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  4. DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks
 
research article

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Mahmoud, Dina Gamaleldin Ahmed Shawky  
•
Dervishi, David
•
Hussein, Samah
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December 22, 2022
IEEE Access

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility of FPGAs with the software programmability of central processing units (CPUs) to improve the performance of processing-intensive workloads. A variety of heterogeneous FPGA-CPU embedded systems are thus available. However, the security of FPGA-CPU systems has not yet been thoroughly evaluated. In this work, we demonstrate the first attack on FPGA-CPU platforms which leverages undervolting caused by the FPGA to inject faults and exploit them against a software encryption algorithm. The aggressor FPGA affects a CPU sharing the same system-on-chip (SoC). We show that circuits in the FPGA fabric, controlled by an attacker, can create a significant supply voltage drop which, in turn, faults the software computation performed by the CPU or even causes a denial-of-service attack. Our results do not rely on any hardware modifications of the target platform. We present a characterization of the attack parameters and the effects observed. Then, we leverage the FPGA-induced undervolting to fault multiplications executing on the CPU. We also highlight how an attacker might benefit from the injected faults to compromise the system’s security by demonstrating differential fault analysis (DFA) against an advanced encryption standard (AES) implementation. Our work exposes a new electrical-level threat in tightly integrated modern FPGA-CPU SoCs, bringing to light a need for more research on countermeasures.

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Type
research article
DOI
10.1109/ACCESS.2022.3231753
Author(s)
Mahmoud, Dina Gamaleldin Ahmed Shawky  
Dervishi, David
Hussein, Samah
Lenders, Vincent
Stojilovic, Mirjana  
Date Issued

2022-12-22

Published in
IEEE Access
Volume

10

Start page

134199

End page

134216

Subjects

FPGA

•

heterogeneous computing

•

differential fault analysis

•

remote attacks

•

undervolting

Note

This research is supported by armasuisse Science and Technology.

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
PARSA  
Available on Infoscience
January 10, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/193640
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