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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