Automating Open Source Intelligence: Algorithms for OSINT

by Robert Layton, Paul A Watters

Overview

Algorithms for Automating Open Source Intelligence (OSINT) presents information on the gathering of information and extraction of actionable intelligence from openly available sources, including news broadcasts, public repositories, and more recently, social media. As OSINT has applications in crime fighting, state-based intelligence, and social research, this book provides recent advances in text mining, web crawling, and other algorithms that have led to advances in methods that can largely automate this process.

The book is beneficial to both practitioners and academic researchers, with discussions of the latest advances in applications, a coherent set of methods and processes for automating OSINT, and interdisciplinary perspectives on the key problems identified within each discipline.

Drawing upon years of practical experience and using numerous examples, editors Robert Layton, Paul Watters, and a distinguished list of contributors discuss Evidence Accumulation Strategies for OSINT, Named Entity Resolution in Social Media, Analyzing Social Media Campaigns for Group Size Estimation, Surveys and qualitative techniques in OSINT, and Geospatial reasoning of open data.

Product Details

ISBN-13:	9780128029169
Publisher:	Elsevier Science
Publication date:	12/09/2015
Series:	Computer Science Reviews and Trends Series
Pages:	222
Product dimensions:	7.40(w) x 9.10(h) x 0.50(d)

About the Author

Dr. Robert Layton is a Research Fellow at the Internet Commerce Security Laboratory (ICSL) at Federation University Australia. Dr Layton’s research focuses on attribution technologies on the internet, including automating open source intelligence (OSINT) and attack attribution. Dr Layton’s research has led to improvements in authorship analysis methods for unstructured text, providing indirect methods of linking profiles on social media.

Paul A. Watters is a Professor of Information Technology at Massey University. He was previously Associate Professor of Information Security at the University of Ballarat, and co-founded the Cybercrime Research Laboratory at Macquarie University. His research interests are human factors in security and open source intelligence, and in measuring the risks associated with cybercrime, especially to children and young people. He is a Fellow of the British Computer Society and his work has been cited 1,249 times He has worked closely with government and industry on many projects, including Westpac, IBM, and the Australian Federal Police (AFP).

Table of Contents

Ch 1. Introduction to OSINT

Ch 2. Advances in Automated OSINT

Ch 3. Named Entity Resolution in Social Media

Ch 4. Relative Cyberattack Attribution

Ch 5. Evidence Accumulation Strategies for OSINT

Ch 6. Analyzing Social Media Campaigns for Group Size Estimation

Ch 7. Crawling the Dark Web

Ch 8. Case Study: The Digital Underground

Ch 9. Graph Creation and Analysis for Linking Actors

Ch 10. Case Study Predicting Crime with OSINT

Ch 11. Ethical Considerations w/Public Data

Ch 12: Limitations of automating OSINT

Ch 13. Geospatial Reasoning of Open Data

Ch 14: Future Trends

What People are Saying About This

From the Publisher

This book provides the state-of-the-art on the algorithms necessary for open source intelligence gathering, presenting information on the extraction of actionable intelligence from openly available sources, including news broadcasts, public repositories, and more recently, social media.

Editorial Reviews

"Each chapter can stand alone, but together they give an accurate view of the current situation - it's a good mix of theory and practice(s)…an interesting read for researchers and digital investigators...an eye-opening one for Internet users in general..." —Help Net Security

From the Publisher