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Innhold levert av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
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How Can Data Science Solve Cybersecurity Challenges?

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Manage episode 359344658 series 1264075
Innhold levert av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.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

174 episoder

Artwork
iconDel
 
Manage episode 359344658 series 1264075
Innhold levert av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.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

174 episoder

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