Crackdown on Fake LinkedIn Profiles
People have been turning to LinkedIn since 2002 as a way to develop their network of business contacts. The professional social networking site has 645 million users in over 200 countries and territories around the world, who spend an average of 17 minutes on the site per month.
While using LinkedIn may be preferable to eating stale croissants and swapping business cards at yet another networking breakfast event, it has one major downside: fake profiles.
Fake profiles are typically characterized by poor spelling and grammar, a lack of engagement, a limited number of connections and a suspicious or incomplete work history.
It’s also not unusual for the photo in a fake profile to depict someone who, if they were really that good looking, would be making a living from modeling underwear on a beach somewhere rather than heading up a small HR team at a recruitment firm in Croydon.
The faux profiles, which are often duplicated, are used to contact genuine professionals to fish for information such as how to get hired at a particular company. Spam of this type can be a frequent and extremely irritating problem for executives bugged daily by multiple connection requests from fake profiles.
LinkedIn is aware of the problem and has been making a concerted effort to rid the site of its pretenders.
Paul Rockwell, LinkedIn’s head of trust and safety, said: “Our teams are working to keep LinkedIn a safe place for professionals by proactively finding fake profiles then removing them and any content they share. Between January and June 2019, we took action on 21.6 million fake accounts.”
LinkedIn managed to prevent 19.5 million fake accounts from being created by automatically halting the registration process. The other 2 million fake accounts were restricted after the company paired human review with AI, machine learning and reports of fake accounts made by genuine members.
Automation plays a key part in LinkedIn’s defense against the incoming wave of fakers. According to Rockwell, automated defenses, including AI and machine learning, prevented or took down 98% of all fake accounts. The rest were captured through manual review.
Rockwell said: “When we stop fake accounts, we start more chances for economic opportunity."
Source: Information Security Magazine