A major factor contributing to this amount is the proliferation of account takeovers. Luckily, there are steps you can take in order to detect this type of activity before it's too late.
Not sure where to start? Don't worry, we’ve got you covered. Let's take a look at everything you need to know about using machine learning to prevent this scenario.
As the name suggests, an account takeover involves an unauthorized party getting access to a user's account and using it for malicious purposes.
For example, a hacker might obtain login information for a user who has an account with a clothing brand. They might then use the customer's stored credit card information to make as many purchases as possible before their activity is discovered.
It should come as no surprise that this type of scenario can easily become catastrophic for both the business involved and the affected user.
As previously mentioned, machine learning is an effective tool that can be used to combat an account take over. In many cases, it can prevent damage from being done as soon as the account becomes compromised.
Let's explore a few of the most noteworthy ways it can do so.
Legitimate users and hackers behave extremely differently. The average user will scroll through a website, browse products, and perhaps read reviews before making a purchase.
Someone who compromises another user's account will immediately rush to add as many products to their cart as they can within a short period of time. Machine learning is able to detect this behavior and send an alert so that the hacker's activity is brought to light.
Since machine learning involves the utilization of advanced software, it's highly efficient at his job.
This means that it can detect certain behaviors instantly, allowing you to take action as quickly as possible. For example, machine learning software could discern that an account has been compromised if there's a login from an unfamiliar IP address accompanied by an immediate password change.
One of the most effective ways that machine learning can detect an account takeover is by cross-referencing past user data with current activity. For example, if a user always ships to a particular address and only makes occasional orders, it's highly suspicious for them to place a large volume of orders that are shipped to a different state.
Combined with the other utility that machine learning provides, this type of software makes it virtually impossible for a takeover to go undetected.
But it doesn't have to be.
With the above information about how machine learning can handle account takeovers in mind, you'll be well on your way toward ensuring that you protect yourself as efficiently as possible.
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