Content-Based Privacy for Consumer-Produced Multimedia

  • Gerald FriedlandEmail author
  • Adam Janin
  • Howard Lei
  • Jaeyoung Choi
  • Robin Sommer


We contend that current and future advances in Internet scale Multimedia analytics , global Inference , and linking can circumvent traditional Security and Privacy barriers. We therefore are in dire need of a new research field to address this issue and come up with new solutions. We present the privacy risks, Attack vectors , details for a preliminary experiment on Account linking , and describe mitigation and educational techniques that will help address the issues.


Face Recognition Equal Error Rate Multimedia Community Speaker Verification Multimedia Document 
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.



This material is based upon work supported by the National Science Foundation under Grant No. CNS-1065240. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. We thank Michael Ellsworth for his rewording suggestions.


  1. 1.
    Prosser D (1960) Privacy. In: California law review, vol 48, p 383Google Scholar
  2. 2.
    House TW (2012) Consumer data privacy in a networked world.
  3. 3.
  4. 4.
    Wikipedia (2013) Secure communication.
  5. 5.
    Sweeney L (1997) Weaving technology and policy together to maintain confidentiality. J Law Med Ethics 25:2–3CrossRefGoogle Scholar
  6. 6.
    Aggarwal C (2005) On k-anonymity and the curse of dimensionality. In: Proceedings of the international conference on very large data basesGoogle Scholar
  7. 7.
    Dinur I, Nissim K (2003) Revealing information while preserving privacy. In: ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems (PODS)Google Scholar
  8. 8.
    Dwork C (2006) Differential privacy. In: 33rd international colloquium on automata, languages, and programming (ICALP)Google Scholar
  9. 9.
    Dwork C (2008) Differential privacy: a survey of results. In: Agrawal M, Du D, Duan Z, Li A (eds) Theory and applications of models of computation., Lecture notes in computer scienceSpringer, Berlin, pp 1–19CrossRefGoogle Scholar
  10. 10.
    Sweeney L (2002) k-anonymity: a model for protecting privacy. J Uncertain Fuzziness Knowl-based Syst 10(5):557–570CrossRefzbMATHMathSciNetGoogle Scholar
  11. 11.
    Narayanan A, Shmatikov V (2008) Robust de-anonymization of large sparse datasets. In: Proceedings of the IEEE symposium on security and privacyGoogle Scholar
  12. 12.
    Narayanan A, Shmatikov V (2009) De-anonymizing social networks. In: Proceedings of the IEEE symposium on security and privacyGoogle Scholar
  13. 13.
    Chow R, Golle P, Staddon J (2008) Detecting privacy leaks using corpus-based association rules. In: Proceeding of the 14th ACM SIGKDD international conference on knowledge discovery and data miningGoogle Scholar
  14. 14.
    Staddon J, Golle P, Zimny B (2007) Web-based inference detection. In: Proceedings of 16th USENIX security symposiumGoogle Scholar
  15. 15.
    Griffith V, Jakobsson M (2005) Messin’ with texas deriving mother’s maiden names using public records. In: Proceedings of the international conference on applied cryptography and network security (ACNS)Google Scholar
  16. 16.
    Balduzzi M, Platzer C, Holz T, Kirda E, Balzarotti D, Kruegel C (2010) Abusing social networks for automated user profiling. In: 13th international symposium on recent advances in intrusion detection, 09 RAID’2010Google Scholar
  17. 17.
    Bishop M, Cummins J, Peisert S, Singh A, Bhumiratana B, Agarwal D, Frincke D, Hogarth M (2010) Relationships and data sanitization: a study in scarlet. In: Proceedings of the workshop on new security paradigmsGoogle Scholar
  18. 18.
    Blumberg A, Eckersley P, On locational privacy, and how to avoid losing it forever. Electronic frontier foundationGoogle Scholar
  19. 19.
