{"title":"Spoofing analysis of mobile device data as behavioral biometric modalities","authors":"T. Neal, D. Woodard","doi":"10.1109/BTAS.2017.8272683","DOIUrl":null,"url":null,"abstract":"While mobile devices are no longer a new technology, using the data generated from the use of these devices for security purposes has just recently been explored. Current methods, such as passwords, are quickly becoming antiquated, lacking the robustness, accuracy, and convenience desired to serve as reliable security measures. Since, researchers have resorted to alternative techniques, such as measurements obtained from keyboard interactions and movement, and behavioral interactions, such as application usage. However, practical implementations require further evaluation of circumvention. Thus, this work thoroughly analyzes various threats against mobile devices which use mobile device usage data as behavioral biometrics for authentication. Experimental results indicate that an outsider with a certain level of knowledge regarding the behavior of the device's owner poses a great security threat. Possible countermeasures to prevent such attacks are also provided.","PeriodicalId":372008,"journal":{"name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Joint Conference on Biometrics (IJCB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BTAS.2017.8272683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
While mobile devices are no longer a new technology, using the data generated from the use of these devices for security purposes has just recently been explored. Current methods, such as passwords, are quickly becoming antiquated, lacking the robustness, accuracy, and convenience desired to serve as reliable security measures. Since, researchers have resorted to alternative techniques, such as measurements obtained from keyboard interactions and movement, and behavioral interactions, such as application usage. However, practical implementations require further evaluation of circumvention. Thus, this work thoroughly analyzes various threats against mobile devices which use mobile device usage data as behavioral biometrics for authentication. Experimental results indicate that an outsider with a certain level of knowledge regarding the behavior of the device's owner poses a great security threat. Possible countermeasures to prevent such attacks are also provided.