{"title":"二进制水印:一个实用的方法,以解决对消费者移动设备的人脸识别重放攻击","authors":"Daniel F. Smith, A. Wiliem, B. Lovell","doi":"10.1109/ISBA.2015.7126344","DOIUrl":null,"url":null,"abstract":"Mobile devices (laptops, tablets, and smart phones) are ideal for the wide deployment of biometric authentication, such as face recognition. However, their uncontrolled use and distributed management increases the risk of remote compromise of the device by intruders or malicious programs. Such compromises may result in the device being used to capture the user's face image and replay it to gain unauthorized access to their online accounts, possibly from a different device. Replay attacks can be highly automated and are cheap to launch worldwide, as opposed to spoofing attacks which are relatively expensive as they must be tailored to each individual victim. In this paper, we propose a technique to address replay attacks for a face recognition system by embedding a binary watermark into the captured video. Our monochrome watermark provides high contrast between the signal states, resulting in a robust signal that is practical in a wide variety of environmental conditions. It is also robust to different cameras and tolerates relative movements well. In this paper, the proposed technique is validated on different subjects using several cameras in a variety of lighting conditions. In addition, we explore the limitations of current devices and environments that can negatively impact on performance, and propose solutions to reduce the impact of these limitations.","PeriodicalId":398910,"journal":{"name":"IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015)","volume":"4 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Binary watermarks: a practical method to address face recognition replay attacks on consumer mobile devices\",\"authors\":\"Daniel F. Smith, A. Wiliem, B. Lovell\",\"doi\":\"10.1109/ISBA.2015.7126344\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile devices (laptops, tablets, and smart phones) are ideal for the wide deployment of biometric authentication, such as face recognition. However, their uncontrolled use and distributed management increases the risk of remote compromise of the device by intruders or malicious programs. Such compromises may result in the device being used to capture the user's face image and replay it to gain unauthorized access to their online accounts, possibly from a different device. Replay attacks can be highly automated and are cheap to launch worldwide, as opposed to spoofing attacks which are relatively expensive as they must be tailored to each individual victim. In this paper, we propose a technique to address replay attacks for a face recognition system by embedding a binary watermark into the captured video. Our monochrome watermark provides high contrast between the signal states, resulting in a robust signal that is practical in a wide variety of environmental conditions. It is also robust to different cameras and tolerates relative movements well. In this paper, the proposed technique is validated on different subjects using several cameras in a variety of lighting conditions. In addition, we explore the limitations of current devices and environments that can negatively impact on performance, and propose solutions to reduce the impact of these limitations.\",\"PeriodicalId\":398910,\"journal\":{\"name\":\"IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015)\",\"volume\":\"4 6\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBA.2015.7126344\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBA.2015.7126344","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Binary watermarks: a practical method to address face recognition replay attacks on consumer mobile devices
Mobile devices (laptops, tablets, and smart phones) are ideal for the wide deployment of biometric authentication, such as face recognition. However, their uncontrolled use and distributed management increases the risk of remote compromise of the device by intruders or malicious programs. Such compromises may result in the device being used to capture the user's face image and replay it to gain unauthorized access to their online accounts, possibly from a different device. Replay attacks can be highly automated and are cheap to launch worldwide, as opposed to spoofing attacks which are relatively expensive as they must be tailored to each individual victim. In this paper, we propose a technique to address replay attacks for a face recognition system by embedding a binary watermark into the captured video. Our monochrome watermark provides high contrast between the signal states, resulting in a robust signal that is practical in a wide variety of environmental conditions. It is also robust to different cameras and tolerates relative movements well. In this paper, the proposed technique is validated on different subjects using several cameras in a variety of lighting conditions. In addition, we explore the limitations of current devices and environments that can negatively impact on performance, and propose solutions to reduce the impact of these limitations.