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 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_IPFA2020.pdf | 2.49 MB | Adobe PDF | ![]() View/Open |
SCOPUSTM
Citations
50
6
Updated on May 24, 2023
Page view(s)
286
Updated on Jun 4, 2023
Download(s) 10
382
Updated on Jun 4, 2023
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.