In:
Journal of Intelligent & Fuzzy Systems, IOS Press, Vol. 40, No. 2 ( 2021-02-02), p. 2981-2991
Abstract:
The unintentional electromagnetic (EM) emission of computer monitors may cause the leakage of image information displayed on the monitor. Detection of EM information leakage risk is significant for the information security of the monitor. The traditional detection method is to verify EM information leakage by reconstructing an image from EM emission. The detection method based on image reconstruction has limitations: adequate signal sampling rate, accurate synchronization signal, and dependence on operational experience. In this paper, we analyze the principle of image information leakage and propose an innovative detection method based on Convolutional Neural Network (CNN). This method can identify the image information in EM emission to verify the EM information leakage risk of the monitor. It overcomes the limitations of the traditional method with machine learning. This is a new attempt in the field of EM information leakage detection. Experimental results show that it is more adaptable and reliable in complex detection environment.
Type of Medium:
Online Resource
ISSN:
1064-1246
,
1875-8967
Language:
Unknown
Publisher:
IOS Press
Publication Date:
2021
detail.hit.zdb_id:
2070080-5
SSG:
11
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