Convolutional neural network based sidechannel attacks
DOI:
https://doi.org/10.54654/isj.v1i15.834Keywords:
Side-channel attack, Profiled attack, machine learningTóm tắt
Abstract—The profiled attack is considered one of
the most effective side-channel attacks (SCA)
methods used to reveal the secret key and evaluate
the security of the cryptographic devices. By
considering a classification problem, profiled SCA
can be successfully conducted by machine learning
techniques, as shown by recent works. However,
these studies only provide general principles of the
attack. Therefore, this paper presents technical
aspects and specific instructions for an attacker
when performing a profiled attack on a specific
cryptographic device using a popular deep
learning technique called convolution neural
network. The experimental process and the results
of the attack on AES-128 are presented to prove
the effectiveness of the attack procedure.
Tóm tắt—Trong các phương pháp tấn công
kênh kề, tấn công mẫu được xem là một trong các
phương pháp hiệu quả được sử dụng để tìm khóa
bí mật và đánh giá độ an toàn của thiết bị mật mã.
Bài toán tấn công mẫu có điểm tương đồng với bài
toán phân lớp sử dụng các kỹ thuật học máy, học
sâu. Các nghiên cứu về tấn công mẫu gần đây chỉ
ra rằng có thể áp dụng thành công kỹ thuật học
sâu khác nhau vào quy trình của cuộc tấn công
mẫu. Tuy nhiên các nghiên cứu này chỉ đưa ra
nguyên lý chung của tấn công. Do đó, bài báo này
đề xuất một quy trình tấn công cụ thể bao gồm các
khía cạnh kỹ thuật, các chỉ dẫn cụ thể cho người
tấn công khi thực hiện cuộc tấn công mẫu trên
thiết bị mật mã cụ thể sử dụng một kỹ thuật học
sâu phổ biến là mạng nơ-ron tích chập. Quá trình
thực nghiệm và kết quả tấn công trên AES-128
cũng được trình bày để chứng minh tính hiệu dụng
của quy trình tấn công đề xuất.
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