SpyDir: Spy Device Localization Through Accurate Direction Finding

TL;DR

SpyDir is a system that accurately localizes hidden spy IoT devices indoors by analyzing electromagnetic emanations, significantly outperforming baseline algorithms in accuracy and error reduction.

Contribution

This work introduces SpyDir, a novel system combining spectrum sniffing, emanation enhancement, and multipath resolution for precise indoor spy device localization.

Findings

Achieves an average AoA error of 6.30 degrees, outperforming baseline algorithms.

Reduces mean localization error to 19.86cm from over 200cm.

Demonstrates effectiveness across various indoor environments.

Abstract

Hidden spy cameras have become a great privacy threat recently, as these low-cost, low-power, and small form-factor IoT devices can quietly monitor human activities in the indoor environment without generating any side-channel information. As such, it is difficult to detect and even more challenging to localize them in the rich-scattering indoor environment. To this end, this paper presents the design, implementation, and evaluation of SpyDir, a system that can accurately localize the hidden spy IoT devices by harnessing the electromagnetic emanations automatically and unintentionally emitted from them. Our system design mainly consists of a portable switching antenna array to sniff the spectrum-spread emanations, an emanation enhancement algorithm through non-coherent averaging that can de-correlate the correlated noise effect due to the square-wave emanation structure, and a multipath-resolving algorithm that can exploit the relative channels using a novel optimization-based sparse AoA derivation. Our real-world experimental evaluation across different indoor environments demonstrates an average AoA error of 6.30 deg, whereas the baseline algorithm yields 21.06 deg, achieving over a 3.3 times improvement in accuracy, and a mean localization error of 19.86cm over baseline algorithms of 206.79cm (MUSIC) and 294.75cm (SpotFi), achieving over a 10.41 times and 14.8 times improvement in accuracy.