@conference { , title = {Secure Pick Up: Implicit Authentication When You Start Using the Smartphone}, year = {2017}, month = {06/21/2017}, address = {Indianapolis}, abstract = {We propose Secure Pick Up (SPU), a convenient, lightweight, in-device, non-intrusive and automatic-learning system for smartphone user authentication. Operating in the background, our system implicitly observes users? phone pick-up movements, the way they bend their arms when they pick up a smartphone to interact with the device, to authenticate the users. Our SPU outperforms the state-of-the-art implicit authentication mechanisms in three main aspects: 1) SPU automatically learns the user?s behavioral pattern without requiring a large amount of training data (especially those of other users) as previous methods did, making it more deployable. Towards this end, we propose a weighted multi-dimensional Dynamic Time Warping (DTW) algorithm to effectively quantify similarities between users? pick-up movements; 2) SPU does not rely on a remote server for providing further computational power, making SPU efficient and usable even without network access; and 3) our system can adaptively update a user?s authentication model to accommodate user?s behavioral drift over time with negligible overhead. Through extensive experiments on real world datasets, we demonstrate that SPU can achieve authentication accuracy up to 96.3% with a very low latency of 2.4 milliseconds. It reduces the number of times a user has to do explicit authentication by 32.9%, while effectively defending against various attacks. }, keywords = {Authentication, Security, Privacy, Machine Learning, Smartphone, Dynamic Time Warping, Mobile System}, author = {Wei-Han Lee and Xiaochen Liu and Yilin Shen and Hongxia Jin and Ruby Lee} }