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Cybersecurity is a field that makes good use of AI (and its closest brother, Machine Learning) to analyze data much more effectively. 

While their usage is leveraged in almost every industry, cybersecurity is one of those that need them with special care. 

AI and Machine Learning are those magic godparents who solve hard problems today and promises greater benefits in the future.

But not everything can be color pink. Let’s see how they’re used, and judge by yourself. 

How do AI and Machine Learning Work in Cybersecurity

These two technologies are far from being new. In fact, they were already a “thing” in the 50s. 

They’re intended to process and understand exaggeratedly large chains of data, very quickly. To a speed that exceeds a lot the human ability.

Incident response models (those used in Cybersecurity) focus on a 3-steps model: protect, detect, and respond. And the 2nd one (detect) is the hardest to perform. 

In this case, beyond the capability of human response, AI and Machine Learning tools would diagnose almost perfectly, when needed.

Although there’s a challenge to overcome here: billion of actions occurring at the same time are too much for humans to process and too hard for current tools to learn on their own. 

Of course, there are security analysts working to solve it. So far, the “supervised learning” (teaching machine learning system the difference between efficient work, to abnormalities) seems the closest solution they have.

Let’s see a few real-life examples:

The financial industry uses AI to make millions of trades per day without human interaction.

Big companies have been using it for 30 years to manage portfolios without many risks. 

And straight on the cybersecurity world, these technologies have improved the area of risk identification, to mention one. Including behavior-based support in real-time.   

Other applications: spam, phishing, and malware detection.

And of course, Microsoft’s Windows Defender is a great example of predictive analytics. It can stop malware attacks before it happens (in milliseconds).

Chronicle is another company implementing this tech to its entire IT defense line. It flags unwanted activity very fast.

These companies are huge and well-prepared. Is AI and Machine Learning also for yours?

AI and Machine Learning good for Cybersecurity? (Advantages)

There’s not a surprise to say that they’re highly-accepted and becoming adopted in every part of the world. 

Most organizations have found efficiency and its use, doesn’t matter the industry… 

But what type of benefits efficiency enters in? What are the Pros of adopting this tech?

  1. AI Data Processing  – The most obvious benefit is how automation saves huge resources when managing huge loads of daily data…. Especially beneficial when we talk about complex threats. How many human employees would be needed to check on millions of files and websites in 1 day? Or 1 fraction of a second?

  2. Algorithms Continue Learning – With the help of Artificial Intelligence and Machine Learning, cybersecurity teams can predict future issues from similar behaviors of the past. Getting ready with an early solution. Meaning, a scary number as million new malware attacks every month won’t mean too much, because it stays up-to-date with the latest, emerging threats. 

  3. No Duplication – The process of detecting threats is extremely repetitive and time-consuming. So, these algorithms can cybersecurity expert’s time to focus on upgrading important aspects of the same. 

It wouldn’t be a challenge to keep pointing at the real benefits that AI and Machine Learning represent to the Cybersecurity industry. 

Organizations have perceived a high improvement in the security staff efficiency – and executives (not only security managers) are the biggest advocates of its use. 

But what about the Cons of relying on AI and Machine Learning completely?

Are Machine Learning and AI BAD for Cybersecurity? (Disadvantages)

Everything looks nice and pretty up to this point…However, the use of AI and Machine Learning in cybersecurity is a two-way street. 

  1. Cybercriminals Can Use It Too – The good guys aren’t the only ones capable of using this technology. Imagine malicious AI, smart enough that’s capable of disguising… Stealing data at lighting-speed. Or a corrupting system, smart enough, to change the entire behavior of the cybersecurity team’s machine learning tool.

  2. Fairly Accurate – Cybersecurity teams new fully solutions before testing it out online. It wouldn’t be the first time where the market rush to capitalize on new technology, and overlook vital infrastructure. Human analysts are still required to detect major alerts, minimizing false positives.

  3. Expensive Tech – Reality is, there aren’t many AI/Machine Learning solutions available for small to mid-size cybersecurity teams. So not affordable yet.

I had to be the one to tell you there’s still a lot of work to do. 

They aren’t prepared for advanced threats, and would probably be vulnerable to exploits. 

Even when no breach happens, it may get false positives, and not every company has the budget to test inaccuracies.

Summary (Is AI good or bad for Cybersecurity?)

AI and Machine can save a lot of time to cybersecurity teams of experts, but they cannot completely replace them, yet.

There is good news, tho. Early stages have shown great potential. Meaning, the tech solutions of the future might isolate many of the internet threats we fear today. 

But that’s just you and me, talking about the future. What about the “now”? 

What you can do instead, is to have IT Cybersecurity experts watching your back, from all the incoming, wandering threats.

Are you going to act now?… Or will you wait to when is too late?

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