New York: As hackers find ways to unlock your phone with your face while you sleep or using a photo from social media to do the same, researchers have developed a way to strengthen security by adding facial features such as smiles and winks to the mix. 作为黑客找到方法来解锁你的电话与你的脸当你睡眠或利用社会媒体来做同样的照片,研究人员开发了一种方法来加强安全通过添加面部特征与微笑和眨眼等。 纽约:黑客找到方法来解锁你的电话与你的脸当你睡眠或利用社会媒体来做同样的照片,研究人员开发了一种方法来加强安全通过添加面部特征与微笑和眨眼等。
D.J. Lee, Professor at Brigham Young University (BYU) in the US, who has filed a patent on the tech already, said the idea is not to compete with Apple or have the application be all about smartphone access<\/a>.
In his opinion, the new technology has broader application, including accessing restricted areas at a workplace, online banking, ATM use, safe deposit box access or even hotel room entry or keyless entry\/access to your vehicle, BYU said in a statement.
The new system is called Concurrent Two-Factor Identity Verification (C2FIV) and it requires both one's facial identity and a specific facial motion<\/a> to gain access.
To set it up, a user faces a camera and records a short 1-2 second video of either a unique facial motion or a lip movement from reading a secret phrase.
The video is then input into the device, which extracts facial features and the features of the facial motion, storing them for later ID verification.
To get technical, C2FIV relies on an integrated neural network framework<\/a> to learn facial features and actions concurrently.
This framework models dynamic, sequential data like facial motions, where all the frames in a recording have to be considered -- unlike a static photo with a figure that can be outlined.
Using this integrated neural network framework, the user's facial features and movements are embedded and stored on a server or in an embedded device and when they later attempt to gain access, the computer compares the newly-generated embedding to the stored one.
That user's ID is verified if the new and stored embeddings match at a certain threshold.
\"We're pretty excited with the technology because it's pretty unique to add another level of protection that doesn't cause more trouble for the user,\" Lee said.
In their preliminary study, Lee and his PhD student Zheng Sun recorded 8,000 video clips from 50 participants making facial movements such as blinking, dropping their jaw, smiling or raising their eyebrows as well as many random facial motions to train the neural network.
They then created a dataset of positive and negative pairs of facial motions and inputted higher scores for the positive pairs (those that matched).
Currently, with the small dataset, the trained neural network verifies identities with over 90 per cent accuracy.
They are confident the accuracy can be much higher with a larger dataset and improvements on the network.
<\/p><\/body>","next_sibling":[{"msid":81633455,"title":"Mindtree to see cloud-based growth over next 3-4 years: Analysts","entity_type":"ARTICLE","link":"\/news\/mindtree-to-see-cloud-based-growth-over-next-3-4-years-analysts\/81633455","category_name":null,"category_name_seo":"telecomnews"}],"related_content":[],"msid":81633734,"entity_type":"ARTICLE","title":"Smiles, winks in face recognition could increase phone security","synopsis":"As hackers find ways to unlock your phone with your face while you sleep or using a photo from social media to do the same, researchers have developed a way to strengthen security by adding facial features such as smiles and winks to the mix.","titleseo":"telecomnews\/smiles-winks-in-face-recognition-could-increase-phone-security","status":"ACTIVE","authors":[],"Alttitle":{"minfo":""},"artag":"IANS","artdate":"2021-03-22 18:00:16","lastupd":"2021-03-22 18:01:57","breadcrumbTags":["risk management","security hackers","Devices","smartphone security","smartphone access","neural network framework","specific facial motion"],"secinfo":{"seolocation":"telecomnews\/smiles-winks-in-face-recognition-could-increase-phone-security"}}" data-authors="[" "]" data-category-name="" data-category_id="" data-date="2021-03-22" data-index="article_1">
微笑、眨眼在人脸识别可以增加手机安全
D.J.李教授杨百翰大学(杨百翰大学)在美国,已经提起了专利技术,谁说这个想法是不能和苹果竞争或应用程序智能手机访问。
在他看来,这项新技术有广泛的应用,包括在工作场所访问限制区域,网上银行,使用自动取款机,保险箱访问甚至酒店房间入口或无钥匙进入/访问您的车辆,杨百翰大学在一份声明中说。
设置它,用户面临着一个相机,记录短1 - 2秒的视频一个独特的面部运动或嘴唇运动从一个秘密的短语。
然后输入设备,视频中提取面部特征和面部运动的特性,储存后ID验证。
技术,C2FIV依赖于一个集成神经网络框架同时学习面部特征和行为。
这个框架模型动态序列数据像面部动作,所有帧记录必须被认为是——与静态照片图可以概述。
使用这个集成神经网络框架,用户的面部特征和运动嵌入和存储在一个服务器或在嵌入式设备,当他们后来试图获取,存储的计算机比较新生成的嵌入到一个。
该用户的ID验证如果新和存储在某个阈值映射进行匹配。
“我们非常兴奋的技术,因为它很独特添加另一个级别的保护,为用户不会引起更多的麻烦,”李说。
在他们的初步研究,李和他的博士生郑太阳记录8000视频剪辑来自50个参与者使面部动作如闪烁,放弃他们的下巴,微笑或提高眉毛以及许多随机面部运动训练神经网络。
然后创建了一个数据集的积极的和消极的对面部动作和输入更高的分数正对(那些匹配)。
目前,小数据集,训练神经网络身份验证,准确率超过90%。
他们有信心可以更高的精度和更大的数据集和改进网络。
New York: As hackers find ways to unlock your phone with your face while you sleep or using a photo from social media to do the same, researchers have developed a way to strengthen security by adding facial features such as smiles and winks to the mix.
