What Is Machine Learning?

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What do self-driving cars and interactive speakers have in common? Both utilize something called “machine learning.” This is when we give systems access to data that enables them to identify patterns and improve their performance, or “learn”, without human programming.

Machine learning is often confused with artificial intelligence (AI), where machines and applications mimic human behavior. Although they often work together, machine learning takes human-like behavior one step further—it enables systems to get smarter as they gain more information. This is why your Alexa speaker, for example, can make recommendations based on what you’ve said in the past.

To do this, computer systems need access to enough digital information to analyze, classify, and store information, and then make predictions. This is where the internet comes in. Even though the term “machine learning” was coined in 1959 by British AI pioneer Arthur Samuel, it wasn’t really possible until the internet was mature enough to provide access to rich data.

But now, machine learning is allowing us to talk to devices like they are human, monitor our health, make personalized recommendations, and even improve our online security. Take, for instance, the fact that Google says it has been using machine learning to help reduce security issues in its Play store. The company said that in 2017 some 60.3% of potentially harmful apps were detected using machine learning incorporated into Google Play Protect.

What’s more, some security developers are using the technology, coupled with AI and game theory, to figure out potential vulnerabilities and patch them before hackers exploit them. And researchers are looking into adding machine learning and sensors to power grids to detect and analyze potential cyber attacks, as well as make the grids themselves more efficient.

But these smart technology advances could also go the other way. Security researchers believe that cybercriminals will soon be using the same techniques to search for new entry points and means of attack. This is concerning given that each day the world is becoming more connected, giving the bad guys a multitude of ways to access our devices and critical information.

While many believe that machine learning will make our lives more convenient, by allowing technology to do many of the tasks that only humans could previously do, it’s also important to be aware of the risks. After all, technology that mimics intelligent humans can also enable malicious ones.

Here are some tips for using smart technologies safely:

  • When investing in new internet-connected devices, choose products with built-in security features
  • Change the default password on new devices as soon as you can, since cybercriminals know many of these default passwords.
  • Don’t let a program or device access more information than it needs to function properly. Take a careful look at permissions to determine whether your personal information is at risk.
  • Keep your connected-home devices on a secure network, preferably separate from your main computer network. This way, if one device is infected with malware it can’t spread to other data-rich devices. Check your router’s user manual to learn how.
  • Always use comprehensive security software, and consider investing in a secure home network that makes it easier to protect all your computers and devices from emerging threats.
  • Keep up-to-date on the latest technologies and potential threats. This will help you be more proactive when it comes to keeping your digital life secure.

Looking for more mobile security tips and trends? Be sure to follow @McAfee Home on Twitter, and like us on Facebook.

Categories: Consumer Threat Notices
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