Agency for Defense Development

Hwaseong Lee

Changhee Choi

Ilhoon Jung

Hosang Yun

Changon Yoo

Sung Jin Park

Jeongchan Park

Jingoog Kim

Yeojeong Yoon

Ilhoon Jeong

This application relates to an apparatus for identifying an abnormal processor. In one aspect, the apparatus includes a memory information collection part that collects memory region information and dynamic library information of a memory. The apparatus may also include a first identification part that identifies an abnormal processor by using a first machine learning model pre-trained based on the memory region information. The apparatus may further include a second identification part that identifies an abnormal processor by using a second machine learning model pre-trained based on the dynamic library information. The apparatus may further include a determination part that determines a final abnormal processor based on either the abnormal processor identified using the first machine learning model or the abnormal processor identified using the second machine learning model.

Apparatus and method for identifying abnormal processor and computer-readable storage medium

The present disclosure relates to an attack group classifying apparatus. The apparatus includes a feature extracting unit configured to extract, from a data set including documents of specific formats, features for identifying attack groups using the documents of the specific formats and an information generating unit configured to generate a machine learning data set based on the extracted features. Further, the apparatus further includes a learning model unit configured to execute a machine learning algorithm on the machine learning data set to generate a classification model for identifying the attack groups.

Apparatus and method for classifying attack groups

There is provided an email authorship classification apparatus. The apparatus includes an information analysis unit configured to analyze header field information in an attribute header of each of emails and extract feature field information related to an authorship of each of the emails from each of the header field information and an information conversion unit configured to convert the feature field information into a feature data set for inputting a learning model thereto. The apparatus further includes a learning model unit configured to generate a classification model for classifying the emails by author by applying a learning process to the feature data set.

Method and apparatus for providing e-mail authorship classification

Growing community of inventors

Daejeon, South Korea

Hwaseong Lee