TY - JOUR
T1 - MAGNETO
T2 - Fingerprinting USB Flash Drives via Unintentional Magnetic Emissions
AU - Ibrahim, Omar Adel
AU - Sciancalepore, Savio
AU - Oligeri, Gabriele
AU - Pietro, Roberto Di
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2021/1
Y1 - 2021/1
N2 - Universal Serial Bus (USB) Flash Drives are nowadays one of the most convenient and diffused means to transfer files, especially when no Internet connection is available. However, USB flash drives are also one of the most common attack vectors used to gain unauthorized access to host devices. For instance, it is possible to replace a USB drive so that when the USB key is connected, it would install passwords stealing tools, root-kit software, and other disrupting malware. In such a way, an attacker can steal sensitive information via the USB-connected devices, as well as inject any kind of malicious software into the host. To thwart the above-cited raising threats, we propose MAGNETO, an efficient, non-interactive, and privacy-preserving framework to verify the authenticity of a USB flash drive, rooted in the analysis of its unintentional magnetic emissions. We show that the magnetic emissions radiated during boot operations on a specific host are unique for each device, and sufficient to uniquely fingerprint both the brand and the model of the USB flash drive, or the specific USB device, depending on the used equipment. Our investigation on 59 different USB flash drives - belonging to 17 brands, including the top brands purchased on Amazon in mid-2019 - reveals a minimum classification accuracy of 98.2% in the identification of both brand and model, accompanied by a negligible time and computational overhead. MAGNETO can also identify the specific USB Flash drive, with a minimum classification accuracy of 91.2%. Overall, MAGNETO proves that unintentional magnetic emissions can be considered as a viable and reliable means to fingerprint read-only USB flash drives. Finally, future research directions in this domain are also discussed.
AB - Universal Serial Bus (USB) Flash Drives are nowadays one of the most convenient and diffused means to transfer files, especially when no Internet connection is available. However, USB flash drives are also one of the most common attack vectors used to gain unauthorized access to host devices. For instance, it is possible to replace a USB drive so that when the USB key is connected, it would install passwords stealing tools, root-kit software, and other disrupting malware. In such a way, an attacker can steal sensitive information via the USB-connected devices, as well as inject any kind of malicious software into the host. To thwart the above-cited raising threats, we propose MAGNETO, an efficient, non-interactive, and privacy-preserving framework to verify the authenticity of a USB flash drive, rooted in the analysis of its unintentional magnetic emissions. We show that the magnetic emissions radiated during boot operations on a specific host are unique for each device, and sufficient to uniquely fingerprint both the brand and the model of the USB flash drive, or the specific USB device, depending on the used equipment. Our investigation on 59 different USB flash drives - belonging to 17 brands, including the top brands purchased on Amazon in mid-2019 - reveals a minimum classification accuracy of 98.2% in the identification of both brand and model, accompanied by a negligible time and computational overhead. MAGNETO can also identify the specific USB Flash drive, with a minimum classification accuracy of 91.2%. Overall, MAGNETO proves that unintentional magnetic emissions can be considered as a viable and reliable means to fingerprint read-only USB flash drives. Finally, future research directions in this domain are also discussed.
KW - USB
KW - critical infrastructures protection
KW - hardware security
KW - magnetic emissions
UR - http://www.scopus.com/inward/record.url?scp=85099216049&partnerID=8YFLogxK
U2 - 10.1145/3422308
DO - 10.1145/3422308
M3 - Article
AN - SCOPUS:85099216049
SN - 1539-9087
VL - 20
JO - Transactions on Embedded Computing Systems
JF - Transactions on Embedded Computing Systems
IS - 1
M1 - 8
ER -