How Can Data Science Solve Cybersecurity Challenges?

Software Engineering Institute (SEI) Webcast Series

Treść dostarczona przez Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

2+ y ago 1:00:01

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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

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#Tech #Cybersecurity #Securecoding #Softwarearchitecture #Softwaredevelopment #Softwareengineering #Carnegie Mellon University Software Engineering Institute #SEI Members of Technical Staff #Video #Podcasting Education