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How Can Data Science Solve Cybersecurity Challenges?

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Manage episode 359344658 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this webcast, Tom Scanlon, Matthew Walsh and Jeffrey Mellon discuss approaches to using data science and machine learning to address cybersecurity challenges. They provide an overview of data science, including a discussion of what constitutes a good problem to solve with data science. They also discuss applying data science to cybersecurity challenges, highlighting specific challenges such as detecting advanced persistent threats (APTs), assessing risk and trust, determining the authenticity of digital content, and detecting deepfakes.  

What attendees will learn:

  • Basics of data science and what makes for a good data science problem
  • How data science techniques can be applied to cybersecurity
  • Ways to get started using data science to address cybersecurity challenges
  continue reading

151 episodes

Artwork
iconShare
 
Manage episode 359344658 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this webcast, Tom Scanlon, Matthew Walsh and Jeffrey Mellon discuss approaches to using data science and machine learning to address cybersecurity challenges. They provide an overview of data science, including a discussion of what constitutes a good problem to solve with data science. They also discuss applying data science to cybersecurity challenges, highlighting specific challenges such as detecting advanced persistent threats (APTs), assessing risk and trust, determining the authenticity of digital content, and detecting deepfakes.  

What attendees will learn:

  • Basics of data science and what makes for a good data science problem
  • How data science techniques can be applied to cybersecurity
  • Ways to get started using data science to address cybersecurity challenges
  continue reading

151 episodes

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