One of the biggest issues that marketers face today is problems with fraud, malware, viruses, and other issues. Whether it is their own devices or systems getting infected (which puts customer data at risk) or their customers getting infected and having issues buying products, it is a major problem. Of course, this type of issue also results in ad fraud, which costs businesses billions per year.
All of these issues fall under the umbrella of security concerns, and they are being addressed in a variety of different ways. One important tool being used in efforts to secure the web is machine learning. In the past couple of years there have been some significant advancements in this area, and many of them are being used specifically to watch for threats, and respond to them.
Ad networks, for example, are able to gather and analyze data much more quickly using advanced machine learning. This can either be done in-house, or by third party analytical firms that have the advanced systems in place and ready to go.
Another area where machine learning is pushing to protect the web is with Internet of Things devices. The IoT devices have been a known ‘weak point’ on the web since most of them don’t have much built in security. This has allowed hackers and other bad actors to use them to conduct large scale DDoS attacks.
Using machine learning, networks can identify inauthentic data coming from these types of devices, and have it dropped before it causes issues. The data gathered can also be used to better secure the devices through updates or other stapes that manufacturers can take.
There are a great many different ways that machine learning can help to protect the net, and marketers are just one group of people who will benefit from it now, and long into the future.
