| Citation: | MAO Jian, LIU Taikang, LIU Peiguoet al. An electromagnetic information leakage detection method using deep learning[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(11): 2200-2207. doi: 10.13700/j.bh.1001-5965.2020.0420(in Chinese)
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Electronic information equipment will emit electromagnetic wave unintentionally, which contains useful information. It will lead to the electromagnetic information leakage, thus threatening the information security. The traditional electromagnetic information leakage detection methods are difficult to extract useful information from uncertain electromagnetic leakage signals in complex environments. Aimed at the problem of electromagnetic information security, the electromagnetic information leakage detection is studied. A detection method based on deep learning is proposed. The method designs a one-dimensional convolutional neural network suitable for electromagnetic signals, and combines an improved gradient-weighted class activation mapping algorithm. It can locate and extract the electromagnetic leakage information characteristics intelligently under the condition of unknown the characteristics through deep learning so as to solve the problem of extracting electromagnetic leakage information in complex environments. The effectiveness of the proposed method is verified by experiments and simulation.
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