Cloud-Based Machine Learning: A New Approach to Security

We live in a world where the internet handles more and more of our processes. From banking to entertainment, our current society lives and breathes on the internet. Because of that, there has been a significant spike in the number of hackers and other cybercriminals looking to make an easy buck by stealing what doesn’t rightfully belong to them. Does that mean we need to use the internet less?

No, it doesn’t. Instead, we need to find new ways to protect our data online, which is where machine learning and cloud computing come into play. The concept of machines learning to do something better than humans is not new, but applying it to this field is a fresh idea. That’s why we’ve put together this guide going over how cloud-based machine learning is a new approach to security.

What Is Machine Learning?

If you haven’t already learned about the concept of machine learning and what it can do, we’ll start there. In the same way that humans learn more about the world as time passes, computers can do the same thing, albeit in a slightly different way.

A person gives the system inputs with which it can analyze and find patterns. Once it has discovered recognizable patterns, it can then use that knowledge to find other instances of the same thing. This technology has nearly perfected processes such as facial recognition and shopping recommendations, and now it’s time to expand it even further.

How Will It Improve Security?

The latest application for machine learning is online security. Internet threats are everywhere, and our standard forms of online protection are having trouble keeping up. The human limit can only take us so far, which is why we need to put our trust in computers to keep us safe from hackers and bots. Tech wizards have already accomplished this by effectively battling spam emails and messages.

Since machine learning has cracked the code for those basic internet threats, it’s time to tackle some bigger ones. The current challenge online security faces is that every time we find a vulnerability and patch it, new ones pop up. Firms specializing in online protection are still proficient at shutting these down before they become an issue. Still, most groups don’t have the capacity to keep up with their internet defenses continually.

On the other hand, computers have nothing but time and can work much faster than humans. Using machine learning, they can identify and patch threats at a much quicker pace. If you can dedicate a percentage of your processing power to a task like this, you could theoretically solve the issue.

Does It Have Issues?

Of course, that’s an ideal scenario. Unfortunately, as great as machine learning is, it’s not a perfect system. In the same way that a person can mistake a random person at the supermarket for someone they know, computers can also make errors. That means hackers occasionally slip by the system. Even worse, sometimes people who should be allowed entry get blocked out by the computer. While these problems are subsiding year after year, expecting perfection is a little far-fetched.

That’s why you need to combine your machine learning system with existing ones. Your IT team will still need to work hard to ensure that the computer system isn’t making any mistakes. You can also use the security systems you already had as a backup for the machine learning one. Regardless of the other techniques you use, you should never let a computer-based one run on its own without periodic checks to make sure it’s running properly.

How Can the Cloud Help?

While this is all good to know, it’s time to cover the cloud portion of this guide on how cloud-based machine learning is a new approach to security. Since all machine learning programs need a data set to begin the process, why not start with a system built for processing data in huge quantities? Cloud servers will allow computers to learn at a much faster rate due to the raw processing power they possess.

This will take a method that’s already fast and speed it up to levels some thought to be impossible. This ability would be invaluable to security systems, making it even harder for hackers to abuse vulnerabilities. With a system like this, issues would get patched up before anyone could take advantage of them.

Plus, the cloud’s design allows for easy connection to any other system that uses the internet. Companies can spread this type of security to other groups. Unless a company owns its own server farm, achieving this level of cloud-based machine learning isn’t possible on an individual scale.

Where Will This Be Used?

Once this idea takes off, theoretically, anybody could use it. From large corporations to individual users, cloud-based machine learning could become the online security gold standard. For the time being, though, cloud service companies will likely be the primary users of this type of program.

Cloud providers need to have the best security on the market due to the amount of important data they store within their servers. Atmosera is no exception. We put our all into Microsoft Azure’s security and compliance methods because we want to ensure that our users have full protection when using our services.

As cloud-based machine learning becomes more widely adopted, all cloud providers will eventually offer it in some capacity. We’ll stay up to date on technological developments to ensure that ours is always the best option.

Who knows? By the time this system becomes fully integrated, our best minds might discover something new that is even better for our ongoing fight with online threats. Whatever security developments surface next, you can be sure that we’ll be at the forefront, learning more and applying the new system when the time is right.

Cloud-Based Machine Learning: A New Approach to Security

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