Synaptics Solves Fingerprint Authentication Security

Synaptics's Match-in-Sensor™ technology keeps fingerprint data within hardware, protecting image data from security threats.

With last year's launch of the iPhone 6 came the simultaneous reveal of Apple Pay, touted as the most secure way to pay for purchases with a debit or credit card. Apple Pay relies on the use of fingerprint recognition--embedded into the home button of iPhones--to send a one-time use code to pay terminals using NFC. The concept works well exterior to the device: even if thieves attempted to gather data transmitted to the terminal, the only information they would be able to steal would be a transaction-specific dynamic security code, which is virtually useless.
However, fingerprint information is still stored within the software of the phone, making it conceivably prone to security threats (no reports of this yet, but the passcode was susceptible until a recent iOS update). This is why Synaptics's new technology is intriguing: the Match-In-Sensor keeps fingerprint image enrollment, pattern storage, and biometric matching within the hardware of the fingerprint sensor. All security sensitive functions are inside the System on Chip, totally isolated from the operating system. That means even if someone figures out how to hack your device, it would be futile without physical accessibility to the fingerprint sensor hardware.

"Match-in-Sensor technology provides for the requirements of smartphone manufacturers, the convenience for end-users, and the security for online service providers when authenticating their customers" --Ritu Favre, senior VP, Biometric Products Division (BPD), Synaptics

With the proliferation of password fatigue, fingerprint sensor technology is definitely at the forefront of technology. We'll be seeing (and indeed already are seeing) fingerprint authentication utilized for everything from banking apps to mobile gaming. Once the world moves entirely from passcodes to physical authentication, security will be a primary concern. Synaptics's Match-in-Sensor could be a viable solution.