Security Properties of Gait for Mobile Device Pairing

TL;DR

This paper analyzes the security properties of gait-based features for mobile device pairing, discussing potential vulnerabilities, attack surfaces, and proposing modifications to improve security, while highlighting limitations against video-supported adversaries.

Contribution

It provides a comprehensive security analysis of gait-based pairing schemes, including attack surface classification, entropy analysis, and security flaw fixes.

Findings

Gait features can be correlated across body locations for secure pairing

Video recording capabilities pose significant security threats

Identified security flaws in existing gait-based schemes and proposed fixes

Abstract

Gait has been proposed as a feature for mobile device pairing across arbitrary positions on the human body. Results indicate that the correlation in gait-based features across different body locations is sufficient to establish secure device pairing. However, the population size of the studies is limited and powerful attackers with e.g. capability of video recording are not considered. We present a concise discussion of security properties of gait-based pairing schemes including a discussion of popular quantization schemes, classification and analysis of attack surfaces, discussion of statistical properties of generated sequences, an entropy analysis, as well as possible threats and security weaknesses of gait-based pairing systems. For one of the schemes considered, we present modifications to fix an identified security flaw. As a general limitation of gait-based authentication or pairing systems, we further demonstrate that an adversary with video support can create key sequences that are sufficiently close to on-body generated acceleration sequences to breach gait-based security mechanisms.