nowadays due to the widespread availability of technologies and designs on the internet. In this paper, we propose a blind fragile watermarking scheme in the spatial domain for 3D model authentication based on the curvature features of the 3D model and chaos sequence. First, we compute the curvature feature for every vertex of the 3D model, after that, the vertices are classified into 3 classes: flat, peak, and In-between vertices using K-means clustering algorithm. We suggested two methods for embedding the watermark based on the least significant bit (LSB) substitution technique; Cluster Type-based Embedding (CTE) and Cluster Size-based Embedding (CSE). The proposed methods employ a Chaos sequence generator to generate a Chaos sequence that is used to generate the embedded watermark, where the tampering region can be verified and located by the Chaos sequence-based watermark check. Many assessment methods are employed to evaluate the proposed method with various unauthorized attacks like rotation, translation, scaling, cropping, and noise addition. The experiment results show an improvement of embedding imperceptibility as well as tempered regions detection compared to existing literature works.","PeriodicalId":137729,"journal":{"name":"IJCI. International Journal of Computers and Information","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130533920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving COVID 19 Detection based on a hybrid data mining approach 基于混合数据挖掘方法改进COVID - 19检测

IJCI. International Journal of Computers and Information Pub Date : 2022-09-01 DOI: 10.21608/ijci.2022.145681.1078

Dina Goda, N. Mahmoud

{"title":"Improving COVID 19 Detection based on a hybrid data mining approach","authors":"Dina Goda, N. Mahmoud","doi":"10.21608/ijci.2022.145681.1078","DOIUrl":"https://doi.org/10.21608/ijci.2022.145681.1078","url":null,"abstract":"The worldwide spread of coronavirus disease (COVID-19) has become a threatening risk for global public health. Currently, doctors resort to PCR analysis, however, it suffers from low accuracy problems. On the other hand, Convolutional neural network (CNN) and despite its high accuracy incorrect classification, it takes a long time to train data, in addition it requires large training dataset. In this paper, we propose a hybrid approach for COVID-19 detection and diagnosis. Our contribution consists of two phases to provide high detection accuracy. In the first phase, we propose a hybrid features-fusion phase that works by fusing four common features extracted from medical image, Row pixel intensity, Colour histogram, Harlick texture and Threshold. Each single classifier is fed with these four features and yielded a 4 different predictions for each feature. A well-known voting technique is then applied to provide final predication result for each classifier. Secondly, the ensemble stacking technique is employed to fuse predication of each classifier, which significantly improves final detection accuracy. The proposed approach has been quantitatively evaluated on a public dataset of 5000 CT- images. The proposed approach yields accuracy of 99.3% and overcome traditional approaches such as KNN (K-nearest neighbours) that yields 92%, and SVM (Support vector machines) that yields 92% comparable computational time that is approximately 4.9 minutes.","PeriodicalId":137729,"journal":{"name":"IJCI. International Journal of Computers and Information","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126198450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Techniques for DDoS Attack in SDN: A Comparative Study SDN中DDoS攻击技术的比较研究

IJCI. International Journal of Computers and Information Pub Date : 2022-08-06 DOI: 10.21608/ijci.2022.133407.1073

A. Yaser, Hamdy M. Mousa, M. Hussien

引用次数: 0

An Enhanced Technique for Skin Lesion Diagnosis using Dermoscopic Images 一种利用皮肤镜图像诊断皮肤病变的增强技术

IJCI. International Journal of Computers and Information Pub Date : 2022-07-18 DOI: 10.21608/ijci.2022.137601.1075

Aya Mosa, A. Afifi, Khalid Amin

引用次数: 0

Ride-Sharing Services: From Centralization to Decentralization 拼车服务:从集中到分散

IJCI. International Journal of Computers and Information Pub Date : 2022-07-14 DOI: 10.21608/ijci.2022.130527.1072

Nesma Mahmoud, Asmaa Ali, Hatem Abdel-Kader

引用次数: 2