Advertisement

Multimedia Tools and Applications

, Volume 78, Issue 22, pp 31003–31017 | Cite as

Ensuring efficient multimedia message sharing in mobile social network

  • Xuejiao LiuEmail author
  • Junmei Sun
  • Wei Yang
  • Mengqing Jiang
  • Fengli Yang
Article
  • 182 Downloads

Abstract

Mobile Social Networks (MSN) are attractive applications which enable users to share data with a group of friends and stay connected. WeChat, QQ are among the most popular applications of MSNs where personal multimedia files are shared among group contacts. However, the security risks accompanying such developments have raised concerns in people. The providers typically store users’ data, and offer few options for the users to custom and manage the dissipation of their data over the network. In this paper, we design a data sharing framework in which individuals retain ownership of their data. The scheme gives users flexible and granular access control over their data, and more importantly it provides protection from the untrusted data provider server. Experiments show the efficiency of our scheme.

Keywords

Mobile social network Message sharing Attribute based encryption 

Notes

Acknowledgments

This research is supported in part by the following funds: National Natural Science Foundation of China under grant number 61502134, 61472113, and 61304188, Zhejiang Provincial Natural Science Foundation of China under grant number LZ13F020004 and LR14F020003, Zhejiang Provincial Science and Technology Innovation Program under grant number 2013TD03, and Hangzhou Science and Technology Development Plan under grant number 20170533B04.

