Most of us probably have asked Siri, Alexa, Google some questions and answers over the past years; Smart assistants are one of those new interactions. And honestly, not that many questions you asked were probably related to networks, were they? And yet, after hearing Juniper present at Security Field Day 3, these type of questions might in the near future become a normal way to allow you to interact with the network. Sounds like something from Star Trek, and is just science fiction? I beg to differ for a number of reasons. 

Before I dive into Juniper’s security strategy, let’s first review the current state of Artificial Intelligence (AI) and Machine Learning (ML) as a concept. To do that, I will explain what happens when you ask Siri to do something or a question like what is the date?.  

First of all, after you’ve asked the question, that audio bit (which is just a record of frequencies) is guessed into a sentence. It is a form of translation, where Machine Learning is used to do well-calculated guesses in what kind of word you tried to pronounce. And I can tell you that if English is not your native tongue, some weird word-guesses come out.

Once there is a digital sentence, another process is used to narrow down your digital sentence into a single pattern-matched result. This allows you to say things like “create a meeting on date X, Y or z”.
The model uses the pattern “create a meeting” for the match and the other values are stored in variables.

After a pattern has been matched, the code corresponding to that pattern is executed. The result of that code will be a string/sentence. That sentence is then being translated to audio using Text-To-Speech and read out loud to you.

This is a perfect flow for a single sentence / command /question. But many of these smart assistents start to show real issues once you start to create related questions, like you can do with a toddler.  And that is because the flow I described above does not have that much space for relaying context between flows. So most models in these smart assistents are built / designed for a single task, and if you put them in sequence, it appears as if the assistent is “smart”. But it is not (yet).

Yes, developments go fast, and I heard last year in San Jose a great story of self-learning models and also the core faults that are inside these models because of the way the models are designed and built. But that is a completely other discussion. 

But if AI/ML is not that far ahead yet, how would you then be able to ask Juniper about the security state of the network? That how is one of the things Juniper told at Security Field Day 3.

They leverage the power of AI/ML (and that is to have more answers than just a yes or now) in their security solutions for only a predefined, supervised, set of options. Juniper uses models (they call them supervised models) to analyse metadata about the flows in your network to detect malware and other anomalies in your network, just like other network and security vendors have done. Juniper has adopted AI/ML on detecting anomalies or other weird behaviour on your network. And that can help you a lot in gaining more visibility and control in your network.

Because with everything connected to the network, increased security by leveraging encryption, more data in the cloud, we as a human are reaching our limits in finding anomalies or odd behaviors by hand. A simple computer, using a properly tuned model, can find those anomalies much faster. And because that model does that, you can focus on determining whether that anomaly is really an anomaly of yet another new application on the network.

And if you would trust those reports blindly, you can of course automate actions, but personally I am always careful with those. Suppose it is the CEO’s smartphone, you might want to call the CEO first before you throw him off the network.

Personally I do believe firmly in that AI/ML can help you in your daily job in finding those odd behaviors that without them you’d never be able to spot and help you in providing a better, smoother, more stable and secure network. But you do need to keep in mind that it is still a computer that presents you information from a lot of data and that presentation will be biased.

But definitely a good thing that Juniper has started to embrace that principle across their portfolio. 
That can bring them quite a bit.