A novel obfuscation method based on majority logic for preventing unauthorized access to binary deep neural networks
Abstract The significant expansion of deep learning applications has necessitated safeguarding the deep neural network (DNN) model from potential unauthorized access, highlighting its importance as a valuable asset. This study proposes an innovative key-based algorithm-hardware co-design methodology...
Saved in:
| Main Authors: | Alireza Mohseni, Mohammad Hossein Moaiyeri, Mohammad Javad Adel |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-09722-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
TOP: A Combined Logical and Physical Obfuscation Method for Securing Networks-on-Chip Against Reverse Engineering Attacks
by: Mona Hashemi, et al.
Published: (2025-01-01) -
Ternary computing using a novel spintronic multi-operator logic-in-memory architecture
by: Amirhossein Fathollahi, et al.
Published: (2025-03-01) -
Obfuscation of combination circuits of digital devices from unauthorized access
by: L. A. Zolotorevich
Published: (2019-09-01) -
Hardware and Software Methods for Secure Obfuscation and Deobfuscation: An In-Depth Analysis
by: Khaled Saleh, et al.
Published: (2025-06-01) -
Code Obfuscation: A Comprehensive Approach to Detection, Classification, and Ethical Challenges
by: Tomer Raitsis, et al.
Published: (2025-01-01)