A Nonlinearity-Based Secure Face-to-Face Device Authentication for Mobile Devices

With the proliferation of mobile devices, face-to-face device-to-device (D2D) communication has been applied to a variety of daily scenarios such as mobile payment and short distance file transfer. In D2D communications, a critical security problem is to verify the device legitimacy when they share no secrets in advance. Previous research proposed device authentication schemes based on pre-built database or exploiting physical properties. However, a remaining challenge is to secure face-to-face D2D communication even in the middle of a crowd, within which an attacker may hide. In this paper, we present
NAuth
, a nonlinearity-enhanced, location-sensitive authentication mechanism. Especially, we target at the secure authentication within a limited range such as 20 cm, which is typical for face-to-face scenarios.
NAuth
designs a
verification scheme
based on the nonlinear distortion of speaker-microphone systems and a location-based
validation model
. The verification scheme guarantees device authentication consistency by extracting acoustic nonlinearity patterns (ANP) while the validation model ensures device legitimacy by measuring the time difference of arrival (TDOA) at two microphones. We analyze the feasibility and security of
NAuth
theoretically and evaluate its performance experimentally. Results demonstrate that
NAuth
can verify the device legitimacy in the presence of nearby attackers.