NLG is the process of transforming structured data into narratives. Contrary to Natural Language Processing (NLP) that reads and analyses textual data to derive analytic insights, NLG composes synthesized text through analysis of pre-defined structured data. NLG is more than the process of rendering data into a language that sounds natural to humans. It can play a vital role in uncovering valuable insights from massive datasets (big data) through automated forms of analysis.
Adaption of NLG in other verticals has increased in recent years, yet applications of NLG technology in the Cyber Threat Intelligence (CTI) domain are sparse. On one hand, intelligence teams accumulate millions of information generated by security controls or obtained from intelligence source. On the other hand, the intelligence product is often a narrative report written by an analyst. With the influx of data, intelligence teams are confronted with challenges pertaining to data assessment and analysis, (near-) real-time creation of intelligence products targeted at the right audience; all while operating at scale and with accuracy.
Speakers
- Jörg Abraham, Chief Analyst
- Sergey Polzunov, Software Engineer