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Facebook Flaw Generates Mores Than 100 Million Fake Likes !!!

Facebook Flaw Generates Mores Than 100 Million Fake Likes

The popularity of a post on Facebook is determined by the number of likes, shares, reactions, and comments received by it. If that post is video-based, it gets a special treatment. Apart from that, if the rate at which a post is liked or shared is high, it’s more likely to turn out to be a more popular post.

The researchers at the University of Iowa and the Lahore University of Management have found that the same factor has been exploited to gain fake Facebook likes. According to the study (Via: Fortune), at least 1 million fake and real Facebook accounts have gained at least 100 million likes by taking part in a “collusion network.”
A collusion network is a large-scale manipulation service on Facebook that collects OAuth access from its members and abuses them to generate fake Facebook likes for its members. As a result, the participants of the collusion network get likes at a rapid pace and get more attention on the social network.
The researchers were able to uncover this flaw in Facebook’s OAuth access tokens by deploying honeypots. They created honeypot Facebook accounts, joined collusion network, and used them to get likes and comments on the honeypot posts. After that, the honeypots were analysed to understand the intricacies of such networks.

The membership size of a network was identified by tracking the number of unique accounts that liked the honeypot posts. It was estimated that the networks had memberships up to 295K for hublaa.me, which is followed by 233K for official-liker.net.

This study is also significant as it was conducted in the wake of 2016 US Presidential Elections. Many people are claiming that the results of the elections were impacted by the Facebook fake news.

In May 2016, Facebook was made aware of the fake Facebook likes and countermeasures were taken. These measures were in place until April 2017, after which a new set of changes were implemented to tackle with collusion network.