Yang et al., 2016 - Google Patents
Security of neuromorphic computing: thwarting learning attacks using memristor's obsolescence effectYang et al., 2016
- Document ID
- 9979033470127875317
- Author
- Yang C
- Liu B
- Li H
- Chen Y
- Barnell M
- Wu Q
- Wen W
- Rajendran J
- Publication year
- Publication venue
- 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
External Links
Snippet
Neuromorphic architectures are widely used in many applications for advanced data processing, and often implements proprietary algorithms. In this work, we prevent an attacker with physical access from learning the proprietary algorithm implemented by the …
- 230000000694 effects 0 title abstract description 15
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
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