The development of key technologies of knowledge graph (KG) has promoted the
development of machine cognition technology, and the combination of KG and industry as …

With the rapid development of Internet technology and the advent of the era of big data,
more and more cyber security texts are provided on the Internet. These texts include not only …

Natural language processing (NLP) is crucial in the current processing of data because it
takes into account many sources, formats, and purposes of data as well as information from …

After Action Reports (AARs) provide incisive analysis of cyber-incidents. Extracting cyber-
knowledge from these sources would provide security analysts with credible information …

The number of published manufacturing science digital articles available from scientific
journals and the broader web have exponentially increased every year since the 1990s. To …

Countless cyber threat intelligence (CTI) reports are used by companies around the world
on a daily basis for security reasons. To secure critical cybersecurity information, analysts …

Abstract Named Entity Recognition (NER) for cyber security aims to identify and classify
cyber security terms from a large number of heterogeneous multisource cyber security texts …

The paper presents the results of applying the BERT representation model in the named
entity recognition task for the cybersecurity domain in Russian. Several variants of the model …

Nowadays the amount of cybersecurity data grows quickly on the Internet, however most of
them are textual unstructured data, which is hard for security analysis to understand in time …

A vast majority of cyber security information is in the form of unstructured text. A much-
needed task is to have a machine-assisted analysis of such information. Named Entity …