At RSA 2017, there are no shortage of companies claiming various usages of artificial intelligence (AI) and machine learning (ML). Some are new to the party. Others are old dogs insisting this is not a new trick for them. Many are making legit claims, but in fact they are using AI or ML in ways that do not move their level of protection beyond what traditional antivirus companies already achieve using legacy technology.
Want to find out who is legit and who is just jumping on the AI/ML bandwagon? Watch our video and learn how Cylance built a native-born artificial intelligence and stirred up the cybersecurity industry:
VIDEO: Cylance VP Bryan Gale Speaks on AI and the Me-Toos
Bryan Gale is a VP at Cylance. Here’s what he has to say on the subject of AI and ML in the antivirus (AV) industry.
Enthuses Gale, “Most of us (here at Cylance) come from a rich heritage background of AV companies, and we all know what the product is doing on the backend. Many of the traditional players may indeed be using ML at this point, but really, all they’re doing is using it to create signatures more efficiently.”
Cylance was born different, claims Gale. But why does that matter? For starters, he says, the company was founded based on the premise that AI and ML could be used to make the primary convictions on the endpoint itself.
“We don’t use any other kind of detection engine, or detection technologies,” explains Gale. “We don’t use heuristics, we don’t use behavioral rules, and we don’t use signatures. Everything is done autonomously on the endpoint, through our machine learning model that has been essentially miniaturized.”
How Cylance is Different
There are plenty of other benefits of using AI and (Read more...)
This is a Security Bloggers Network syndicated blog post authored by Matt Stephenson. Read the original post at: Cylance Blog