BehavePassDB: Public Database for Mobile Behavioral Biometrics and Benchmark Evaluation
作者：
Highlights：
• We present a new HCI database, BehavePassDB, with a novel data collection approach.
• We exploit the touchscreen and background sensor data for mobile authentication.
• We employ a deep learning approach based on LSTM to benchmark BehavePassDB.
• We evaluate two different impostor scenarios considering real-life use cases.
• We evaluate the influence of device bias on the authentication performance.
摘要
•We present a new HCI database, BehavePassDB, with a novel data collection approach.•We exploit the touchscreen and background sensor data for mobile authentication.•We employ a deep learning approach based on LSTM to benchmark BehavePassDB.•We evaluate two different impostor scenarios considering real-life use cases.•We evaluate the influence of device bias on the authentication performance.
论文关键词：Mobile authentication,Continuous authentication,Behavioral biometrics,BehavePassDB,Device bias,68T10,68M25
论文评审过程：Received 6 June 2022, Revised 6 September 2022, Accepted 28 September 2022, Available online 1 October 2022, Version of Record 17 October 2022.
论文官网地址：https://doi.org/10.1016/j.patcog.2022.109089
