I started learning about biometrics after the Equifax hack which exposed information of approximately 143 million accounts.

Equifax黑客入侵后，我开始学习生物识别技术，该技术暴露了大约1.43亿个帐户的信息。

It’s mind-boggling how easy it can be to steal identities.

令人难以置信的是，窃取身份信息有多么容易。

There are different software tools and processes available for individuals to protect themselves and exercise good cyber hygiene.

个人可以使用不同的软件工具和过程来保护自己并保持良好的网络卫生。

But our efforts may turn out to be a waste of time if companies holding our information don’t follow best practices for securing sensitive data.

但是，如果持有我们信息的公司不遵循保护敏感数据的最佳实践，那么我们的努力可能会浪费时间。

Perhaps we need to change the way we think about proving who we are, both digitally and face-to-face?

也许我们需要改变思考方式，以数字方式和面对面的方式证明自己是谁？

Biometric systems, widely used now, but controversial, show great promise, especially if businesses will be able to develop trust in these systems.

生物识别系统已被广泛使用，但存在争议，它显示出巨大的希望，特别是如果企业能够在这些系统上建立信任的话。

How can we make sure that companies will not use our biometric data without our permission? How can we guarantee that this data will not end up in the wrong hands?

我们如何确保未经我们许可，公司不会使用我们的生物识别数据？ 我们如何保证这些数据不会落入错误的人手中？

Hackers always find ways to compromise new systems, including biometrics.

黑客总是想办法破坏包括生物识别技术在内的新系统。

The hackers could, for example, create a trigger to corrupt images used to train the Artificial Intelligence (AI) system. The system would, therefore, learn incorrect labels and develop models that make the wrong predictions of what an image contains.

黑客可以例如创建触发器来破坏用于训练人工智能(AI)系统的图像。 因此，系统将学习错误的标签并开发对图像包含的内容做出错误预测的模型。

There are many sources of information on the web that may create confusion and fear.

网络上有许多信息源，可能会引起混乱和恐惧。

I believe that a public awareness campaign that explains the benefits and dangers of biometrics in simple language is needed.

我认为，需要开展以简单语言解释生物识别技术的好处和危险的公众意识运动。

什么是生物识别？ (What are biometrics?)

Biometrics or biometric systems measure and analyze people’s physical and behavioral features. These technologies are mainly used for identification and granting access, or for identifying and monitoring persons who are under surveillance.

生物识别或生物识别系统可以测量和分析人们的身体和行为特征。 这些技术主要用于识别和授予访问权限，或者用于识别和监视受监视的人员。

Biometric verification incorporates different ways of identifying a person using one or several biological traits. Unique identifiers may comprise of fingerprints, retina and iris patterns, voice, DNA, hand or earlobe geometry, as well as signatures.

生物特征识别 验证结合了使用一种或多种生物特征来识别一个人的不同方法。 唯一标识符可以包括指纹，视网膜和虹膜图案，声音，DNA，手或耳垂的几何形状以及签名。

谁发明了生物识别技术？ (Who invented biometrics?)

In the late 1800s, an explorer and anthropologist Francis Galton, obtained a large sample of fingerprints through his laboratories, collecting over 8,000 sets. He constructed a statistical proof of the uniqueness of individual prints. Galton’s study provided the foundation for a meaningful comparison of different fingerprints, which led to the first fingerprint classification system.

1800年代后期，一位探险家兼人类学家弗朗西斯·高尔顿(Francis Galton)通过他的实验室获得了大量指纹样本，收集了8000多套指纹。 他构建了单个印刷品唯一性的统计证明。 高尔顿的研究为不同指纹的有意义的比较提供了基础，这导致了第一个指纹分类系统。

According to Wikipedia, Josh Ellenbogen and Nitzan Lebovic made a case that biometrics origin comes from the systems developed by Alphonse Bertillon (1853–1914). He was a Parisian anthropologist and police desk clerk, who developed a method for identifying criminals, known as Bertillonage.

根据Wikipedia的说法，乔什·埃伦博根(Josh Ellenbogen)和尼桑·莱博维奇(Nitzan Lebovic)提出了生物识别技术起源于Alphonse Bertillon (1853–1914)开发的系统的案例。 他是一名巴黎人类学家和警察柜台服务员，他开发了一种识别罪犯的方法，称为Bertillonage。

The idea for using the iris for identification purposes originated in the 1930s. But the first iris recognition algorithm was not patented until 1994.