D.J. Lee, Professor at Brigham Young University (BYU) in the US, who has filed a patent on the tech already, said the idea is not to compete with Apple or have the application be all about smartphone access<\/a>.
In his opinion, the new technology has broader application, including accessing restricted areas at a workplace, online banking, ATM use, safe deposit box access or even hotel room entry or keyless entry\/access to your vehicle, BYU said in a statement.
The new system is called Concurrent Two-Factor Identity Verification (C2FIV) and it requires both one's facial identity and a specific facial motion<\/a> to gain access.
To set it up, a user faces a camera and records a short 1-2 second video of either a unique facial motion or a lip movement from reading a secret phrase.
The video is then input into the device, which extracts facial features and the features of the facial motion, storing them for later ID verification.
To get technical, C2FIV relies on an integrated neural network framework<\/a> to learn facial features and actions concurrently.
This framework models dynamic, sequential data like facial motions, where all the frames in a recording have to be considered -- unlike a static photo with a figure that can be outlined.
Using this integrated neural network framework, the user's facial features and movements are embedded and stored on a server or in an embedded device and when they later attempt to gain access, the computer compares the newly-generated embedding to the stored one.
That user's ID is verified if the new and stored embeddings match at a certain threshold.
\"We're pretty excited with the technology because it's pretty unique to add another level of protection that doesn't cause more trouble for the user,\" Lee said.
In their preliminary study, Lee and his PhD student Zheng Sun recorded 8,000 video clips from 50 participants making facial movements such as blinking, dropping their jaw, smiling or raising their eyebrows as well as many random facial motions to train the neural network.
They then created a dataset of positive and negative pairs of facial motions and inputted higher scores for the positive pairs (those that matched).
Currently, with the small dataset, the trained neural network verifies identities with over 90 per cent accuracy.
They are confident the accuracy can be much higher with a larger dataset and improvements on the network.
<\/p><\/body>","next_sibling":[{"msid":81633455,"title":"Mindtree to see cloud-based growth over next 3-4 years: Analysts","entity_type":"ARTICLE","link":"\/news\/mindtree-to-see-cloud-based-growth-over-next-3-4-years-analysts\/81633455","category_name":null,"category_name_seo":"telecomnews"}],"related_content":[],"msid":81633734,"entity_type":"ARTICLE","title":"Smiles, winks in face recognition could increase phone security","synopsis":"As hackers find ways to unlock your phone with your face while you sleep or using a photo from social media to do the same, researchers have developed a way to strengthen security by adding facial features such as smiles and winks to the mix.","titleseo":"telecomnews\/smiles-winks-in-face-recognition-could-increase-phone-security","status":"ACTIVE","authors":[],"Alttitle":{"minfo":""},"artag":"IANS","artdate":"2021-03-22 18:00:16","lastupd":"2021-03-22 18:01:57","breadcrumbTags":["risk management","security hackers","Devices","smartphone security","smartphone access","neural network framework","specific facial motion"],"secinfo":{"seolocation":"telecomnews\/smiles-winks-in-face-recognition-could-increase-phone-security"}}" data-news_link="//www.iser-br.com/news/smiles-winks-in-face-recognition-could-increase-phone-security/81633734">
评论
现在评论 阅读评论(1)所有评论
找到这个评论进攻?
下面选择你的理由并单击submit按钮。这将提醒我们的版主采取行动