References

  1. 1.
    Baden R, Bender A, Spring N, Bhattacharjee B, Starin D (2009) Persona: an online social network with user-defined privacy ACM SIGCOMM Computer Communication Review, vol 39. ACM, pp 135–146Google Scholar
  2. 2.
    Beimel A (1996) Secure schemes for secret sharing and key distribution. PhD thesis, Israel Institute of Technology, Technion, Haifa, IsraelGoogle Scholar
  3. 3.
    Bethencourt J, Sahai A, Waters B (2007) Ciphertext-policy attribute-based encryption. In: IEEE Symposium on Security and Privacy, pp 321–334Google Scholar
  4. 4.
    Boneh D, Franklin M (2001) Identity-based encryption from the weil pairing Proceedings of Crypto on Advances in Cryptology. Springer, pp 213–229Google Scholar
  5. 5.
    Boyen X, Waters B (2007) Full-domain subgroup hiding and constant-size group signatures Proceedings of the International Conference on Practice and Theory in Public-Key Cryptography, Beijing, China, pp 1–15Google Scholar
  6. 6.
    Chen J, Song X, Nie L, Wang X, Zhang H, Chua T-S (2016) Micro tells macro: Predicting the popularity of micro-videos via a transductive model Proceedings of the 2016 ACM on Multimedia Conference. ACM, pp 898–907Google Scholar
  7. 7.
    Cheung L, Newport C (2007) Provably secure ciphertext policy abe. In: Proceedings of the 14th ACM Conference on Computer and Communications Security, pp 456–465Google Scholar
  8. 8.
    Dong W, Dave V, Qiu L, Zhang Y (2011) Secure friend discovery in mobile social networks. Proc IEEE Int Conf Comput Commun 34(17):1647–1655Google Scholar
  9. 9.
    Gao H, Hu J, Huang T, Wang J, Chen Y (2011) Security issues in online social networks. IEEE Internet Comput 15(4):56–63CrossRefGoogle Scholar
  10. 10.
    Green AAM, Rushanan M. libfenc: the functional encryption library. http://code.google.com/p/libfenc/
  11. 11.
    Green M, Hohenberger S, Waters B (2011) Outsourcing the decryption of abe ciphertexts. In: Proceedings of the 20th Usenix Conference on Security, pp 34–34Google Scholar
  12. 12.
    Hohenberger S, Waters B (2013) Attribute-based encryption with fast decryption. In: Public Key Cryptography, pp 162–179CrossRefGoogle Scholar
  13. 13.
    Kate A, Zaverucha G, Goldberg I (2007) Pairing-based onion routing Privacy Enhancing Technologies. Springer, pp 95–112Google Scholar
  14. 14.
    Lewko A, Okamoto T, Sahai A, Takashima K, Waters B (2010) Fully secure functional encryption: Attribute-based encryption and (hierarchical) inner product encryption. In: Proceedings of Eurocrypt on Advances in Cryptology, pp 62–91Google Scholar
  15. 15.
    Liang X, Cao Z, Shao J, Lin H (2007) Short group signature without random oracles. Springer, Berlin HeidelbergCrossRefGoogle Scholar
  16. 16.
    Liang X, Xu L, Zhang K, Lu R (2013) Fully anonymous profile matching in mobile social networks. IEEE J Select Areas Commun 31(9):641–655CrossRefGoogle Scholar
  17. 17.
    Li J, Ren K, Bo Z, Wan Z (2009) Privacy-aware attribute-based encryption with user accountability. In: Information Security, pp 347–362Google Scholar
  18. 18.
    Li M, Cao N, Yu S, Lou W (2011) Findu: Privacy-preserving personal profile matching in mobile social networks. Proc IEEE Int Conf Comput Commun 2 (3):2435–2443Google Scholar
  19. 19.
    Liu X, Xia Y, Jiang S, Xia F, Wang Y (2013) Hierarchical attribute-based access control with authentication for outsourced data in cloud computing Proceedings of the 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications. IEEE, pp 477–484Google Scholar
  20. 20.
    Liu X, Xia Y, Chen W, Xiang Y, Hassan MM, Alelaiwi A (2016) Semd: Secure and efficient message dissemination with policy enforcement in vanet. J Comput Syst Sci 82:1316–1328MathSciNetCrossRefGoogle Scholar
  21. 21.
    Lynn B. Stanford pairings-based crypto library. http://crypto.stanford.edu/pbc/
  22. 22.
    Ostrovsky R, Sahai A, Waters B (2007) Attribute-based encryption with non-monotonic access structures. In: Proceedings of the 14th ACM Conference on Computer and Communications Security, pp 195–203Google Scholar
  23. 23.
    Sahai A., Waters B. (2005) Fuzzy identity-based encryption. In: Proceedings of Eurocrypto on Advances in Cryptology, pp 557–557Google Scholar
  24. 24.
    Sahai A, Seyalioglu H, Waters B (2012) Dynamic credentials and ciphertext delegation for attribute-based encryption. In: Proceedings of Crypto on Advances in Cryptology, pp 199–217Google Scholar
  25. 25.
    Song X, Ming Z-Y, Nie L, Zhao Y-L, Chua T-S (2016) Volunteerism tendency prediction via harvesting multiple social networks. ACM Trans Inf Syst 34 (2):10CrossRefGoogle Scholar
  26. 26.
