How Can Data Science Solve Cybersecurity Challenges?

Software Engineering Institute (SEI) Webcast Series

Контент предоставлен Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Весь контент подкастов, включая эпизоды, графику и описания подкастов, загружается и предоставляется непосредственно компанией Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff или ее партнером по платформе подкастов. Если вы считаете, что кто-то использует вашу работу, защищенную авторским правом, без вашего разрешения, вы можете выполнить процедуру, описанную здесь https://ru.player.fm/legal.

2+ y ago 1:00:01

MP4•Главная эпизода

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

174 эпизодов

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