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

Abstract

We demonstrate the BANDANA gait-based ad-hoc device pairing scheme. Our quantization approach extracts binary fingerprints from the deviation of acceleration sequences representing instantaneous gait vs. mean gait and establishes identical keys for fingerprints generated at distinct locations on the same body via a fuzzy commitment scheme. The separation between device-pairs on same-body and distinct body is possible as the fingerprint similarity exceeds 70% for same-body device pairs but on average reaches only 50% (random guess) for different body device pairs. The application of the BANDANA adhoc pairing will be demonstrated on a pair of Nexus 5X android phones and with a Huawei Watch 2.

Design and Simulation of Lightweight Identity Authentication Mechanism in Body Area Network

“…If more physiological data need to be obtained in some cases, such as an emergency, the access rights of personal information need to be realized based on device authentication. In reference [11], a device-to-device authentication scheme is proposed, that is, the authentication mechanism between two sensor nodes deployed on the human body. e key is always fresh and secure from the user's gait mode through the change of instantaneous acceleration.…”

“…e network model based on three roles is shown in Figure 10 (five sensor nodes). Use equation ( 4) to calculate the results of the cross-correlation algorithm of ECG signals at Ti − 2 and Ti; (7) Use equation ( 9) to calculate the cross-correlation coefficient; (8) ELSE the result of Ti executing the algorithm is normal; (9) Select the ECG signal at Ti − 1; (10) Use equation ( 4) to calculate the results of the cross-correlation algorithm of ECG signals at Ti − 2 and Ti or Ti − 1 and Ti; (11) Use equation ( 9 (1). //INPUT: request access to information.…”