Can I read NOWHERE TO HIDE: Open Source Intelligence Gathering - CASEBOOK: How the FBI, Media, and Public Identiified the January 6, 2021 U.S. Capitol Rioters on EtoBox?

NOWHERE TO HIDE: Open Source Intelligence Gathering - CASEBOOK: How the FBI, Media, and Public Identiified the January 6, 2021 U.S. Capitol Rioters by Daniel Farber Huang is a nonfiction available to read on EtoBox.

What is NOWHERE TO HIDE: Open Source Intelligence Gathering - CASEBOOK: How the FBI, Media, and Public Identiified the January 6, 2021 U.S. Capitol Rioters about?

NOWHERE TO HIDE: Open Source Intelligence Gathering provides practical insight into the investigative tools and open source intelligence gathering (commonly known as “OSINT”) used by law enforcement, the media, and the general public to identify individuals involved in the events of January 6, 2021, at the U.S. Capitol Building in Washington, DC. NOWHERE TO HIDE retraces the FBI’s investigative techniques – some using cutting-edge technology and others using old fashioned, knocking-on-doors detective work – used to pursue the hundreds of thousands of leads received from the general public. NOWHERE TO HIDE is filled with real world case studies, specific resources and practical “how to” guides to equip both beginner and seasoned OSINT investigators with the right tools for their OSINT toolboxes. This insightful volume includes 36 case studies that follow the FBI’s investigations of individual persons of interest, including the tactics, techniques, and procedures used by law enforcement, the media, and public sleuths to track down, identify, and – most importantly – verify the identities of suspected rioters. Learn how the FBI sifted through hundreds of thousands of leads, fa

Who reads NOWHERE TO HIDE: Open Source Intelligence Gathering - CASEBOOK: How the FBI, Media, and Public Identiified the January 6, 2021 U.S. Capitol Rioters?

Author

Daniel Farber Huang

Publisher

Independently published

Published

2022

Language

EN

ISBN

9788415462217

Category

nonfiction

Subjects

Engineering, Computer Technology, Stem