A novel machine learning-based framework for detecting fake Instagram profiles

Publication Name

Concurrency and Computation: Practice and Experience


Recently, there has been a massive rise in the popularity of Instagram, which connects individuals globally and allows videos and images to be uploaded and exchanged, and communicated over social media. Instagram is also an online playground of deceit. The use of filters, lighting, and cunning angles transforms the mundane into something spectacular. Automated spam accounts and fake profiles use this to their malicious advantage for executing attacks targeting high-profile executives. Creating fake Instagram identities is easy to reproduce the idea of being accepted by many fans on social media. Fake accounts are used in the marketing of fake services and products. This research focused on designing and training a unique neural network model and proposed a new algorithm for detecting automated spam and fake Instagram account profiles. The precision and accuracy of the proposed method were achieved at 93% and 91%, respectively.

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