Chandra Hermawan Heruatmadja, Meyliana, A. Hidayanto, Harjanto Prabowo
{"title":"生物识别技术作为虚拟现实环境中的安全认证:系统的文献综述","authors":"Chandra Hermawan Heruatmadja, Meyliana, A. Hidayanto, Harjanto Prabowo","doi":"10.1109/ICONAT57137.2023.10080713","DOIUrl":null,"url":null,"abstract":"Virtual Reality (VR) is a type of technology that enables users to interact each other inside artificial environments. While this technology makes life easier, it also creates new issues, particularly in the areas of security and authentication. In contrast to authentication techniques in general, where users can use a pin or password safely and securely, in VR this security model creates a new security loophole and the better authentication method and more secure authentication in virtual reality have both been the subject of numerous studies including using biometric. In order to learn more about biometric authentication, which is the most common issue in VR authentication research, this research is conducted in a systematic literature review to answer the research questions what biometric media, HeadMounted Display (HMD), also examines what machine learning and biometric media are frequently used, and how accurate biometric authentication can identify individual person, and in the end, to help future researchers to shorten the time in conducting research or have the right authentication method for a VR service. Result of the research found that to build biometric authentication model, researcher often use k-Nearest Network and Support Vector Machine (SVM) machine learning, and finger vein and hand movement are the most accurate biometric authentication among others.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Biometric as Secure Authentication for Virtual Reality Environment: A Systematic Literature Review\",\"authors\":\"Chandra Hermawan Heruatmadja, Meyliana, A. Hidayanto, Harjanto Prabowo\",\"doi\":\"10.1109/ICONAT57137.2023.10080713\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Virtual Reality (VR) is a type of technology that enables users to interact each other inside artificial environments. While this technology makes life easier, it also creates new issues, particularly in the areas of security and authentication. In contrast to authentication techniques in general, where users can use a pin or password safely and securely, in VR this security model creates a new security loophole and the better authentication method and more secure authentication in virtual reality have both been the subject of numerous studies including using biometric. In order to learn more about biometric authentication, which is the most common issue in VR authentication research, this research is conducted in a systematic literature review to answer the research questions what biometric media, HeadMounted Display (HMD), also examines what machine learning and biometric media are frequently used, and how accurate biometric authentication can identify individual person, and in the end, to help future researchers to shorten the time in conducting research or have the right authentication method for a VR service. Result of the research found that to build biometric authentication model, researcher often use k-Nearest Network and Support Vector Machine (SVM) machine learning, and finger vein and hand movement are the most accurate biometric authentication among others.\",\"PeriodicalId\":250587,\"journal\":{\"name\":\"2023 International Conference for Advancement in Technology (ICONAT)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference for Advancement in Technology (ICONAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONAT57137.2023.10080713\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference for Advancement in Technology (ICONAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONAT57137.2023.10080713","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biometric as Secure Authentication for Virtual Reality Environment: A Systematic Literature Review
Virtual Reality (VR) is a type of technology that enables users to interact each other inside artificial environments. While this technology makes life easier, it also creates new issues, particularly in the areas of security and authentication. In contrast to authentication techniques in general, where users can use a pin or password safely and securely, in VR this security model creates a new security loophole and the better authentication method and more secure authentication in virtual reality have both been the subject of numerous studies including using biometric. In order to learn more about biometric authentication, which is the most common issue in VR authentication research, this research is conducted in a systematic literature review to answer the research questions what biometric media, HeadMounted Display (HMD), also examines what machine learning and biometric media are frequently used, and how accurate biometric authentication can identify individual person, and in the end, to help future researchers to shorten the time in conducting research or have the right authentication method for a VR service. Result of the research found that to build biometric authentication model, researcher often use k-Nearest Network and Support Vector Machine (SVM) machine learning, and finger vein and hand movement are the most accurate biometric authentication among others.