Sga Solutions Co., Ltd.

Su Yeon Yoo

Sung Kyu Kim

Sung Jin Kim

Soo Hwan Kim

Seung Jae Kim

The present invention relates to an exploit kit detection system based on a neural network using an image and provides a configuration including: a file collection module for collecting a web file created in a web document code and a script code; a distribution module for distributing and storing the collected web file; a management module for assigning, when the web file is received, a job ID to the web file and registering the web file in an inspection target list; an image conversion module for converting a corresponding web file into grayscale, targeting the web file registered in the inspection target list; a classification model, as a classification model based on the neural network, for receiving an image of grayscale and classifying existence and a type of the exploit kit (EK); and a result processing module for receiving a classification result, creating a result data, and transmitting the result data to the distribution module. According to the system as described above, as maliciousness of an image is determined by analyzing the image, an environment of detecting an exploit kit through only one conversion process is provided, and thus a fast performance can be demonstrated, and the system may be used for easy filtering of a malicious file from large-scale web page files.

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Daejeon, South Korea

Su Yeon Yoo