Archived Webinar: Using Machine Learning to Stop Malware 

 

Tuesday, 29 August 2017
12 pm (EDT) / 11 am (CDT) / 9 am (PDT) / 16:00 (UTC)
60 minutes
1 CPE (Members only)


An experienced, well-trained human eye can spot malware, usually by recognizing features it shares with other known-malware. But how do we teach machines to recognize malware on their own? Especially as threats become faster than ever, change disguises, and piggyback behind clean applications? Enter machine learning. In this webcast, we’ll explore exactly how machine learning works, how we can teach machines to recognize all forms of malware, and why it’s important to do so.

Robert Leong, Director of Product Management at Intel Security,
McAfee

As director of product management within McAfee Labs, the R&D arm of McAfee, Robert Leong is responsible for product management of innovation technologies and threat landscape research, with emphasis on client platform technologies. Robert attended MIT, where he earned simultaneous BS/MS degrees in electrical engineering and computer science. His early career began with designing custom ICs and circuit boards, as well as co-founding an enterprise security company. Leong has been in enterprise security since 2007 and with McAfee since 2014.