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In the last decades, Social Networks (SNs) have deeply changed interactions and habits of the users that are also prone to create more than one profile on the same SN. On the flip side, fake profiles (i.e., impersonating profiles), have become a considerable problem in digital investigations. In this paper, we propose a method for user profiles resolution through a cluster-based approach of the smartphone fingerprints extracted from the images being posted on SNs. The proposed method is thus able to detect fake profiles. To evaluate our approach, we use a real dataset of 1,500 images from 10 different smartphone devices and Facebook and WhatsApp platforms. The results show that the average of sensitivity and specificity for user profiles resolution is about 98%.
Rouhi et al. (Mon,) studied this question.
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