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Digital security is a greater concern in 2019 than ever before. Over the years, cybersecurity experts have come to a hard truth. They have recognized that password protection alone is inadequate for many applications. They need more sophisticated ways to authenticate users. Fortunately, machine learning is providing some new solutions to this challenge. It can evaluate a number of factors, including dynamic keystroke patterns of users.

Machine learning approaches to user authentication are proving to be especially useful for mobile applications. This is one of the many things that developers must think of when they are trying to decide how to build a social media app. There are too many mobile security risks these days including:

The risk that mobile devices can be stolen and breached
A growing number of password crackers give hackers access to mobile applications remotely
Trojan software can infiltrate mobile apps and hijack the users’ account

Traditional authentication systems are inadequate for handling these threats. Machine learning is filling the void by offering more comprehensive protections.

How is machine learning improving the effectiveness of user authentication?

CSO Online reported that the same types of machine learning algorithms that have been used by financial services companies are now being employed by mobile application platforms. …

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