  Fingerprint authentication has been extensively employed in contemporary
identity verification systems owing to its rapidity and cost-effectiveness. Due
to its widespread use, fingerprint leakage may cause sensitive information
theft, enormous economic and personnel losses, and even a potential compromise
of national security. As a fingerprint that can coincidentally match a specific
proportion of the overall fingerprint population, MasterPrint rings the alarm
bells for the security of fingerprint authentication. In this paper, we propose
a new side-channel attack on the minutiae-based Automatic Fingerprint
Identification System (AFIS), called PrintListener, which leverages users'
fingertip swiping actions on the screen to extract fingerprint pattern features
(the first-level features) and synthesizes a stronger targeted
PatternMasterPrint with potential second-level features. The attack scenario of
PrintListener is extensive and covert. It only needs to record users' fingertip
friction sound and can be launched by leveraging a large number of social media
platforms. Extensive experimental results in realworld scenarios show that
Printlistener can significantly improve the attack potency of MasterPrint.
