Enhanced Crime and Threat Intelligence Hunter with Named Entity Recognition and Sentiment Analysis

Abstract

Collecting cybercrime evidence on the Internet typically involves reconnaissance and analyses of information extracted. Scouring the Internet, especially the Deep Web, often requires manual effort and is time-consuming. Hence, it is imperative to have an efficient framework for an intelligent tool to gather cyber intel automatically according to programmed directives. In this paper, we present an updated design to our prior threat intelligence hunter. We make use of machine learning for parsing linguistic intel.