Automating Open Source Intelligence (Paperback)

Robert Layton

ISBN 10: 0128029161 / ISBN 13: 9780128029169

Edité par Syngress Media,U.S., Rockland, MA, 2015

A propos de cet article

Paperback. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

N° de réf. du vendeur 9780128029169

Détails bibliographiques

• Titre: Automating Open Source Intelligence (Paperback)
• Éditeur: Syngress Media,U.S., Rockland, MA
• Date de parution: 2015
• Langue: anglais
• ISBN à 10 chiffres: 0128029161
• ISBN à 13 chiffres: 9780128029169
• Reliure: Paperback
• État de l'article: new

A propos de ce titre

Synopsis

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.

À propos des auteurs

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).