Dr. Aqib Rashid

We intended to prove out that you could use CDR telemetry.

So that is the structural telemetry that you obtain as a result of cleaning files and analyzing files and using that kind of data to build machine learning models.

So we wanted to first prove out that end-to-end process.

Some researchers in the past had proved that it could work to some degree, but there was room for improvement in the performance there.

So effectively, the MVP there became, let's first understand which bits of telemetry, if any, can be used for this process.

If so, how good can we get this?

I'm Dr. Akim Rashid.

I am the Applied AI Lead at GlassWall.

There's nothing on the back end.

GlassWall is a company that has existed for a couple of decades now, actually.

It's a cybersecurity company based in the UK and the US.

And the expertise that our company has built up over time is around a technology known as content disarmament reconstruction.

I don't need to describe too much the phenomenon of malware and malicious actors trying to get into your system and wreak havoc in your corporate network or wherever it might be.

And one way that they typically do that is through files.

So that could be PDF files, it could be office files.

And of course, files are...

the lifeblood of an organization, whether it's sent over email or Slack or whatever it might be.

And what you'll find is that traditional cybersecurity technologies, when they try to detect whether particular files are malicious, they invoke signature-based detection, they invoke some kind of heuristics.

Your traditional AV will do a decent job of detecting malware.

But in certain situations, in certain environments, all you want is a clean and pristine file and you can't tolerate malware at all.