Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147144
Title: Practical cold boot attack on IoT device - Case study on Raspberry Pi -
Authors: Won, Yoo-Seung
Park, Jong-Yeon
Han, Dong-Guk
Bhasin, Shivam
Keywords: Engineering::Computer science and engineering::Information systems::Information systems applications
Issue Date: 2020
Source: Won, Y., Park, J., Han, D. & Bhasin, S. (2020). Practical cold boot attack on IoT device - Case study on Raspberry Pi -. 2020 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits. https://dx.doi.org/10.1109/IPFA49335.2020.9260613
metadata.dc.contributor.conference: 2020 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits
Abstract: Volatile memory like SDRAM, forms an integral part of any computer system. It stores variety of data including sensitive data like passwords and PIN. The data stored in SDRAM is wiped off on power-off. However, by bringing the RAM to freezing cold temperature before power off, the data can persist for several seconds, allowing recovery through cold boot attacks. In this work, we investigate the vulnerability of IoT device such as Raspberry Pi against cold boot attack for the first time. Our study found that even though the boot sequence is different from laptop, personal computer, and smartphone, we demonstrate that it is still possible to steal the RAM data, even when the bootloader is not public. The net cost of the attack was under 10 dollars and 99.99% of the RAM data was successfully recovered.
URI: https://hdl.handle.net/10356/147144
DOI: 10.1109/IPFA49335.2020.9260613
Research Centres: Temasek Laboratories 
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/IPFA49335.2020.9260613
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:TL Conference Papers

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