Glowworm Attack: Optical TEMPEST Sound Recovery via a Device's Power Indicator LED
Ben Nassi, Yaron Pirutin, Tomer Cohen Galor, Yuval Elovici, Boris Zadov
摘要
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.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper6
- mmEve: eavesdropping on smartphone's earpiece via COTS mmWave deviceChao Wang, Feng Lin, Tiantian Liu, Kaidi Zheng 等MobiCom 2022 · 被引用 60 次
- VibSpeech: Exploring Practical Wideband Eavesdropping via Bandlimited Signal of Vibration-based Side ChannelChao Wang, Feng Lin, Hao Yan, Tong Wu 等USENIX Security 2024 · 被引用 16 次
- EchoLight: Sound Eavesdropping based on Ambient Light ReflectionGuoming Zhang, Zhijie Xiang, Heqiang Fu, Yanni Yang 等INFOCOM 2024 · 被引用 9 次
- Hiding an Ear in Plain Sight: On the Practicality and Implications of Acoustic Eavesdropping with Telecom Fiber Optic CablesYouqian Zhang, Zheng Fang, Huan Wu, Sze-Yiu Chau 等NDSS 2026
- Side Eye: Characterizing the Limits of POV Acoustic Eavesdropping from Smartphone Cameras with Rolling Shutters and Movable LensesYan Long, Pirouz Naghavi, Blas Kojusner, Kevin R. B. Butler 等S&P 2023
它引用的顶会 Paper9
- Screaming Channels: When Electromagnetic Side Channels Meet Radio TransceiversGiovanni Camurati, Sebastian Poeplau, Marius Muench, Tom Hayes 等CCS 2018 · 被引用 186 次
- My Smartphone Knows What You Print: Exploring Smartphone-based Side-channel Attacks Against 3D PrintersChen Song, Feng Lin, Zhongjie Ba, Kui Ren 等CCS 2016 · 被引用 122 次
- Speechless: Analyzing the Threat to Speech Privacy from Smartphone Motion SensorsS. Abhishek Anand, Nitesh SaxenaS&P 2018 · 被引用 110 次
- Leave Your Phone at the Door: Side Channels that Reveal Factory Floor SecretsAvesta Hojjati, Anku Adhikari, Katarina Struckmann, Edward Chou 等CCS 2016 · 被引用 78 次
- Synesthesia: Detecting Screen Content via Remote Acoustic Side ChannelsDaniel Genkin, Mihir Pattani, Roei Schuster, Eran TromerS&P 2019 · 被引用 63 次
相关 Paper
- Optical Cryptanalysis: Recovering Cryptographic Keys from Power LED Light FluctuationsBen Nassi, Ofek Vayner, Etay Iluz, Dudi Nassi 等CCS 2023 · 被引用 9 次
- TEMPEST Comeback: A Realistic Audio Eavesdropping Threat on Mixed-signal SoCsJieun Choi, Hae-Yong Yang, Dong-Ho ChoCCS 2020 · 被引用 33 次
- LightThief: Your Optical Communication Information is Stolen behind the WallXin Liu, Wei Wang, Guanqun Song, Ting ZhuUSENIX Security 2023
- Lamphone: Passive Sound Recovery from a Desk Lamp's Light Bulb VibrationsBen Nassi, Yaron Pirutin, Raz Swisa, Adi Shamir 等USENIX Security 2022
- PPG-Hear: A Practical Eavesdropping Attack with Photoplethysmography SensorsYuchen Su, Shiyue Huang, Hongbo Liu, Yuefeng Chen 等UbiComp 2024 · 被引用 5 次
