Fake Profiles Identification on Social Networks With Bio Inspired Algorithm

People are attracted to social media platforms all over the world, for example Facebook or Twitter. Even so, the more frequently these social networks are used, the more security, integrity and confidentiality issues arise. Now, and more than ever, it important to make sure of following the right account or dealing with a real consumer on any online social network, to avoid dangerous and harmful situations. This paper proposes an approach for detecting fake profiles on social media. This approach is based on hybridization between a machine learning algorithm and a bio inspired algorithm. To detect fake profiles, the proposed approach makes use of a dataset from Facebook social network. The hybrid approach consists of two stages. The first stage is to use Satin Bowerbird Optimization algorithm which assures us of finding the best bower, which is used in stage two as an initial centroid within k-means clustering algorithm, that make sure of accurate profiles types detection. When the outcomes of the suggested method are contrasted with well-known machine learning algorithms, it outperforms them.