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Contenido proporcionado por Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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How Can Data Science Solve Cybersecurity Challenges?

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Contenido proporcionado por Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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 episodios

Artwork
iconCompartir
 
Manage episode 359344658 series 1264075
Contenido proporcionado por Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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 episodios

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