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About Breaking Cryptographic Implementations Using Deep Learning Techniques
This document discusses applying deep learning techniques to side channel attacks on cryptographic implementations. It begins with an overview of side channel attacks and existing countermeasures. It then discusses how previous work has applied machine learning techniques like support vector machines and random forests to side channel profiling attacks with some success in breaking protected and unprotected implementations. The document proposes to continue this line of research by applying more sophisticated deep learning profiling techniques. It hypothesizes that deep learning attacks will be more effective than existing machine learning and template attacks at recovering keys from both unprotected and protected cryptographic implementations.
Detailed Information
| Author: | ['Anjishnu Mahanta'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 25 |
| Language: | English |
| Format: | |
| Price: | FREE |
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