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A method for detecting image information leakage risk from electromagnetic emission of computer monitors.

Authors :
Mao, Jian
Liu, Jinming
Zhang, Jiemin
Han, Zhenzhong
Shi, Sen
Source :
Journal of Intelligent & Fuzzy Systems. Sep2020, p1-12. 12p.
Publication Year :
2020

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
147566330
Full Text :
https://doi.org/10.3233/jifs-189337