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Video s3
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    Presenter(s)
    Jun Sheng Ng Headshot
    Display Name
    Jun Sheng Ng
    Affiliation
    Affiliation
    Nanyang Technological University
    Country
    Author(s)
    Display Name
    Jun Sheng Ng
    Affiliation
    Affiliation
    Nanyang Technological University
    Display Name
    Juncheng Chen
    Affiliation
    Affiliation
    Nanyang Technological University
    Display Name
    Nay Aung Kyaw
    Affiliation
    Affiliation
    Nanyang Technological University
    Display Name
    Ne Kyaw Zwa Lwin
    Affiliation
    Affiliation
    Nanyang Technological University
    Display Name
    Kwen-Siong Chong
    Affiliation
    Affiliation
    Zero-Error Systems Pte Ltd
    Display Name
    Joseph Chang
    Affiliation
    Affiliation
    Nanyang Technological University
    Display Name
    Bah-Hwee Gwee
    Affiliation
    Affiliation
    Nanyang Technological University
    Abstract

    We present a side-channel-attack (SCA) resistant asynchronous-logic (async-logic) Advanced Encryption Standard (AES) accelerator embodying both the masking and hiding SCA countermeasures. Our async-logic masked AES accelerator adopts a dual-rail data encoding to perform the masked 128-bit AES operations, and to enable dual-hiding to moderate both the amplitude (vertical dimension) and the time (horizontal dimension) of the side-channel signals. We implement our async-logic masked AES accelerator in FPGA and comprehensively perform the SCA evaluations based on the electromagnetic (EM) emanation. The SCA evaluations are performed based on bus-wise Hamming Distance model, bus-wise & bit-wise Hamming Weight models, and Zero-Value (ZV) model. Based on our experiment results, we show that our async-logic masked AES is secured against SCA with 1 million EM emanations. This is at least 8.3× more resistance than synchronous-logic masked AES and 199.2× more resistance than the synchronous-logic unmasked AES.

    Slides
    • An Asynchronous-Logic Masked Advanced Encryption Standard (AES) Accelerator and its Side-Channel Attack Evaluations (application/pdf)