Biometric authentication vs AI threats: Is mobile security ready?

Quality biometric solutions provide outstanding security with a seamless UX. This makes it appealing for use cases ranging from state-of-the-art access control for critical government infrastructure, to something as routine as unlocking your phone. However, this diversity of use cases brings its own challenges. The varying needs of different applications, coupled with the speed with which the technology has developed, has created a fragmented ecosystem with little standardisation.

Many emerging use cases rely on the biometric capabilities of consumer’s own commercially available off the shelf (COTS) device. Android platform recognized this and has laid the groundwork to enfranchise device manufacturers and biometric solution vendors to create the next generation of state-of-the-art authentication products. And it does so just in time. Artificial Intelligence has transformed the biometric security battleground, and it is vital that stakeholders understand both the threats they face, and the steps that must be taken to meet them head on.

The changing threat landscape.

Biometric authentication is based around using an individual’s unique identifiers such as their iris, fingerprint, or face to provide an additional data point to verify identity. When launched, it was praised for the infallibility and security it provided as biometric data was, quite literally, always ‘on hand’ for users, but it couldn’t be lost or stolen.

Except now it can. Easily.

Artificial Intelligence, or AI, has unlocked a host of efficiencies in our life, specifically in data management and customer experience. However, these same AI tools are also readily available to fraudsters who can use them to execute devastating attacks. For example, photos can be taken from a user’s social media and in a matter of moments be transformed into a deepfake video to be used in an injection attack that aims to spoof facial recognition technologies and gain access to private data.

Meanwhile, AI is also being used to work through extensive data caches to locate and exploit any vulnerability in a security system. This has caused a rapid expansion in both the scale and sophistication of cyberattacks. 

Stakeholders throughout the authentication ecosystem are working to adopt more robust practices. Biometrics has a key role to play in this, but only if it can be secured and trusted. The uniqueness of each individual’s biometrics, its greatest strength as an authenticator, can also be its most fundamental risk. If the data is compromised, a user cannot simply rewrite their fingerprints in the same way they change their password. It is therefore crucial the data is protected and secure. Similarly, if a biometric solution can be easily spoofed fraudsters can gain access to the user’s device, accounts and personal information. 

An updated approach.

To meet the challenges posed by this evolving threat landscape, Android defined its three classes of biometric strength for devices operating under its remit. Its Compatibility Definition Documents (CDD), the requirements that each Android device must comply with should it wish to participate in the Android ecosystem, outlines the requirements for biometric security as Class 3 (formerly known as Strong), Class 2 (formerly Weak), and Class 1 (formerly Convenience).

Devices require independent third-party testing to evaluate their Spoof Acceptance Rate (SAR) along with verification of False Acceptance Rate (FAR) and False Rejection Rate (FRR) as a part of their Biometrics Compliance Report (BCR). 

Android’s biometric requirement and the ISO/IEC 30107 standard also defines Presentation Attack Detection (PAD) testing to evaluate the liveness detection capability of the biometric solutions. This is a crucial step towards detecting and resisting spoofing attacks such as deepfakes and protecting the end users.

Independent testing and compliance will raise the baseline for the minimum performance and security of biometric solutions. It requires all biometric solution providers and Android device OEMs to carefully develop their offer to ensure it meets the minimum thresholds backed by impartial evidence. This means that authentication should work right first time for the verified user, while also prevent spoofing and hacks. Not only will this help mitigate the rising threat of spoofing and fraud, it also elevates the user experience, thereby increasing trust in the biometrics ecosystem and proliferating its growth into additional use cases.

Adding value with testing and 3rd party validation.

The process of 3rd party evaluation with industrial standards acts as a layer of trust between all players operating in ecosystem. It should not be thought of as a tick-box exercise, but rather a continuous process to ensure compliance with the latest standards and regulatory requirements. In doing so, device manufacturers and biometric solution providers can collectively raise the bar for biometric security.

The robust testing and compliance protocols ensure that all devices and components meet standardized requirements. This is made possible by trusted and recognized labs, like Fime, who can provide OEMs and solution providers with tools and expertise to continually optimize their products.

But testing doesn’t just safeguard the ecosystem; it elevates it. As an example, new innovative techniques like test the biases of demographic groups (blog) or environmental conditions. Using these techniques allow testers to discover any differential performances by using or simulating different demographic groups or environmental conditions. Biases detection can prevent security issue on real life deployment. This allows also solution providers to optimize the quality and inclusivity of their solutions to meet the needs of more markets and differentiate from the competition.

Building for the future.

We have reached a critical moment for the future of biometric authentication. The success of the technology is predicated on the continued growth in its adoption, but with AI giving fraudsters the tools they need to transform the threat landscape at a faster pace than ever before, it is essential that biometric solution providers stay one step ahead to retain and grow user trust. Stakeholders must therefore focus on one key question:

Can the user trust that they are not sacrificing security for convenience when using biometric authentication?

Product managers must make sure that the performance of their biometric offer balances these two seemingly contradictory demands, but if successful, there are a whole host of emerging use cases that could unlock new revenue streams for them. These include biometrics backed in store checkout, enhanced access control, augmented automotive experiences, and more.

