AdPriRec: A Context-Aware Recommender System for User Privacy in MANET Services

  • Zheng Yan
  • Peng Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6905)


Mobile ad hoc network (MANET) has become a practical platform for pervasive services. Various user data could be requested for accessing such a service. However, it is normally difficult for a user to justify whether it is safe and proper to disclose personal data to others in different contexts. For solving this problem, we propose AdPriRec, a context-aware recommender system for preserving user privacy in MANET services. To support frequent changes of node pseudonyms in MANET, we develop a hybrid recommendation generation solution. We apply a trusted recommendation sever who knows the node’s real identity to calculate a recommendation vector based on long term historical experiences. The vector can be also generated at each MANET node according to recent experiences accumulated based on node pseudonyms, while this vector could be further fine-tuned when the recommendation server is accessible. We design a number of algorithms for AdPriRec to generate context-aware recommendations for MANET users. The recommendation vector is calculated based on a number of factors such as data sharing behaviors and behavior correlation, service popularity and context, personal data type, community information of nodes and trust value of each involved party. An example based evaluation illustrates the usage and implication of the factors and shows AdPriRec’s effectiveness. A prototype implementation based on Nokia N900 further proves the concept of AdPriRec design.


Collaborative Filter User Privacy Recommendation Trust Pervasive Service Service Popularity 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Sun, Y., Yu, W., Han, Z., Liu, K.J.R.: Information Theoretic Tramework of Trust Modeling and Evaluation for Ad Hoc Networks. IEEE Journal on Selected Area in Communications 24(2), 305–317 (2006)CrossRefGoogle Scholar
  2. 2.
    Theodorakopoulos, G., Baras, J.S.: On Trust Models and Trust Evaluation Metrics for Ad Hoc Networks. IEEE Journal on Selected Areas in Communications 24(2), 318–328 (2006)CrossRefGoogle Scholar
  3. 3.
    Raya, M., Papadimitratos, P., Gligory, V.D., Hubaux, J.-P.: On Data-Centric Trust Establishment in Ephemeral Ad Hoc Networks. In: IEEE INFOCOM, pp. 1912–1920 (2008)Google Scholar
  4. 4.
    Zouridaki, C., Mark, B.L., Hejmo, M., Thomas, K.R.: Robust Cooperative Trust Establishment for MANETs. In: SASN 2006: Proceedings of the Fourth ACM Workshop on Security of Ad Hoc and Sensor Networks, pp. 23–34(2006)Google Scholar
  5. 5.
    Resnick, P., Varian, H.R.: Recommender Systems. Communications of the ACM 40(3), 56–58 (1997)CrossRefGoogle Scholar
  6. 6.
    Hancock, J.T., Toma, C., Ellison, N.: The Truth about Lying in Online Dating Profiles. In: Proceedings of the ACM CHI 2007, pp. 449–452. ACM, New York (2007)Google Scholar
  7. 7.
    Su, X., Khoshgoftaar, T.M.: A Survey of Collaborative Filtering Techniques. In: Advances in Artificial Intelligence vol. 19 (2009), doi:10.1155/2009/421425Google Scholar
  8. 8.
    O’Donovan, J., Smyth, B.: Trust in Recommender Systems. In: IUI 2005, pp. 167–174 (2005)Google Scholar
  9. 9.
    Polat, H., Du, W.L.: Privacy-Preserving Top-N Recommendation on Horizontally Partitioned Data. In: The 2005 IEEE/WIC/ACM International Conference on Web Intelligence, 725–731 (2005)Google Scholar
  10. 10.
    Luo, Y., Le, J., Chen, H.: A Privacy-Preserving Book Recommendation Model Based on Multi-agent. In: WCSE 2009, pp. 323–327 (2009)Google Scholar
  11. 11.
    Li, T., Gao, C., Du, J.: A NMF-Based Privacy-Preserving Recommendation Algorithm. In: ICISE 2009, pp. 754–757 (2009)Google Scholar
  12. 12.
    Bilge, A., Polat, H.: Improving Privacy-Preserving NBC-Based Recommendations by Preprocessing. In: WI-IAT 2010, pp. 143–147 (2010)Google Scholar
  13. 13.
