التفاصيل البيبلوغرافية
| العنوان: |
Machine Learning Attacks‐Resistant Security by Mixed‐Assembled Layers‐Inserted Graphene Physically Unclonable Function (Adv. Sci. 30/2023). |
| المؤلفون: |
Lee, Subin (AUTHOR), Jang, Byung Chul (AUTHOR), Kim, Minseo (AUTHOR), Lim, Si Heon (AUTHOR), Ko, Eunbee (AUTHOR), Kim, Hyun Ho (AUTHOR), Yoo, Hocheon (AUTHOR) |
| المصدر: |
Advanced Science. 10/26/2023, Vol. 10 Issue 30, p1-1. 1p. |
| مصطلحات موضوعية: |
*MACHINE learning, *GRAPHENE |
| مستخلص: |
By introducing diverse functional groups via mixed-assembled monolayers into the graphene device, they created an unconventional dipole distribution, yielding distinct characteristics and abundant randomness. This approach achieves significant results: 50% uniformity, 45.5% inter-Hamming distance, and a strong 10.33% defense rate against machine learning attacks. B Machine Learning Attacks-Resistant Security b In article number 2302604, Hocheon Yoo and co-workers present an efficient method for extracting a security key using graphene at just 100 mV voltage. [Extracted from the article] |
| قاعدة البيانات: |
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