How Machine Learning Helps Fight Email Phishing?

Fortunately, although phishing techniques are constantly developing, detection methods are advancing just as quickly. Confrontation from attackers will persist as long as their attempts are profitable.

Fromont, CA:Phishing remains one of the most fraudulent tricks that can be found in malicious email traffic. In this type of attack, a recipient will receive an email, for example, disguised as a message from a well-known company that requires them to follow a link and login to a service or enter bank card details on a fake web page.

In 2019, Kaspersky’s anti-phishing system identified 467 million attempted transitions to phishing websites. Nearly one-in-seven of our users has faced this threat.

Fortunately, although phishing techniques are constantly developing, detection methods are advancing just as quickly. Confrontation from attackers will persist as long as their attempts are profitable. Therefore, phishing protection mechanisms must work to decrease the response time to new scam techniques to make attacks as unprofitable as possible.

How Phishing has developed and how to spot it

Around 10 years ago, manually-created dictionaries were used to detect phishing in e-mail traffic. They listed all possible variants that may be included in the phishing text. Later, heuristics began to appear in the arsenal of detection technologies. Heuristics means looking for signs that suggest the essence of a message and how it could be harmful.For instance, if there is a connection in a malicious email, the indicator may be an unprotected protocol such as http instead of https or the recipient's email being present within the link. Another common sign is that the message seems to have been sent from a well-known organization.