{"title":"基于用户行为分析的连续认证系统","authors":"Ines Brosso, A. L. Neve, G. Bressan, W. Ruggiero","doi":"10.1109/ARES.2010.63","DOIUrl":null,"url":null,"abstract":"This paper presents a continuous authentication system based on user behavior analysis that makes use of environmental context information, users’ behavior analysis and Neuro-Fuzzy Logic. This system must be able to acquire information in context, making them into a computational environment. This information is the basis of user behavior. The System, based on the evidences of the behavior, establishes if it can trust the user or not. According to the user behavior, levels of trust are released, to access the application software. Weights are attributed in the fuzzyfication process, according to the rules that were previously established for the parameters which help to establish the evidences of behavioral trust, in its different degrees. The neuro-fuzzy logic allows that the user behavioral database be continuously updated, interacting with the fuzzyfication mechanism, so as to keep trust levels updated according to the user behavior, in a more accurate and faithful way.","PeriodicalId":360339,"journal":{"name":"2010 International Conference on Availability, Reliability and Security","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"A Continuous Authentication System Based on User Behavior Analysis\",\"authors\":\"Ines Brosso, A. L. Neve, G. Bressan, W. Ruggiero\",\"doi\":\"10.1109/ARES.2010.63\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a continuous authentication system based on user behavior analysis that makes use of environmental context information, users’ behavior analysis and Neuro-Fuzzy Logic. This system must be able to acquire information in context, making them into a computational environment. This information is the basis of user behavior. The System, based on the evidences of the behavior, establishes if it can trust the user or not. According to the user behavior, levels of trust are released, to access the application software. Weights are attributed in the fuzzyfication process, according to the rules that were previously established for the parameters which help to establish the evidences of behavioral trust, in its different degrees. The neuro-fuzzy logic allows that the user behavioral database be continuously updated, interacting with the fuzzyfication mechanism, so as to keep trust levels updated according to the user behavior, in a more accurate and faithful way.\",\"PeriodicalId\":360339,\"journal\":{\"name\":\"2010 International Conference on Availability, Reliability and Security\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Availability, Reliability and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARES.2010.63\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Availability, Reliability and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARES.2010.63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Continuous Authentication System Based on User Behavior Analysis
This paper presents a continuous authentication system based on user behavior analysis that makes use of environmental context information, users’ behavior analysis and Neuro-Fuzzy Logic. This system must be able to acquire information in context, making them into a computational environment. This information is the basis of user behavior. The System, based on the evidences of the behavior, establishes if it can trust the user or not. According to the user behavior, levels of trust are released, to access the application software. Weights are attributed in the fuzzyfication process, according to the rules that were previously established for the parameters which help to establish the evidences of behavioral trust, in its different degrees. The neuro-fuzzy logic allows that the user behavioral database be continuously updated, interacting with the fuzzyfication mechanism, so as to keep trust levels updated according to the user behavior, in a more accurate and faithful way.