FPGADefender: Malicious Self-Oscillator Scanning for Xilinx UltraScale+ FPGAs
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 178619735
- Type
- D - Journal article
- DOI
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10.1145/3402937
- Title of journal
- ACM Transactions on Reconfigurable Technology and Systems
- Article number
- 3402937
- First page
- -
- Volume
- 13
- Issue
- 3
- ISSN
- 1936-7406
- Open access status
- Exception within 3 months of publication
- Month of publication
- September
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
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A - Computer Science
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper proposes the first solution to detect malicious FPGA configurations by investigating FPGA binaries (bitstreams).
This work was recognized by the FPGA market leader Xilinx who supported further work with USD60,000 cash and USD20,000 equipment.
The methodology was used to identify security holes (and appropriate patches) in Amazon Web Services offerings - adopted by AWS in summer 2020."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