使用虹膜进行识别的想法起源于1930年代。 但是第一个虹膜识别算法直到1994年才获得专利。

In the 1960s, developers founded facial recognition methods that made it possible to analyze facial features within an image and extract tractable feature points.

在1960年代，开发人员建立了面部识别方法，从而可以分析图像中的面部特征并提取易于处理的特征点。

By 1969, fingerprint and facial recognition became widely used by law enforcement. The FBI then funded the development of automated processes. The creation of more sophisticated sensors for biometric capture and data extraction started.

到1969年，指纹和面部识别已被执法部门广泛使用。 然后，FBI资助了自动化流程的开发。 开始创建用于生物特征捕获和数据提取的更复杂的传感器。

In the 1980s, the National Institute of Standards and Technology (NIST) founded a Speech Group to study similar applicable methods for speech recognition technology. These studies are the foundation for the new voice command and recognition systems.

在1980年代，美国国家标准技术研究院(NIST)成立了语音小组，研究类似的语音识别技术适用方法。 这些研究是新的语音命令和识别系统的基础。

In 1991, the first crude facial detection technology, making real-time recognition of a person from an image or video possible, was developed. Nowadays, this technology uses biometric software with Artificial Intelligence (AI) enabled devices for facial feature mapping.

1991年，开发了第一种粗略的面部检测技术，该技术可以从图像或视频中实时识别人。 如今，该技术将生物识别软件与具有人工智能(AI)功能的设备结合使用来进行面部特征映射。

Hundreds of biometric identification algorithms were patented in the United States by the 2000s.

到2000年代，数百种生物特征识别算法在美国获得了专利。

Biometrics found use outside large enterprises and government institutions. Biometric systems were incorporated into commercial products and implemented at events.

生物识别技术在大型企业和政府机构之外使用。 生物识别系统已被纳入商业产品并在活动中实施。

However, even advanced facial recognition systems still often fail to map the faces of women and people of color correctly.

但是，即使是先进的面部识别系统，仍然经常无法正确绘制女性和有色人种的面Kong。

“Object recognition is a key component of future intelligent systems, and the Army must safeguard these systems from cyberattacks,” MaryAnne Fields, program manager for the Army Research Office’s (ARO’s) intelligent systems, said in a statement. “This work will lay the foundations for recognizing and mitigating backdoor attacks in which the data used to train the object recognition system is subtly altered to give incorrect answers.”

“物体识别是未来智能系统的关键组成部分，陆军必须保护这些系统免受网络攻击，”陆军研究办公室(ARO)智能系统项目经理MaryAnne Fields在一份声明中说。 “这项工作将为识别和减轻后门攻击奠定基础，在后者中，用于训练对象识别系统的数据被巧妙地更改以给出错误的答案。”

(Source: Techxlpore)

(来源： Techxlpore )

现在如何使用生物识别技术？ (How are biometrics used now?)

Biometric identification has become a standard feature on various platforms, including smartphones.

生物识别已经成为包括智能手机在内的各种平台的标准功能。

Examples from everyday life:

日常生活中的例子：

Newer iPhone and Samsung phone owners use Face ID to unlock their phones. Many consumers are getting used to biometric authentication, thanks to smartphones.

较新的iPhone和Samsung手机所有者使用Face ID解锁手机。 得益于智能手机，许多消费者已经习惯了生物特征认证。

Citibank and Bank of America allow logging into bank accounts using a fingerprint.

花旗银行和美国银行允许使用指纹登录银行帐户。

Facebook and Google have implemented sophisticated facial recognition technology.

Facebook和Google已经实施了复杂的面部识别技术。

Employers provide fitness tracking devices to monitor every step employees take.

雇主提供健身跟踪设备，以监控员工采取的每个步骤。

Beauty apps analyze customers’ skin to recommend products and services.

美容应用程序会分析客户的皮肤，以推荐产品和服务。

As part of their admission system, Disney theme parks collect fingerprints data from visitors who have tickets.

作为其门票系统的一部分，迪斯尼主题公园从持有门票的游客那里收集指纹数据。

The Transportation Security Administration (TSA) is using and testing fingerprint scanners at various U.S. airports. Global Entry kiosks take photos of travelers.

美国运输安全管理局(TSA)正在美国的各个机场使用和测试指纹扫描仪。 全球入境服务亭为旅行者拍照。

In 2018, Delta Airlines launched optional facial recognition in Atlanta after two years of testing. The carrier now offers biometric boarding also in Minneapolis, Salt Lake City, New York, Detroit, and Los Angeles. They have stated that 72% of travelers in Atlanta preferred biometric boarding as it is faster than traditional boarding. Delta does not save or store any images or biometric data.

