Quickest Intruder Detection for Multiple User Active Authentication
This work addresses latency reduction in intruder detection for multi-user authentication systems, representing an incremental advancement in the field.
The paper tackled the problem of detecting intruders with low latency in multi-user active authentication systems by extending the Quickest Change Detection framework to multiple users and proposing the MQID algorithm, which achieved improved detection performance on two face modality datasets.
In this paper, we investigate how to detect intruders with low latency for Active Authentication (AA) systems with multiple-users. We extend the Quickest Change Detection (QCD) framework to the multiple-user case and formulate the Multiple-user Quickest Intruder Detection (MQID) algorithm. Furthermore, we extend the algorithm to the data-efficient scenario where intruder detection is carried out with fewer observation samples. We evaluate the effectiveness of the proposed method on two publicly available AA datasets on the face modality.