    Ahn, J., Amatriain, X: Towards Fully Distributed and Privacy-Preserving Recommendations via Expert Collaborative Filtering and RESTful Linked Data. In: WI-IAT 2010, pp. 66–73 (2010)Google Scholar
  14. 14.
    Tada, M., Kikuchi, H., Puntheeranurak, S.: Privacy-Preserving Collaborative Filtering Protocol Based on Similarity between Items. In: AINA 2010, pp. 573–578 (2010)Google Scholar
  15. 15.
    Kikuchi, H., Kizawa, H., Tada, M.: Privacy-Preserving Collaborative Filtering Schemes. In: ARES 2009, pp. 911–916 (2009)Google Scholar
  16. 16.
    Katzenbeisser, S., Petkovic, M.: Privacy-Preserving Recommendation Systems for Consumer Healthcare Services. In: ARES 2008, pp. 889–895 (2008)Google Scholar
  17. 17.
    Yu, Z., Zhou, X., Zhang, D., Chin, C., Wang, X., Men, J.: Supporting Context-Aware Media Recommendations for Smart Phones. IEEE Pervasive Computing 5(3), 68–75 (2006)CrossRefGoogle Scholar
  18. 18.
    Yap, G., Tan, A., Pang, H.: Discovering and Exploiting Causal Dependencies for Robust Mobile Context-Aware Recommenders. IEEE Transactions on Knowledge and Data Engineering 19(7), 977–992 (2007)CrossRefGoogle Scholar
  19. 19.
    Wang, J., Kodama, E., Takada, T., Li, J.: Mining context-related sequential patterns for recommendation systems. In: CAMP 2010, pp. 270–275 (2010)Google Scholar
  20. 20.
    Zhang, D., Yu, Z.: Spontaneous and Context-Aware Media Recommendation in Heterogeneous Spaces. In: IEEE VTC 2007, pp. 267–271 (2007)Google Scholar
  21. 21.
    Chuong, C., Torabi, T., Loke, S.W.: Towards Context-aware Task Recommendation. In: JCPC 2009, pp. 289–292 (2009)Google Scholar
  22. 22.
    Liiv, I., Tammet, T., Ruotsalo, T., Kuusik, A.: Personalized Context-Aware Recommendations in SMARTMUSEUM: Combining Semantics with Statistics. In: SEMAPRO 2009, pp. 50–55 (2009)Google Scholar
  23. 23.
    Liu, D., Meng, X., Chen, J.: A Framework for Context-Aware Service Recommendation. In: ICACT 2008, pp. 2131–2134 (2008)Google Scholar
  24. 24.
    Xiao, H., Zou, Y., Ng, J., Nigul, L.: An Approach for Context-Aware Service Discovery and Recommendation. In: IEEE ICWS 2010, pp. 163–170 (2010)Google Scholar
  25. 25.
    Seetharam, A., Ramakrishnan, R.: A context sensitive, yet private experience towards a contextually apt recommendation of service. In: IMSAA 2008, pp. 1–6 (2008)Google Scholar
  26. 26.
    Berkovsky, S., De Luca, E.W., Said, A.: Proceedings of the Workshop on Context-Aware Movie Recommendation (2010)Google Scholar
  27. 27.
    Ahtiainen, A., Kalliojarvi, K., Kasslin, M., Leppanen, K., Richter, A., Ruuska, P., Wijting, C.: Awareness Networking in Wireless Environments: Means of Exchanging Information. IEEE Vehicular Technology Magazine 4(3), 48–54 (2009)CrossRefGoogle Scholar
  28. 28.
    Yan, Z., Chen, Y.: AdContRep: A privacy enhanced reputation system for MANET content services. In: Yu, Z., Liscano, R., Chen, G., Zhang, D., Zhou, X. (eds.) UIC 2010. LNCS, vol. 6406, pp. 414–429. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  29. 29.
    Wang, J., Wang, F., Yan, Z., Huang, B.: Message Receiver Determination in Multiple Simultaneous IM Conversations. IEEE Intelligent Systems 26(3), 24–31 (2011)CrossRefGoogle Scholar
  30. 30.
    Yan, Z., Liu, C., Niemi, V., Yu, G.: Trust information indication: effects of displaying trust information on mobile application usage. Technical Report NRC-TR-2009-004, Nokia Research Center,
  31. 31.
    Hu, J., Burmester, M.: LARS: A locally Aware Reputation System for Mobile Ad Hoc Networks. In: Proc. of the 44th ACM Annual Southeast Regional Conf., pp. 119–123 (2006)Google Scholar
  32. 32.
    Douceur, J.R.: The sybil attack. In: Druschel, P., Kaashoek, M.F., Rowstron, A. (eds.) IPTPS 2002. LNCS, vol. 2429, pp. 251–260. Springer, Heidelberg (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Zheng Yan
    • 1
    • 2
  • Peng Zhang
    • 3
  1. 1.Aalto UniversityEspooFinland
  2. 2.XiDian UniversityXi’anChina
  3. 3.Xi’an University of Post and TelecommunicationsXi’anChina

Personalised recommendations