4.6 Review

Open source intelligence extraction for terrorism-related information: A review

Publisher

WILEY PERIODICALS, INC
DOI: 10.1002/widm.1473

Keywords

OSINT; text mining; terrorism

Ask authors/readers for more resources

In the contemporary era, terrorists have taken advantage of the extensive use of the internet and social media to spread their propaganda and further their goals. Open Source Intelligence (OSINT) provides a solution to analyze online information and extract intelligence in combating terrorism. This paper reviews the latest developments in OSINT and discusses tools and techniques for extracting terrorism-related textual information from publicly accessible sources. It also highlights the challenges and gaps in different phases of OSINT extraction.
In this contemporary era, where a large part of the world population is deluged by extensive use of the internet and social media, terrorists have found it a potential opportunity to execute their vicious plans. They have got a befitting medium to reach out to their targets to spread propaganda, disseminate training content, operate virtually, and further their goals. To restrain such activities, information over the internet in context of terrorism needs to be analyzed to channel it to appropriate measures in combating terrorism. Open Source Intelligence (OSINT) accounts for a felicitous solution to this problem, which is an emerging discipline of leveraging publicly accessible sources of information over the internet by effectively utilizing it to extract intelligence. The process of OSINT extraction is broadly observed to be in three phases (i) Data Acquisition, (ii) Data Enrichment, and (iii) Knowledge Inference. In the context of terrorism, researchers have given noticeable contributions in compliance with these three phases. However, a comprehensive review that delineates these research contributions into an integrated workflow of intelligence extraction has not been found. The paper presents the most current review in OSINT, reflecting how the various state-of-the-art tools and techniques can be applied in extracting terrorism-related textual information from publicly accessible sources. Various data mining and text analysis-based techniques, that is, natural language processing, machine learning, and deep learning have been reviewed to extract and evaluate textual data. Additionally, towards the end of the paper, we discuss challenges and gaps observed in different phases of OSINT extraction. This article is categorized under: Application Areas > Government and Public Sector Commercial, Legal, and Ethical Issues > Social Considerations Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available