Deep Learning Based Side Channel Attacks on Lightweight Cryptography (Student Abstract)
| العنوان: | Deep Learning Based Side Channel Attacks on Lightweight Cryptography (Student Abstract) |
|---|---|
| المؤلفون: | Alexander Benjamin, Jack Herzoff, Liljana Babinkostova, Edoardo Serra |
| المصدر: | Proceedings of the AAAI Conference on Artificial Intelligence. 36:12911-12912 |
| بيانات النشر: | Association for the Advancement of Artificial Intelligence (AAAI), 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | General Medicine |
| الوصف: | Computing devices continue to be increasingly spread out within our everyday environments. Computers are embedded into everyday devices in order to serve the functionality of electronic components or to enable new services in their own right. Existing Substitution-Permutation Network (SPN) ciphers, such as the Advanced Encryption Standard (AES), are not suitable for devices where memory, power consumption or processing power is limited. Lightweight SPN ciphers, such as GIFT-128 provide a solution for running cryptography on low resource devices. The GIFT-128 cryptographic scheme is a building block for GIFT-COFB (Authenticated Encryption with Associated Data), one of the finalists in the ongoing NIST lightweight cryptography standardization process (NISTIR 8369). Determination of an adequate level of security and providing subsequent mechanisms to achieve it, is one of the most pressing problems regarding embedded computing devices. In this paper we present experimental results and comparative study of Deep Learning (DL) based Side Channel Attacks on lightweight GIFT-128. To our knowledge, this is the first study of the security of GIFT-128 against DL-based SCA attacks. |
| تدمد: | 2374-3468 2159-5399 |
| DOI: | 10.1609/aaai.v36i11.21592 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::ea42b138b4cdf74e9c50cb5e6dd90638 https://doi.org/10.1609/aaai.v36i11.21592 |
| رقم الانضمام: | edsair.doi...........ea42b138b4cdf74e9c50cb5e6dd90638 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 23743468 21595399 |
|---|---|
| DOI: | 10.1609/aaai.v36i11.21592 |