Continuous User Authentication via Unlabeled Phone Movement Patterns

Autor:	Kumar, Rajesh, Kundu, Partha Pratim, Shukla, Diksha, Phoha, Vir V.
Rok vydání:	2017
Předmět:	Computer Science - Human-Computer Interaction Computer Science - Cryptography and Security K.6.5
Druh dokumentu:	Working Paper
Popis:	In this paper, we propose a novel continuous authentication system for smartphone users. The proposed system entirely relies on unlabeled phone movement patterns collected through smartphone accelerometer. The data was collected in a completely unconstrained environment over five to twelve days. The contexts of phone usage were identified using k-means clustering. Multiple profiles, one for each context, were created for every user. Five machine learning algorithms were employed for classification of genuine and impostors. The performance of the system was evaluated over a diverse population of 57 users. The mean equal error rates achieved by Logistic Regression, Neural Network, kNN, SVM, and Random Forest were 13.7%, 13.5%, 12.1%, 10.7%, and 5.6% respectively. A series of statistical tests were conducted to compare the performance of the classifiers. The suitability of the proposed system for different types of users was also investigated using the failure to enroll policy. Comment: IEEE International Joint Conference on Biometrics (IJCB 2017), Denver, Colorado
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1708.04399 Zobrazit plný text záznamu View this record from Arxiv