POS2 - Smart Redundancy Schemes for ANNs Against Fault Attacks
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hdl:2117/372123
Document typeConference report
Defense date2022-05
Rights accessRestricted access - publisher's policy
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Abstract
Artificial neural networks (ANNs) are used to
accomplish a variety of tasks, including safety critical ones.
Hence, it is important to protect them against faults that
can influence decisions during operation. In this paper, we
propose smart and low-cost redundancy schemes that protect
the most vulnerable ANN parts against fault attacks. Experimental
results show that the two proposed smart schemes
perform similarly to dual modular redundancy (DMR) at a
much lower cost, generally improve on the state of the art,
and reach protection levels in the range of 93% to 99%.
CitationKöylü, T.Ç.; Hamdioui, S.; Taouil, M. POS2 - Smart Redundancy Schemes for ANNs Against Fault Attacks. A: 27th IEEE European Test Symposium (ETS). 2022,
Publisher versionhttps://ieeexplore.ieee.org/xpl/conhome/9810327/proceeding
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PS2-2.pdf | 396,8Kb | Restricted access |