Once thought of as a lofty concept only seen in spy series like James Bond, biometrics, the measurement and analysis of unique physical characteristics for security purposes, has been gaining traction in the field of technology (particularly in mobile devices).
Biometric technology has been seeping its way into the digital technology world for years, gradually trickling down and reaching consumers. Technologies such as retinal scanning, often initially used by security firms as authentication methods for gaining access to data, have made their way into the hands of consumers through devices such as the recently-released Microsoft Lumia 950 and Lumia 905 XL.
Apple’s Touch ID technology (a capacitance fingerprint sensor embedded within the home button of Apple products such as iPhone and iPad devices manufactured during or after 2013) allows users to use fingerprint authentication to unlock their device, make purchases in the iTunes and App Store, and forgo using their password to login to specific apps such as mobile banking. Touch ID is also being suggested for use in multi-method authentication for identity verification when making major changes to software on the device, such as updating, downgrading or factory resetting the operating system.
Touch ID has received criticism about the easy ability for fingerprints to be spoofed or falsified by hackers trying to gain access to a device, though security and verification has improved over the years since capacitive fingerprint identification methods have been introduced.
Another form of biometric recognition and authentication technology, voice recognition, has been used for years in everything from automotive manufacturing and development (e.g. in-car systems such as OnStar) to mobile devices (such as Apple’s Siri or Microsoft’s Cortana) to hands-free computing (as used heavily in accessibility devices in the healthcare field).
Google recently opened up their speech recognition API technology to third-party developers, directly entering into competition with Nuance and other voice recognition technology companies. Google Cloud Speech API recognizes over 80 languages in real-time or batch mode, allowing software developers to implement speech-to-text uses in their programs, and additionally use real-time translation, allowing for wider ranges of communication between users. This API release will undoubtedly affect Nuance, often thought of as the spearhead company in the voice recognition technology market, and the power behind popular software such as Apple’s digital assistant, Siri.
Facial recognition technology has also recently been emerging in marketing technology, specifically in the use of the popularized “selfie”. Large-scale companies such as Amazon and Alibaba are beginning to open the gates to technology that will allow customers to make payment for items or verify identity for account information using something as simple as a real-time photo of the user’s face.
Mastercard, in collaboration with Bank of Montreal, has recently introduced methods of facial recognition technology to authenticate users for use in mobile banking. Informally known as “selfie pay”, BMO corporate users have been approved for use with this technology, and it will soon be opened up to the general banking public for widespread use.
This recognition goes hand-in-hand with the already widespread MasterPass authentication, which utilizes fingerprint recognition among other security methods. One of the challenges to this type of biometric authentication is technology’s ability to detect liveness- the difference between the ability to authenticate for security purposes with a real-time face or with a photograph. Early prototypes for scanners using facial recognition technology failed introductory testing, susceptible to users holding up a photograph, with improvements being made in more modern pieces (using more layers of authentication methods) of this type of machinery.