Image Manipulation on Facebook for Forensics Evidence

  • Marco MoltisantiEmail author
  • Antonino Paratore
  • Sebastiano Battiato
  • Luigi Saravo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)


The growth of popularity of Social Network Services (SNSs) opened new perspectives in many research fields, including the emerging area of Multimedia Forensics. In particular, the huge amount of images uploaded to the social networks can represent a significant source of evidence for investigations, if properly processed. This work aims to exploit the algorithms and techniques behind the uploading process of a picture on Facebook, in order to find out if any of the involved steps (resizing, compression, renaming, etc.) leaves a trail on the picture itself, so to infer proper hypotheses about the authenticity and other forensic aspects of the pipeline.


JPEG Compression Social Network Service JPEG Image Image Manipulation Forensic Evidence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Battiato, S., Moltisanti, M.: The future of consumer cameras. In: Proceedings of the SPIE Elecronic Imaging, Image Processing: Algorithms and Systems XIII, PANORAMA special session, San Francisco, California, USA, February 8–12 (2015)Google Scholar
  2. 2.
    Jang, Y. J., Kwak., J.: Digital forensics investigation methodology applicable for social network services. Multimedia Tools and Applications, 1–12 (2014)Google Scholar
  3. 3.
    Oliveira, A., Ferrara, P., De Rosa, A., Piva, A., Barni, M., Goldenstein, S., Dias, Z., Rocha, A.: Multiple parenting identification in image phylogeny. In: IEEE International Conference on Image Processing (ICIP), pp. 5347–5351 (2014)Google Scholar
  4. 4.
    Usage of Image File Formats for Websites.
  5. 5.
    Kee, E., Johnson, M.K., Farid, H.: Digital image authentication from JPEG headers. IEEE Transactions on Information Forensics and Security 6(3), 1066–1075 (2011)CrossRefGoogle Scholar
  6. 6.
    Piva, A.: An overview on image forensics. Proceedings of ISRN Signal Process., p. 496701 (2013)Google Scholar
  7. 7.
    Stamm, M.C., Wu, M., Liu, K.J.R.: Information forensics: An overview of the first decade. IEEE Access 1, 167–200 (2013)CrossRefGoogle Scholar
  8. 8.
    Bruna, A.R., Messina, G., Battiato, S.: Crop Detection through Blocking Artefacts Analysis. In: Maino, G., Foresti, G.L. (eds.) ICIAP 2011, Part I. LNCS, vol. 6978, pp. 650–659. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  9. 9.
    Luo, W., Qu, Z., Huang, J., Qiu G.: A novel method for detecting cropped and recompressed image block. In: Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP), vol. 2, pp. II217–II220 (2007)Google Scholar
  10. 10.
    Battiato, S., Farinella, G.M., Messina, E., Puglisi, G.: Robust image alignment for tampering detection. IEEE Transactions on Information Forensics and Security 7(4), 1105–1117 (2012)CrossRefGoogle Scholar
  11. 11.
    Kee, E., Farid, H.: Digital image authentication from thumbnails. In: Proceedings of SPIE, vol. 7541 (January 2010)Google Scholar
  12. 12.
    Gloe, T.: Forensic analysis of ordered data structures on the example of JPEG files. In: Proceedings of IEEE International Workshop on Information Forensics and Security (WIFS), pp. 139–144 (2012)Google Scholar
  13. 13.
    Chen, Y., Thing, V.L.L.: A study on the photo response nonuniformity noise pattern based image forensics in real-world applications. In: Proceedings of IEEE International Conference on Image Processing, Computer Vision, Pattern Recognit. (IPCV) (July 2012)Google Scholar
  14. 14.
    Battiato, S., Messina G.: Digital forgery estimation into DCT domain: A critical analysis. In: Proceedings of ACM Workshop on Multimedia Forensics (MiFor), pp. 37–42 (2009)Google Scholar
  15. 15.
    Redi, J.A., Taktak, W., Dugelay, J.L.: Digital image forensics: A booklet for beginners. Multimedia Tools and Applications 51(1), 133–162 (2011)CrossRefGoogle Scholar
  16. 16.
    Galvan, F., Puglisi, G., Bruna, A.R., Battiato, S.: First Quantization Matrix Estimation From Double Compressed JPEG Images. IEEE Transactions on Information Forensics and Security 9(8), 1299–1310 (2014)CrossRefGoogle Scholar
  17. 17.
    Camera & Imaging Products Association: Standardization Committee - Exchangeable image file format for digital still cameras: Exif Version 2.3.
  18. 18.
    Pratama, S.F., Pratiwi, L., Abraham, A., Muda, A.K.: Computational Intelligence in Digital Forensics. In: Muda, A.K., Choo, Y.-H., Abraham, A., N. Srihari, S. (eds.) Computational Intelligence in Digital Forensics. SCI, vol. 555, pp. 1–16. Springer, Heidelberg (2014) CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Marco Moltisanti
    • 1
    Email author
  • Antonino Paratore
    • 1
  • Sebastiano Battiato
    • 1
  • Luigi Saravo
    • 2
  1. 1.Image Processing Laboratory – Dipartimento di Matematica e InformaticaUniversità degli Studi di CataniaCataniaItaly
  2. 2.Arma dei Carabinieri – Reparto Investigazioni ScientificheNaplesItaly

Personalised recommendations