.png){kind=icon}
返回
An Efficient Collision Power Attack on AES Encryption in Edge Computing
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2896256.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Edge computing has become a promising paradigm for the context-aware and delay-sensitive IoT data analytics. For the sake of security, some cryptographic algorithms such as AES, RSA, and so on, are employed for the encryption communication and authentication. The collision power attack is a typical physical attack to recover the secret key of the AES algorithm. However, almost all collision attacks aim at the detection of internal collisions caused by the output of S-boxes, and the linear layers are not concerned with those protected implementations. The relation between the mask and the masked data has been given little attention and stays as is, where the leakages still exist. In this paper, we focus on three typical AES implementations in edge computing, and propose a new type of collision attack by making use of leakages from linear layers, which is capable of breaking masking schemes with uniformly distributed random masks. In addition, a novel scalable collision attack of general applicability and high-efficiency is proposed and applied to masked linear layers and masked S-boxes. It can reach an equal level of performance compared to the second-order power analysis with acceptable off-line search, which improves the known collision attacks significantly.
Keyword:
Edge computing
collision attack
scalable collision
side-channel attack
linear layer
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
.png){kind=icon}
分享收藏Understanding and Incorporating Home-Based Child Care Into Early Education and Development Systems
OAAI
OAAI分享收藏Distilling at the Edge: A Local Differential Privacy Obfuscation Framework for IoT Data Analytics
PREAI
分享收藏 没有更多内容
没有更多内容