经过两年的测试， 达美航空于2018年在亚特兰大推出了可选的面部识别系统。 该航空公司现在还在明尼阿波利斯，盐湖城，纽约，底特律和洛杉矶提供生物识别登机服务。 他们说，亚特兰大有72％的旅行者喜欢生物识别登机，因为它比传统登机快。 达美航空不保存或存储任何图像或生物特征数据。

High-end hotels and retailers are using facial recognition for loyalty programs and to identify VIPs for preferred service.

高端酒店和零售商正在使用面部识别来进行忠诚度计划，并识别VIP以获得优先服务。

In retail outfits, faces of persons caught on camera are turned into a biometric template and compared with a database for a possible match with known criminals.

在零售店中，被照相机捕获的人的面部被转换成生物特征模板，并与数据库进行比较，以与已知罪犯进行匹配。

Retailers use the same platform that helps identify shoplifters to find out which displays are working better, where the customer traffic is, to improve sales.

零售商使用相同的平台来帮助识别入店行窃者，以找出哪些显示效果更好，客户流量在哪里，以提高销售。

Technology has evolved much faster than legislation. Improper use of facial recognition technology is on the rise and is concerning.

技术的发展远快于立法。 面部识别技术的不当使用正在上升并且令人担忧。

The most recent example of possible improper use involves a New York start-up, Clearview AI. It matches photographs submitted by subscribers against more than 3 billion photos, scraped from various public websites.

可能不当使用的最新示例涉及纽约的一家初创公司Clearview AI 。 它将订户提交的照片与从各个公共网站抓取的超过30亿张照片进行匹配。

Although Clearview AI’s database has supposedly helped law enforcement officials identify and find criminals, there is currently no way for people whose photos are included in the database without their knowledge, to remove their images from this collection.

尽管Clearview AI的数据库据称已帮助执法人员识别和发现罪犯，但目前尚无法将不知道其照片包含在数据库中的人从该收藏集中删除其图像。

The Commercial Facial Recognition Privacy Act of 2019, introduced to US Congress in March 2019, strives to prohibit entities from using facial recognition technology to identify or track an end user without obtaining consent, and for other purposes.

2019年《商业面部识别隐私法》(2019年《商业面部识别隐私法》)于2019年 3月提交美国国会，旨在禁止实体在未经同意的情况下以及其他目的使用面部识别技术来识别或跟踪最终用户。

Hopefully, new laws will protect consumers. I also hope that the government will not develop a system of surveillance following China’s example.

希望新法律能够保护消费者。 我也希望政府不要仿照中国的榜样建立监视系统。

There is a difference between monitoring individuals as an effort to protect them versus stalking people.

监视个人与保护缠扰者之间的区别在于努力保护他们。

企业可以做些什么来保持客户的信任？ (What can businesses do to keep customers’ trust?)

New biometric technologies, if implemented carefully, bring new opportunities for improved and safer customer experiences.

如果精心实施新的生物识别技术，将为改善和更安全的客户体验带来新的机遇。

David Britton, who is currently VP of Industry Solutions of Global Fraud and Identity at Experian, believes that legitimate consumers trying to gain access to an account need a seamless, frictionless consumer experience. The company’s system should recognize them and block fraudsters out.

益百利全球欺诈与身份行业解决方案副总裁，现任大卫·布里顿(David Britton)认为，试图获得帐户访问权限的合法消费者需要无缝，无摩擦的消费者体验。 公司的系统应识别它们并阻止欺诈者。

(Source: Biometric Update)

(来源： 生物识别更新 )

In their recent study, Experian found that 74 percent of businesses are confident that if they can recognize the consumer by identifying them upfront, they can prevent fraud. By understanding how the consumer behaves and interacts with the company’s services, businesses believe they can differentiate a legitimate user from a fraudster.

益百利在最近的研究中发现，有74％的企业有信心，如果他们能通过提前识别消费者来识别消费者，那么他们可以防止欺诈。 通过了解消费者的行为方式以及与公司服务的交互，企业相信他们可以区分合法用户和欺诈者。

In summary, businesses and organizations must protect customer data. Transparency is critical; customers need to know how companies use their information, including biometric data.

总之，企业和组织必须保护客户数据。 透明度至关重要。 客户需要了解公司如何使用其信息，包括生物识别数据。

As a consumer, I give my trust and loyalty to companies that serve me well, are transparent, and protect my information.

作为消费者，我对那些为我服务良好，透明并保护我的信息的公司表示信任和忠诚。