Abstract
In recent years, the spread of smartphones has attributed to changes in the user behaviour with respect to multimedia content sharing on online social networks (SNs). One noticeable behaviour is taking pictures using smartphone cameras and sharing them with friends through online social platforms. On the downside, this has contributed to the growth of the cyber crime through SNs. In this paper, we present a method to extract the characteristic fingerprint of the source camera from images being posted on SNs. We use this technique for two investigation activities (i) smartphone verification: correctly verifying if a given picture has been taken by a given smartphone and (ii) profile linking: matching user profiles belonging to different SNs. The method is robust enough to verify the smartphones in spite of the fact that the images get downgraded during the uploading/downloading process. Also, it is capable enough to compare different images belonging to different SNs without using the original images. We evaluate our process on real dataset using three different social networks and five different smartphones. The results, show smartphone verification and profile linking can provide 96.48 % and 99.49 % respectively, on an average of the three social networks, which shows the effectiveness of our approach.
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Acknowledgments
This work has been supported in part by the Italian Ministry of Education, Universities and Research IMPACT project (RBFR107725) and OPLON project (SCN_00176).
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© 2015 Institute for Computer Sciences, Social informatics and Telecommunication Engineering
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Bertini, F., Sharma, R., Iannì, A., Montesi, D. (2015). Smartphone Verification and User Profiles Linking Across Social Networks by Camera Fingerprinting. In: James, J., Breitinger, F. (eds) Digital Forensics and Cyber Crime. ICDF2C 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 157. Springer, Cham. https://doi.org/10.1007/978-3-319-25512-5_12
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DOI: https://doi.org/10.1007/978-3-319-25512-5_12
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