%0 Conference Proceedings
%T Improving Resilience of Behaviometric Based Continuous Authentication with Multiple Accelerometers
%+ Distributed Systems and Computer Networks (DistriNet)
%+ IMEC (IMEC)
%A Hamme, Tim, Van
%A Preuveneers, Davy
%A Joosen, Wouter
%Z Part 5: Secure Systems
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 31th IFIP Annual Conference on Data and Applications Security and Privacy (DBSEC)
%C Philadelphia, PA, United States
%Y Giovanni Livraga
%Y Sencun Zhu
%I Springer International Publishing
%3 Data and Applications Security and Privacy XXXI
%V LNCS-10359
%P 473-485
%8 2017-07-19
%D 2017
%R 10.1007/978-3-319-61176-1_26
%Z Computer Science [cs]Conference papers
%X Behaviometrics in multi-factor authentication schemes continuously assess behavior patterns of a subject to recognize and verify his identity. In this work we challenge the practical feasibility and the resilience of accelerometer-based gait analysis as a behaviometric under sensor displacement conditions. To improve misauthentication resistance, we present and evaluate a solution using multiple accelerometers on 7 positions on the body during different activities and compare the effectiveness with Gradient-Boosted Trees classification. From a security point of view, we investigate the feasibility of zero and non-zero effort attacks on gait analysis as a behaviometric. Our experimental results with data from 12 individuals show an improvement in terms of EER with about 2% (from 5% down to 3%), with an increased resilience against observation attacks. When trained to defend against such attacks, we observe no decrease in classification performance.
%G English
%Z TC 11
%Z WG 11.3
%2 https://inria.hal.science/hal-01684348/document
%2 https://inria.hal.science/hal-01684348/file/453481_1_En_26_Chapter.pdf
%L hal-01684348
%U https://inria.hal.science/hal-01684348
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC11
%~ IFIP-WG11-3
%~ IFIP-DBSEC
%~ IFIP-LNCS-10359