Can Machine Learning Ensure Better Smart Home Security?

Should we be worried about the security of smart homes?


Nearly everybody knows what smart homes are, but only 26% of people appear to be interested in living in one. What’s the deal? Who wouldn’t want to live in one of those futuristic homes that were once depicted in childhood cartoons and sci-fi movies? As it turns out, a fair number of the people who said they would abstain from life in a smart home are concerned with security and data privacy.

So, what can be done to improve confidence in smart homes? One solution might be machine learning. Keep reading to learn more.

The IoT: Growth And Growing Pains

Did you get an Alexa for Christmas, or one of those thermostats you can control from your phone? You aren’t alone. The IoT is growing. In fact, predictions are that the industry will surpass 1.7 trillion dollars in potential revenues by the time 2020 rolls around. That’s a lot of connected devices, and a lot of data being passed around. There’s also a lot of potential for criminals to exploit that data.

In fact, just last year, it was discovered that Samsung had difficulty maintaining security over the data it received from smart homes.

How Big Data And Machine Learning Can Help

By harvesting data through a variety of platforms, it is possible to gather sample sizes that are large enough to be useful. Through the use of machine learning, systems can access that data, learn to recognize patterns, and thus become smarter when it comes to recognizing security threats. Until recently, this wasn’t possible. Individual devices from various manufacturers simply didn’t make up enough data to educate machines.

Other Risks And Opportunities.

Of course, this doesn’t completely mitigate all security risks related to smart homes. There is a major component of all of this that involves users. If homeowners don’t follow basic security protocols, for example, no amount of machine learning is going to keep their data safe. This includes:

  • Keep apps updated to ensure that security patches are installed
  • Register IoT Devices with the manufacturer
  • Use strong passwords
  • Make sure home routers are secure
  • When purchasing used devices contact the manufacturer to ensure that registration information is transferred
  • Disconnect devices when they aren’t in use

Another simple technique that people don’t consider is to simply reboot their devices.

Of course, companies have a role to play as well. Using improved encryption technologies for one thing will be very important going into the future. Of course, the real trick could be in what was mentioned above.

Machine learning works when data is shared. Likewise, when companies work together to share information, experiences, and technology breakthroughs related to keeping devices and the data they transmit and receive safe from hackers.

Another option is to modularize as many IoT components as possible and to communicate only the information that is absolutely needed between the systems. This way, if one piece of software becomes infected in some way, or hackers find a vulnerability, the damage that they can do is limited to that particular module. This also makes testing and auditing easier.

There is no doubt that machine learning will play a role in creating smart home technology that is more secure. However, there is much more to it than that. Home owners and users, data scientists, manufacturers, and IT security experts must all continue to modify their behaviors and work towards balancing the ‘wow’ factor of IoT with data security. Once this happens, the number of people who are willing to adopt these new technologies will certainly grow.


Read next:

Why Blockchain Hype Must End