Quickest Intruder Detection for Multiple User Active Authentication

TL;DR

This paper introduces a low-latency intruder detection method for multi-user active authentication systems, extending quickest change detection techniques to multiple users and data-efficient scenarios, validated on face datasets.

Contribution

It develops the MQID algorithm for rapid intruder detection in multi-user AA systems and adapts it for data-efficient operation, a novel extension of existing methods.

Findings

Effective intruder detection with low latency demonstrated on face datasets.

Algorithm performs well in data-efficient scenarios with fewer observations.

Extension of quickest change detection to multi-user active authentication.

Abstract

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.