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New Method for Computer Identification Through Electromagnetic Radiation

Jun Shi1, Zhujun Zhang2, Yangyang Li1,*, Rui Wang1, Hao Shi1, Xile Li3

China Academy of Electronics and Information Technology, Badachu High-Tech Park, Shijingshan District, Beijing, 100041, China.
Institute of Information Engineering, Chinese Academy of Sciences, 89 Minzhuang Road, Beijing, 100093, China.
Solace Corporation, 535 Legget Drive, 3rd Floor, Ottawa, Ontario, K2K 3B8, Canada.

* Corresponding Author: Yangyang Li. Email: email.

Computers, Materials & Continua 2018, 57(1), 69-80. https://doi.org/10.32604/cmc.2018.03688

Abstract

The electromagnetic waves emitted from devices can be a source of information leakage and can cause electromagnetic compatibility (EMC) problems. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. In addition, the leaks may reveal the hardware information of the computer, which is more important for some attackers, protectors and security inspection workers. In this paper, we propose a statistical distribution based algorithm (SD algorithm) to extracted eigenvalues from electromagnetic radiate video signals, and then classified computers by using classifier based on Bayesian and SVM. We can identify computers automatically and accurately through electromagnetic radiation by using the algorithm in our experiment environment.

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Cite This Article

APA Style
Shi, J., Zhang, Z., Li, Y., Wang, R., Shi, H. et al. (2018). New method for computer identification through electromagnetic radiation. Computers, Materials & Continua, 57(1), 69-80. https://doi.org/10.32604/cmc.2018.03688
Vancouver Style
Shi J, Zhang Z, Li Y, Wang R, Shi H, Li X. New method for computer identification through electromagnetic radiation. Comput Mater Contin. 2018;57(1):69-80 https://doi.org/10.32604/cmc.2018.03688
IEEE Style
J. Shi, Z. Zhang, Y. Li, R. Wang, H. Shi, and X. Li, “New Method for Computer Identification Through Electromagnetic Radiation,” Comput. Mater. Contin., vol. 57, no. 1, pp. 69-80, 2018. https://doi.org/10.32604/cmc.2018.03688



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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