How Can Data Science Solve Cybersecurity Challenges?

Software Engineering Institute (SEI) Webcast Series

A tartalmat a Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

2+ y ago 1:00:01

MP4•Epizód kép

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

170 epizódok

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