Automating Open Source Intelligence
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.
Review
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.
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.
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