    Hoh B, Gruteser M, Herring R, Ban J, Work D, Herrera J-C, Bayen AM, Annavaram M, Jacobson Q (2008) Virtual trip lines for distributed privacy-preserving traffic monitoring. In: Proceeding of the 6th international conference on mobile systems, applications, and services MobiSys’08Google Scholar
  20. 20.
    Popa RA, Balakrishnan H, Blumberg A (2009) VPriv: protecting privacy in location-based vehicular services. In: Proceedings of the USENIX security symposiumGoogle Scholar
  21. 21.
    Zhong G, Goldberg I, Hengartner U (2007) Louis, lester and pierre: three protocols for location privacy. In: Proceedings of the privacy enhancing technologies symposiumGoogle Scholar
  22. 22.
  23. 23.
    Friedland G, Sommer R (2010) Cybercasing the joint: on the privacy implications of geo-tagging. In: Proceedings of the USENIX workshop on hot topics in security, August 2010Google Scholar
  24. 24.
    Friedland G, Choi J (2011) Semantic computing and privacy: a case study using inferred geo-location. Int J Semant Comput 5(01):79–93CrossRefGoogle Scholar
  25. 25.
    Lukas J, Fridrich J, Goljan M (2006) Digital camera identification from sensor pattern noise. IEEE Trans Inf Forensics Secur 1(2):205–214CrossRefGoogle Scholar
  26. 26.
    Dufaux F, Ebrahimi T (2006) Scrambling for video surveillance with privacy. In: computer vision and pattern recognition workshop. CVPRW’06. In: Proceeding of the conference on, pp 160–160Google Scholar
  27. 27.
    Fan J, Luo H, Hacid M-S, Bertino E (2005) A novel approach for privacy-preserving video sharing. In: Proceedings of the 14th ACM international conference on information and knowledge management, CIKM’05. ACM, New York, pp 609–616Google Scholar
  28. 28.
    Koshimizu T, Toriyama T, Babaguchi N (2006) Factors on the sense of privacy in video surveillance. In: Proceedings of the 3rd ACM workshop on continuous archival and retrival of personal experiences, CARPE’06. ACM, New York, pp 35–44Google Scholar
  29. 29.
    Neustaedter C, Greenberg S, Boyle M (2006) Blur filtration fails to preserve privacy for home-based video conferencing. ACM Trans Comput-Hum Interact 13(1):1–36CrossRefGoogle Scholar
  30. 30.
    Dufaux F, Ebrahimi T (2010) A framework for the validation of privacy protection solutions in video surveillance. In: IEEE international conference on multimedia and expo (ICME), pp 66–71Google Scholar
  31. 31.
    Friedland G, Maier G, Sommer R, Weaver N (2011) Sherlock Holmes evil twin: on the impact of global inference for online privacy. In: Proceedings of the new security paradigms workshop (NSPW), September 2011Google Scholar
  32. 32.
    Cohan P (2009) Why executives risk their job to tip a hedge fund.,
  33. 33. Mechanical Turk,
  34. 34.
    Mediaeval web site.
  35. 35.
    Burget L, Oldřich P, Sandro C, Glembek O, Matějka P, Brümmer N (2011) Discriminantly trained probabilistic linear discriminant analysis for speaker verification. In: Proceedings of ICASSP, Brno, Czech RepublicGoogle Scholar
  36. 36.
    Mathias L, Chatzichristofis SA (2008) Lire: Lucene image retrieval—an extensible Java CBIR library. In: Proceedings of the 16th ACM international conference on multimedia, pp 1085–1088, October 2008Google Scholar
  37. 37.
    Hatch AO (2006) Generalized linear kernels for one-versus-all classification: application to speaker recognition. In: Proceedings of ICASSP, Toulouse, FranceGoogle Scholar
  38. 38.
    Ioffe S (2006) Probabilistic linear discriminant analysis. In: Proceedings of ECCV, pp 531–542Google Scholar
  39. 39.
  40. 40.
    Bonastre J, Wils F, Meignier S (2005) Alize, a free toolkit for speaker recognition. In: Proceedings of the ICASSP, vol 1, pp 737–740Google Scholar
  41. 41.
    Hmm toolkit (htk).
  42. 42.
  43. 43.
    Tools for teaching privacy to k12 and undergraduate students.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gerald Friedland
    • 1
    Email author
  • Adam Janin
    • 1
  • Howard Lei
    • 1
  • Jaeyoung Choi
    • 1
  • Robin Sommer
    • 1
  1. 1.International Computer Science InstituteBerkeleyUSA

Personalised recommendations