Presented at
DEF CON 31 (2023),
Aug. 12, 2023, 12:30 p.m.
(45 minutes)
In this talk, we present video-based cryptanalysis, a new method to recover secret keys from a non-compromised device by analyzing video footage obtained from a device’s power LED. We show that cryptographic computations performed by the device’s CPU change the power consumption of the device which affects the brightness/color of the device’s power LED. The changes in the brightness can be detected at a sufficient sampling rate for cryptanalysis by obtaining video footage from a device’s power LED (by filling the frame with the LED) and exploiting the video camera’s rolling shutter, to increase the sampling rate by three orders of magnitude. The frames of the video footage are analyzed in the RGB space, and the RGB values are used to recover the secret key. We demonstrate the recovery of: (1) a 256- bit ECDSA key from a smartcard using video footage obtained from the power LED of the smartcard reader via a hijacked Internet-connected security camera located 16 meters away from the smartcard reader, and (2) a 378-bit SIKE key from a Samsung Galaxy S8 using video footage obtained from the power LED of Logitech Z120 USB speakers (that were connected to the same USB Hub of the Galaxy S8) via iPhone 12.
We discuss countermeasures, limitations, and the future of video-based cryptanalysis.
Presenters:
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Ofek Vayner
- M.Sc. Student at Ben-Gurion University of the Negev
Ofek Vayner is an M.Sc student at Ben-Gurion University of the Negev and a security researcher at BGU's Cyber Security Research Center. He holds a B.Sc. degree from the Department of Electrical Engineering at Ben-Gurion University of the Negev. His primary research interests are side-channel attacks and cryptanalysis.
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Ben Nassi
- Postdoctoral Researcher at Cornell Tech
Dr. Ben Nassi is a postdoctoral researcher at Cornell Tech. He is interested in building robust systems and investigates the security and privacy of cyber-physical systems and hardware/devices in the topics of side-channel attacks and AI security using signal processing and machine learning techniques. His research has been presented at top academic conferences, published in journals and Magazines, and covered by international media. Ben has spoken at prestigious industrial conferences (Black Hat Asia and USA, RSAC USA, AI Week, CodeBlue, SecTor, and CyberTech) and he serves as a PC member in ACM CCS (22 and 23) and BlackHat Asia (22 and 23). His research entitled him to two nominations for the Pwnie Award.
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