S2w Inc.

Korea Advanced Institute of Science and Technology

Jin Woo Chung

Yong Jae Lee

Seung Won Shin

Sang Duk Suh

Chang Hoon Yoon

Young Jin Jin

Jian Cui

Da Yeon Yim

Eu Gene Jang

Provided is a system for training a language model for cybersecurity, which includes: a document collection unit that collects a cybersecurity document used for training a language model for cybersecurity; an extraction unit that identifies non-linguistic elements in the cybersecurity document based on a non-linguistic element database; a tokenization unit that tokenizes the cybersecurity document to generate a plurality of tokens; and a language model application unit that controls the language model to simultaneously perform a first task of classifying types of the non-linguistic elements including at least one of a Bitcoin address, a hash value, an IP address, and a vulnerability identifier included in the cybersecurity document and a second task of recovering only linguistic elements of the cybersecurity document.

Method of training language model for cybersecurity and system performing the same

The present disclosure relates to a method of collecting, by a terminal, learning data of an artificial intelligence model to perform dark web document classification, the method including: generating a first word set masked with a first identifier based on text included in a first dark web document; generating a second word set masked with a second identifier based on text included in a second dark web document; calculating a similarity by comparing the first word set and the second word set; and, based on the similarity, collecting the second dark web document in a second storage unit when the similarity does not exceed a specific value, and discarding the second dark web document when the similarity exceeds the specific value.

Method of collecting and preprocessing learning data of artificial intelligence model to perform dark web document classification

Growing community of inventors

Seongnam-si, South Korea

Jin Woo Chung