    Song X, Nie L, Zhang L, Akbari M, Chua T-S (2017) Multiple social network learning and its application in volunteerism tendency prediction Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, pp 213–222Google Scholar
  27. 27.
    Tootoonchian A, Saroiu S, Ganjali Y, Wolman A (2009) Lockr: better privacy for social networks Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies,. ACM, pp 169–180Google Scholar
  28. 28.
    Wang W, Yan Y, Zhang L, Hong R, Sebe N (2016) Collaborative sparse coding for multiview action recognition. IEEE MultiMed 23(4):80–87CrossRefGoogle Scholar
  29. 29.
    Waters B (2009) Dual system encryption: Realizing fully secure ibe and hibe under simple assumptions. In: Proceedings of Crypto on Advances in Cryptology, pp 619–636CrossRefGoogle Scholar
  30. 30.
    Waters B (2011) Ciphertext-policy attribute-based encryption: An expressive, efficient, and provably secure realization. In: Public Key Cryptography, pp 53–70CrossRefGoogle Scholar
  31. 31.
    Xia Y, Ren X, Peng Z, Zhang J, Li S (2014) Effectively identifying the influential spreaders in large-scale social networks. Multimedia Tools and Applications, pp 1–13Google Scholar
  32. 32.
    Xia Y, Liu X, Xia F, Wang G (2016) A reduction of security notions in designated confirmer signatures. Theor Comput Sci 618:1–20MathSciNetCrossRefGoogle Scholar
  33. 33.
    Zhang L, Song M, Li N, Bu J, Chen C (2009) Feature selection for fast speech emotion recognition Proceedings of the 17th ACM international conference on Multimedia. ACM, pp 753–756Google Scholar
  34. 34.
    Zhang R, Zhang R, Sun J, Yan U (2012) Fine-grained private matching for proximity-based mobile social networking. Proc IEEE Int Conf Comput Commun 131 (5):1969–1977Google Scholar
  35. 35.
    Zhang L, Han Y, Yi Y, Song M, Yan S, Qi T (2013) Discovering discriminative graphlets for aerial image categories recognition. IEEE Trans Image Process 22(12):5071–5084MathSciNetCrossRefGoogle Scholar
  36. 36.
    Zhang L, Song M, Qi Z, Liu X, Bu J, Chen C (2013) Probabilistic graphlet transfer for photo cropping, vol 22MathSciNetCrossRefGoogle Scholar
  37. 37.
    Zhang L, Gao Y, Xia Y, Lu K, Shen J, Ji R (2014) Representative discovery of structure cues for weakly-supervised image segmentation. IEEE Trans Multimed 16 (2):470–479CrossRefGoogle Scholar
  38. 38.
    Zhang L, Yi Y, Gao Y, Yu Y, Wang C, Li X (2014) A probabilistic associative model for segmenting weakly supervised images. IEEE Trans Image Process 23(9):4150–4159MathSciNetCrossRefGoogle Scholar
  39. 39.
    Zhang L, Gao Y, Zimmermann R, Qi T, Li X (2014) Fusion of multichannel local and global structural cues for photo aesthetics evaluation. IEEE Trans Image Process 23(3):1419–1429MathSciNetCrossRefGoogle Scholar
  40. 40.
    Zhang J, Nie L, Wang X, He X, Huang X, Chua TS (2016) Shorter-is-better Venue category estimation from micro-video Proceedings of the 2016 ACM on Multimedia Conference. ACM, pp 1415– 1424Google Scholar
  41. 41.
    Zhang L, Hong R, Gao Y, Ji R, Dai Q, Li X (2016) Image categorization by learning a propagated graphlet path. IEEE Trans Neural Netw Learn Syst 27(3):674–685MathSciNetCrossRefGoogle Scholar
  42. 42.
    Zhang L, Wang M, Hong R, Yin B-C, Li X (2016) Large-scale aerial image categorization using a multitask topological codebook. IEEE Trans Cybern 46 (2):535–545CrossRefGoogle Scholar
  43. 43.
    Zhang L, Yang Y, Wang M, Hong R, Nie L, Li X (2016) Detecting densely distributed graph patterns for fine-grained image categorization. IEEE Trans Image Process 25(2):553–565MathSciNetCrossRefGoogle Scholar
  44. 44.
    Zhang L, Gao Y, Xia Y, Dai Q, Li X (2017) A fine-grained image categorization system by cellet-encoded spatial pyramid modeling. IEEE Trans Indust Electron 62(1):564–571CrossRefGoogle Scholar
  45. 45.
    Zhang L, Xia Y, Ji R, Li X (2017) Spatial-aware object-level saliency prediction by learning graphlet hierarchies. IEEE Trans Indust Electron 62(2):1301–1308CrossRefGoogle Scholar
  46. 46.
    Zhang L, Gao Y, Ji R, Dai Q, Li X Actively learning human gaze shifting paths for photo cropping. IEEE Transcations on Image Processing, pages 2235–2245Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Xuejiao Liu
    • 1
    Email author
  • Junmei Sun
    • 1
  • Wei Yang
    • 2
    • 3
  • Mengqing Jiang
    • 4
  • Fengli Yang
    • 1
  1. 1.Institute of Service EngineeringHangzhou Normal UniversityHangzhouChina
  2. 2.Wuhan UniversityWuhanChina
  3. 3.Institute of No.145 Erqi RoadWuhanChina
  4. 4.Hangzhou Yuantiao Technology CorporationHangzhouChina

Personalised recommendations