Privacy-Aware Identity Cloning Detection Based on Deep Forest

We propose a novel method to detect identity cloning of social-sensor cloud service providers prevent the detrimental outcomes caused by deception. This approach leverages non-privacy-sensitive user profile data gathered from social networks and powerful deep learning model perform cloned detection. evaluated proposed against state-of-the-art detection techniques other popular deception models atop real-world dataset. The results show that our significantly outperforms these techniques/models in terms Precision F1-score.