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http://dx.doi.org/10.5573/ieie.2017.54.2.076

Image-based Artificial Intelligence Deep Learning to Protect the Big Data from Malware  

Kim, Hae Jung (Department of Cyber Security, Kyung-il University)
Yoon, Eun Jun (Department of Cyber Security, Kyung-il University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.54, no.2, 2017 , pp. 76-82 More about this Journal
Abstract
Malware, including ransomware to quickly detect, in this study, to provide an analysis method of malicious code through the image analysis that has been learned in the deep learning of artificial intelligence. First, to analyze the 2,400 malware data, and learning in artificial neural network Convolutional neural network and to image data. Extracts subgraphs to convert the graph of abstracted image, summarizes the set represent malware. The experimentally analyzed the malware is not how similar. Using deep learning of artificial intelligence by classifying malware and It shows the possibility of accurate malware detection.
Keywords
Malware; Artificial Intelligence; Deep Learning; Convolutional Neural Network; Security;
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