Categories: learning materials

AI for OSINT – part 1 – Progress

Open Source Intelligence (OSINT) is about using openly available information to extract insights.

Governments, for example, utilize OSINT sources for different purposes such as national security, counterterrorism, cybertracking of terrorists, understanding domestic and foreign public views on different subjects, supplying policy makers with required information to quantities of data on the Internet.

OSINT analysts are good at finding and preventing threats to organizations. But they are only human. On the other hand, AI can scour the huge swaths of available information at a rate greater by several orders of magnitude and extract statistical insights using its tremendous computational ability that we humans cannot. In this series of blog posts, I am going to discuss recent advances in AI’s use for OSINT:

 

Areas of Significant Progress

 

  • Monitoring the Dark Web and hacker forums for upcoming threats
  • Monitoring Social Media, such as Facebook, Twitter and YouTube
  • Identity and demographic recognition from video, image and audio footage

 

In the next 3 blog posts, I will elaborate on each of these topics.

Dr. Emmanuel Tsukerman

Award-Winning Cybersecurity Data Scientist Dr. Tsukerman graduated from Stanford University and UC Berkeley. In 2017, his machine-learning-based anti-ransomware product won Top 10 Ransomware Products by PC Magazine. In 2018, he designed a machine-learning-based malware detection system for Palo Alto Network’s WildFire service (over 30k customers). In 2019, Dr. Tsukerman authored the Machine Learning for Cybersecurity Cookbook and launched the Cybersecurity Data Science Course and Machine Learning for Red Team Hackers Course.

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