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2018: The Year Machine Intelligence Arrived in Cybersecurity
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Dr.T
Dr.T,
User Rank: Ninja
12/27/2018 | 11:39:43 AM
Speed
“What machine learning has really given us is the ability to predict patterns before they actually happen” I think this is the important aspect of AI in cyber security, the speed.
Dr.T
Dr.T,
User Rank: Ninja
12/27/2018 | 11:41:31 AM
Probabilistic
"The best use of AI is to give security admins the ability to deconflict tasks – to know which, out of scores of possibilities, are critical and will have the greatest impact," This makes sense. AI is probabilistic, not deterministic. So someone should intervene at one point.
Dr.T
Dr.T,
User Rank: Ninja
12/27/2018 | 11:43:04 AM
False positives
“Microsoft sees 6.5 trillion security signals a day. AI helps rationalize them down to a quantity that humans can deal with” Yes. This helps us avoiding false positives.
Dr.T
Dr.T,
User Rank: Ninja
12/27/2018 | 11:44:55 AM
Big data
“Machines are really good at looking at vast amounts of data and making sense of it all in a statistical way, and humans are not“ That makes sense. Humans are not equipped for big data, we need AI help to deal with it.
Dr.T
Dr.T,
User Rank: Ninja
12/27/2018 | 11:47:16 AM
Humans and AI
“we're a long away from totally automating out the need for some type of security professional that occasionally has to make a decision." I would agree. Currently decision of action would still require humans in most scenarios.
Joe Stanganelli
Joe Stanganelli,
User Rank: Ninja
12/31/2018 | 10:39:05 PM
Re: Big data
@Dr. T: That's the very definition of big data: data collections that are so big that humans unaided by tech automation cannot possibly contend with them.

The real question, however, is to what extent actual ML and AI are necessary for this. Terrific analytics advances have been made -- but hurdles are still left to be overcome.
Joe Stanganelli
Joe Stanganelli,
User Rank: Ninja
12/31/2018 | 10:42:13 PM
Re: Probabilistic
> AI is probabilistic, not deterministic.

Is it, though? I mean, sure, modern ML programming relies on PPLs, but we have not reached true/generalized AI yet. Perhaps AI models will evolve such that some are more deterministic in nature.

Or maybe I'm overthinking this.
Joe Stanganelli
Joe Stanganelli,
User Rank: Ninja
12/31/2018 | 10:44:24 PM
Re: False positives
@Dr. T: In security studies, security-alert fatigue is routinely identified as the top or near-top obstacle facing security teams.

AI/ML can help, but you can also accomplish a lot by trying some lower-tech techniques (like banning all non-whitelisted bots, for instance).
Curt Franklin
Curt Franklin,
User Rank: Author
1/2/2019 | 10:54:52 AM
Re: Probabilistic
Joe, my understanding is that AI can be deterministic, but it's capable of being deterministic in ways that the developer didn't anticipate. Where machine learning is great at reaching rapid conclusions within a known population of answers, AI should be capable of "thinking outside the box" and finding correlations (and therefore, conclusions) that are outside any previously anticipate answers.

That's a much tougher thing to develop, and why most of the AI researchers I've talked to say that what we're seeing in security (and most of commercia computing) today is correctly classified as ML rather than AI.
Joe Stanganelli
Joe Stanganelli,
User Rank: Ninja
1/8/2019 | 7:01:24 PM
Re: Probabilistic
@Curt: Yep. When you press even the most gung-ho "We offer AI!" marketers, they will admit that, no, they really don't -- at least, not generalized AI (a.k.a. "true AI", as we tend to think of it).

Unrelatedly, I really dig the drawn portrait that is your avatar. Florida artist?


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