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Titel:

Counteract Side-Channel Analysis of Neural Networks by Shuffling

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Brosch, Manuel and Probst, Matthias and Sigl, Georg
Abstract:
Machine learning is becoming an essential part in almost every electronic device. Implementations of neural networks are mostly targeted towards computational performance or memory footprint. Nevertheless, security is also an important part in order to keep the network secret and protect the intellectual property associated to the network. Especially, since neural network implementations are demonstrated to be vulnerable to side-channel analysis, powerful and computational cheap countermeasures...     »
Stichworte:
neural networks, side-channel analysis, counter- measure, shuffling
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Kongress- / Buchtitel:
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Kongress / Zusatzinformationen:
Antwerp, Belgium
Datum der Konferenz:
14.-23.03.2022
Verlag / Institution:
IEEE
Jahr:
2022
Quartal:
1. Quartal
Jahr / Monat:
2022-03
Monat:
Mar
Reviewed:
ja
Sprache:
en
WWW:
https://www.date-conference.com/
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