Gesture-based continuous authentication for wearable devices

The smart glasses use case

Jagmohan Chauhan*, Hassan Jameel Asghar, Anirban Mahanti, Mohamed Ali Kaafar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

13 Citations (Scopus)


We study the feasibility of touch gesture behavioural biometrics for implicit authentication of users on smart glasses by proposing a continuous authentication system on Google Glass using two classifiers: SVM with RBF kernel, and a new classifier based on Chebyshev’s concentration inequality. Based on data collected from 30 users, we show that such authentication is feasible both in terms of classification accuracy and computational load on Glass. We achieve a classification accuracy of up to 99% with only 75 training samples using behavioural biometric data from four different types of touch gestures. To show that our system can be generalized, we test its performance on touch data from smartphones and found the accuracy to be similar to Glass. Finally, our experiments on the permanence of gestures show that the negative impact of changing user behaviour with time on classification accuracy can be best alleviated by periodically replacing older training samples with new randomly chosen samples.

Original languageEnglish
Title of host publication14th International Conference on Applied Cryptography and Network Security (ACNS) 2016 : proceedings
Subtitle of host publicationApplied Cryptography and Network Security
EditorsMark Manulis, Steve Schneider, Ahmad-Reza Sadeghi
PublisherSpringer, Springer Nature
Number of pages18
ISBN (Electronic)9783319395555
ISBN (Print)9783319395548
Publication statusPublished - 2016
Externally publishedYes
Event14th International Conference on Applied Cryptography and Network Security, ACNS 2016 - Guildford, United Kingdom
Duration: 19 Jun 201622 Jun 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Conference on Applied Cryptography and Network Security, ACNS 2016
CountryUnited Kingdom

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