Daniel William is content director and a cyber security consultant at IDStrong
With the Big Data gathering precious information, and us leaving our digital footprints all over the internet, it appears that hackers have their hands full. Only in 2018, there were over 3 million identity theft cases in the US. In 25% of them, the amount of money was lost.
Machine learning and AI have benefited our lifestyle in many ways. Preventing identity theft is one more way they have improved our lives. Let’s take a look at some examples of how machine learning aids cyber security and prevents data breaches.
Before we delve in into the digital world, we’ll deal with more tangible matters. Driver’s licenses, passports and ID cards are still objects of fraudulent activities.
While an untrained eye may not notice the difference, authentication tests can spot the fraud right away. For example, microprint tests, facial recognition, OCR-barcode-magnetic stripe cross verification, and paper-and-ink validation raise security levels. By analyzing this data and comparing it to an unknown database it is possible to detect a con artist timely.
Besides training a team about today’s cybersecurity measures, it is necessary to equip the team with the right security software. They can be on the pricey side, but with the hackers raising their game every day, installing maximum protection is vital. Also, in the long run, investing in new software is cheaper than hiring an extra IT specialist.
The software helps with detecting and rejecting potential threats, protects the company’s and clients’ data, along with the application system. Half a billion personal records were stolen in 2018, according to statistics. Fortunately, a good modern identity protection service is much more than an anti-virus tool.
While we are using our computers or mobile phones, we tend to carry out a lot of similar tasks, day after day.
Thanks to machine learning, these algorithms are recognized from a multitude of input and output data. Consequently, it is possible to set off an alarm if behavior is noticed that does not follow the familiar pattern.
What is wonderful about machine learning is the fact that it’s not used just for rejecting threats, but it’s going into the enemy’s territory, so to speak. Machine learning is used by experts to collect information about potential breaches in advance.
By monitoring channels in the dark web one can detect the exchange of information among hackers, just like they try to monitor exchanging data by their potential victims. Thanks to machine learning, it’s possible to move from protection to prevention.
Last but not least, one of the best things about machine learning and IT is that they resolve problems in real time and are available 24/7. The right software never gets tired of data analysis.
Admittedly, for the prevention of identity theft, it is obligatory to be up to date and take advantage of the latest solutions provided by machine learning and AI. Only in that way can we be one step ahead and avoid all the issues that may occur with identity theft.
Author bio: Daniel William is content director and a cyber security consultant at IDStrong. His great passion is to maintain the safety of the organization’s online systems and networks. He knows that both individuals and businesses face the constant challenge of cyber threats. Identifying and preventing these attacks is a priority for Daniel.
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