Simultaneous Intrusion Detection and Localization Using ISAC Network

TL;DR

This paper presents a novel Wi-Fi-based method for accurately detecting and localizing physical intrusions in smart homes, achieving high accuracy and low false alarm rates through simulation.

Contribution

It introduces a new approach combining access point signals and an anchor node for simultaneous intrusion detection and localization in indoor environments.

Findings

92% accuracy in detection and localization

False positive rate below 5%

False negative rate around 3%

Abstract

The rapid increase in utilization of smart home technologies has introduced new paradigms to ensure the security and privacy of inhabitants. In this study, we propose a novel approach to detect and localize physical intrusions in indoor environments. The proposed method leverages signals from access points (APs) and an anchor node (AN) to achieve accurate intrusion detection and localization. We evaluate its performance through simulations under different intruder scenarios. The proposed method achieved a high accuracy of 92% for both intrusion detection and localization. Our simulations demonstrated a low false positive rate of less than 5% and a false negative rate of around 3%, highlighting the reliability of our approach in identifying security threats while minimizing unnecessary alerts. This performance underscores the effectiveness of integrating Wi-Fi sensing with advanced signal processing techniques for enhanced smart home security.