Sökning: "Keyi Liu"

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  1. 1. Far Field EM Side-Channel Attack Based on Deep Learning with Automated Hyperparameter Tuning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Keyi Liu; [2021]
    Nyckelord :Side-Channel Attack; Deep Learning; Far Field EM emission; Auto Hyperparameter Tuning; Auto-Keras; AES; Sidokanalattack; Machine Learning; Multilayer Perceptron; Hyperparameter Tuning; Bayesian Optimization; Auto-Keras; AES;

    Sammanfattning : Side-channel attacks have become a realistic threat to the implementations of cryptographic algorithms. By analyzing the unintentional, side-channel leakage, the attacker is able to recover the secret of the target. Recently, a new type of side-channel leakage has been discovered, called far field EM emissions. LÄS MER