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Full Description
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.
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
