BANDANA -- Body Area Network Device-to-device Authentication using Natural gAit

TL;DR

BANDANA is a novel implicit authentication scheme that uses gait-based acceleration patterns to securely and spontaneously authenticate wearable devices on the same body, robust against noise and attacks.

Contribution

It introduces the first gait-based device-to-device authentication method for body-worn devices, leveraging natural gait variations for secure spontaneous pairing.

Findings

Robustness demonstrated on two gait datasets

Effective discrimination between intra- and inter-body cases

Resilience against noise and active attacks

Abstract

Secure spontaneous authentication between devices worn at arbitrary location on the same body is a challenging, yet unsolved problem. We propose BANDANA, the first-ever implicit secure device-to-device authentication scheme for devices worn on the same body. Our approach leverages instantaneous variation in acceleration patterns from gait sequences to extract always-fresh secure secrets. It enables secure spontaneous pairing of devices worn on the same body or interacted with. The method is robust against noise in sensor readings and active attackers. We demonstrate the robustness of BANDANA on two gait datasets and discuss the discriminability of intra- and inter-body cases, robustness to statistical bias, as well as possible attack scenarios.