Another significant trend on the horizon is the increasing use of biometrics in identity verification for eID and eKYC use cases. Digital identity is offering a faster, more secure way to verify identity in the online world. Biometrics can provide a simple, seamless to augment the enrollment and verification process for this, but much like in the payments ecosystem, its success depends on the implementation of state of the art solutions throughout the user journey.

Compliance and quality validation are no longer optional. They are essential to protecting end users, preserving brand integrity, enabling innovation, and safeguarding the future of biometric technology.

Identity in the Metaverse

An aurora accents Earth's atmospheric glow underneath a starry sky

I had the privilege to chair a discussion about identity in the metaverse at the Identiverse conference in Denver in June 2022, and had great fun discussing the new landscape for identity with Heather Vescent, Jonathan Howle, Katryna Dow and Gopal Padinjaruveetil. In order to frame my thoughts and get the discussion about identity and privacy going, I needed a mental model.

What Exactly Is A Smart Wallet?

pexels-photo-887751.jpeg

A wallet is a way of organising things. My Apple Wallet, just like my real wallet, doesn’t have any cash in it. It has credit cards, debit cards, loyalty cards, vaccination records, boarding passes, train tickets and driving licences (Apple have just gone live with their driving licence and state in Arizona). These things are all held independently in the wallet: they don’t talk to each other and they don’t share data with each other. They are also, as you will have noticed, mostly about identity, not money.

Biometrics on Cards

Improving Cardholder Authentication

On-card fingerprint readers have been in development for a few years now, with a number of products now in market from vendors such as Fingerprint Cards, Zwipe, Idemia and G+D.

PIN: we need to talk about our relationship

person holding black and gray digital device

16 years on from PIN day (Valentines Day 2006) how is our relationship with PIN holding up?

Last year Dave Birch postulated that PIN was in decline and indeed no longer necessary as our mobile phones make use of various biometrics to authenticate us and our transactions, but as we often remind ourselves in Chyp, we’re not normal.  UK Finance statistics tells us that whilst the use of Apple Pay & Google Pay at the Point of Sale is on the rise, the humble plastic card is still the preferred way to pay.

Be on the smart side of the Great Reset

planet earth

The human society is now at crossroads – demanding changes in our lifestyle, health choices, economics, and civil liberties. These changes are accelerated by climate change, political response to the pandemic, the need for racial and gender equality, human migration, and of course, a few break-through technologies such as digital automation, data analytics, and machine-learning (AI). So where are we heading? The call for “Great Reset” has been reverberating since the past few years and is now getting louder and louder. This was the topic of the virtual fireside chat by two visionaries on our Tomorrow’s Transactions webinar, Brett King and Dave Birch, discussing the societal and technological changes that are foreseen in the next few decades. This conversation was centered around Brett King’s (Richard Petty, co-author) book, “The Rise of Technosocialism and aligns with Consult Hyperion’s engagement with think tanks on global issues.  Our aim to is separate foresight and facts from fiction in trying to understand the trends in the market that our clients should watch-out for especially in payments, banking, transit, digital identity, and information security.

Payments are hard. That’s why the world’s leading payment organisations come to us.

Contact-free public transport (Part 3)

person holding smartphone

This is the third of three blogs about technologies to support contact-free use of public transport.

The radio again – I hear that the Transport Minister for England had just reported that there have been fewer than 400 fines for people failed to wear face covering on public transport. More than 115,000 travellers have been stopped and reminded that face coverings are mandatory, and 9,500 people prevented from travelling.

The tension in facial recognition

Facial recognition camera

The rise of facial recognition technology and the erosion of privacy

In the 2002 movie Minority Report, Tom Cruise’s character has his eyes surgically replaced so he can avoid being identified by the all-pervasive retina scanning system that the state uses to track people… and of course, uses to show targeted ads to people. This is a rather dystopian view of the broad application of biometrics technology.  However, judging by a lawsuit targeting Macy’s for their use of Clearview AI’s facial recognition technology in their stores, it seems that staying anonymous in the bricks and mortar world is becoming a little more like the movie. Whilst you may not require surgery, you may soon require something akin to glasses and a fake beard to avoid being tracked. The issue here is that Clearview AI has been scraping images from publicly viewable sources on the web for a while, enabling them to create a database of facial biometrics against which to match captured facial images. Amongst the sources of this data are Facebook, Twitter, LinkedIn, YouTube and Vimeo, with some of these companies having sent cease and desist letters to Clearview AI for breach of their terms of service.  The aim it seems is for Clearview AI to create a one-to-many facial recognition solution that can identify an individual from only an image of their face from anyone who is in a photo or video on the web.  Based on a report on Buzzfeed, they were working with over 2000 companies as of February 2020, and they are probably not alone, so perhaps we should be concerned.

Subscribe to our newsletter

You have successfully subscribed to the newsletter

There was an error while trying to send your request. Please try again.

By accepting the Terms, you consent to Consult Hyperion communicating with you regarding our events, reports and services through our regular newsletter. You can unsubscribe anytime through our newsletters or by emailing us.