Keerthan Simha.R, Raghavan H K, Akshatha Prabhu, Pallavi Joshi
{"title":"超越密码:多因素身份验证法实现稳健的数字安全","authors":"Keerthan Simha.R, Raghavan H K, Akshatha Prabhu, Pallavi Joshi","doi":"10.1002/itl2.555","DOIUrl":null,"url":null,"abstract":"Multi‐Factor Authentication (MFA) strengthens digital security by necessitating users to verify their identity. It uses various authentication methods like adding an extra layer of protection beyond conventional passwords. Proposed method introduces a novel MFA system that integrates multiple authentication layers, starting with two phase Graphical password with the traditional email‐password and progressing to facial recognition using Convolutional Neural Networks (CNN) and Quick response (QR) code authentication. To prove the robustness of our method, we are considering some test cases and few performance metrics like delay, accuracy, etc. The results are derived for False positive rates, complexity. The success rate is observed to be more than 93% for the proposed model.","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Beyond passwords: A multi‐factor authentication approach for robust digital security\",\"authors\":\"Keerthan Simha.R, Raghavan H K, Akshatha Prabhu, Pallavi Joshi\",\"doi\":\"10.1002/itl2.555\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi‐Factor Authentication (MFA) strengthens digital security by necessitating users to verify their identity. It uses various authentication methods like adding an extra layer of protection beyond conventional passwords. Proposed method introduces a novel MFA system that integrates multiple authentication layers, starting with two phase Graphical password with the traditional email‐password and progressing to facial recognition using Convolutional Neural Networks (CNN) and Quick response (QR) code authentication. To prove the robustness of our method, we are considering some test cases and few performance metrics like delay, accuracy, etc. The results are derived for False positive rates, complexity. The success rate is observed to be more than 93% for the proposed model.\",\"PeriodicalId\":100725,\"journal\":{\"name\":\"Internet Technology Letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet Technology Letters\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.1002/itl2.555\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Technology Letters","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1002/itl2.555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Beyond passwords: A multi‐factor authentication approach for robust digital security
Multi‐Factor Authentication (MFA) strengthens digital security by necessitating users to verify their identity. It uses various authentication methods like adding an extra layer of protection beyond conventional passwords. Proposed method introduces a novel MFA system that integrates multiple authentication layers, starting with two phase Graphical password with the traditional email‐password and progressing to facial recognition using Convolutional Neural Networks (CNN) and Quick response (QR) code authentication. To prove the robustness of our method, we are considering some test cases and few performance metrics like delay, accuracy, etc. The results are derived for False positive rates, complexity. The success rate is observed to be more than 93% for the proposed model.