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| Main Authors: | , , , , |
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| Format: | Preprint |
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2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.00411 |
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| _version_ | 1866910006743400448 |
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| author | Chen, Wenhao Zhang, Wenyi Morty Sun, Wei Bharadia, Dinesh Ayyalasomayajula, Roshan |
| author_facet | Chen, Wenhao Zhang, Wenyi Morty Sun, Wei Bharadia, Dinesh Ayyalasomayajula, Roshan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_00411 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SpyDir: Spy Device Localization Through Accurate Direction Finding Chen, Wenhao Zhang, Wenyi Morty Sun, Wei Bharadia, Dinesh Ayyalasomayajula, Roshan Cryptography and Security 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. |
| title | SpyDir: Spy Device Localization Through Accurate Direction Finding |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2602.00411 |