research-article

Glowworm Attack: Optical TEMPEST Sound Recovery via a Device's Power Indicator LED

Authors:

Boris ZadovAuthors Info & Claims

CCS '21: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security

Pages 1900 - 1914

https://doi.org/10.1145/3460120.3484775

Published: 13 November 2021 Publication History

Abstract

Two main classes of optical TEMPEST attacks against the confidentiality of information processed/delivered by devices have been demonstrated in the past two decades; the first class includes methods for recovering content from monitors, and the second class includes methods for recovering keystrokes from physical and virtual keyboards. In this paper, we identify a new class of optical TEMPEST attacks: recovering sound by analyzing optical emanations from a device's power indicator LED. We analyze the response of the power indicator LED of various devices to sound and show that there is an optical correlation between the sound that is played by connected speakers and the intensity of their power indicator LED due to the facts that: (1) the power indicator LED of various devices is connected directly to the power line, (2) the intensity of a device's power indicator LED is correlative to the power consumption, and (3) many devices lack a dedicated means of countering this phenomenon. Based on our findings, we present the Glowworm attack, an optical TEMPEST attack that can be used by eavesdroppers to recover sound by analyzing optical measurements obtained via an electro-optical sensor directed at the power indicator LED of various devices (e.g., speakers, USB hub splitters, and microcontrollers). We propose an optical-audio transformation (OAT) to recover sound in which we isolate the speech from optical measurements obtained by directing an electro-optical sensor at a device's power indicator LED. Finally, we test the performance of the Glowworm attack in various experimental setups and show that an eavesdropper can apply the attack to recover speech from speakers' power LED indicator with good intelligibility from a distance of 15 meters and with fair intelligibility from 35 meters.

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Cited By

Zhang GFu HXiang ZZhou XHu PCheng XYang Y(2025)Ambient Light Reflection-Based Eavesdropping Enhanced With cGANIEEE Transactions on Mobile Computing10.1109/TMC.2024.346039224:1(72-85)Online publication date: Jan-2025
https://doi.org/10.1109/TMC.2024.3460392
Okuła RMironowicz P(2025)How decoherence affects the security of BB84 quantum key distribution protocolQuantum Information Processing10.1007/s11128-025-04650-824:2Online publication date: 1-Feb-2025
https://doi.org/10.1007/s11128-025-04650-8
Wang CLin FYan HWu TXu WRen KBalzarotti DXu W(2024)VibSpeechProceedings of the 33rd USENIX Conference on Security Symposium10.5555/3698900.3699124(3997-4014)Online publication date: 14-Aug-2024
https://dl.acm.org/doi/10.5555/3698900.3699124
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Index Terms

Glowworm Attack: Optical TEMPEST Sound Recovery via a Device's Power Indicator LED
1. Security and privacy
  1. Security in hardware
    1. Hardware attacks and countermeasures

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cover image ACM Conferences

CCS '21: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security

November 2021

3558 pages

ISBN:9781450384544

DOI:10.1145/3460120

General Chairs:
Yongdae Kim
KAIST, Republic of Korea
,
Jong Kim
POSTECH, Republic of Korea
,
Program Chairs:
Giovanni Vigna
University of California, Santa Barbara / VMware, USA
,
Elaine Shi
Carnegie Mellon University, USA

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Okuła RMironowicz P(2025)How decoherence affects the security of BB84 quantum key distribution protocolQuantum Information Processing10.1007/s11128-025-04650-824:2Online publication date: 1-Feb-2025
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https://dl.acm.org/doi/10.5555/3698900.3699124
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