Call for Paper - November 2022 Edition
IJCA solicits original research papers for the November 2022 Edition. Last date of manuscript submission is October 20, 2022. Read More

Profile Privacy Aware Framework for Static objects Participatory Sensing

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Dorothy Kalui, Dezheng Zhang
10.5120/ijca2016910805

Dorothy Kalui and Dezheng Zhang. Profile Privacy Aware Framework for Static objects Participatory Sensing. International Journal of Computer Applications 153(9):1-9, November 2016. BibTeX

@article{10.5120/ijca2016910805,
	author = {Dorothy Kalui and Dezheng Zhang},
	title = {Profile Privacy Aware Framework for Static objects Participatory Sensing},
	journal = {International Journal of Computer Applications},
	issue_date = {November 2016},
	volume = {153},
	number = {9},
	month = {Nov},
	year = {2016},
	issn = {0975-8887},
	pages = {1-9},
	numpages = {9},
	url = {http://www.ijcaonline.org/archives/volume153/number9/26428-2016910805},
	doi = {10.5120/ijca2016910805},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Mobile devices users in Participatory Sensing Systems (PSS) are required to collect information from their nearby data collection points (DCs). A query normally reveals the identity (id), location, and user profile (e.g., race domain). This information facilitates an adversary PS server to infer over time a comprehensive user location summary with a high degree of precision. Some privacy techniques in PSS have been suggested recently to provide user privacy protection. However, only a few techniques that consider trust in static objects but disregard profile information. For credibility of data, there is scarcely any service, which entails the user to prove that she is at a particular DC point at a certain time. Yet none of the position and time information achieved by nowadays mobile devices is reliable. In this paper, we propose an enhanced K-location privacy-aware framework for static objects in PS system. The experimental results demonstrate in our approach user a high degree of anonymity and reliability of collected data.

References

  1. A. Asuncion and D.J. Newman. UCI machine learning repository, 2007.
  2. C. Y Chow, M. F. Mokbel, and Liu. Spatial cloaking for anonymous location-based services in mobile peer-to-peer, environments. GIS., 15:351–380, 2009.
  3. Cisco and its affiliates. Global mobile data trafic forecast. Cisco visual networking index, 2013.
  4. C Cornelius, A Kapadia, D Kotz, D Peebles, M Shin, and N Triandopoulos. Anonysense: privacy-aware people-centric sensing. MobiSys ., pages 211–224, 2008.
  5. BCM Fung, K. Wang, R. Chen, and P.S Yu. Privacypreserving data publishing: a survey of recent developments. ACM Comput Surv, 42(4):1–14, 2010.
  6. K. L. Huang, S. S. Kanhere, andW. Hu. On the need for a reputation system in mobile phone based sensing. Ad Hoc Networks, 12.
  7. KL Huang, SS Kanhere, and W Hu. Towards privacysensitive participatory sensing. PERCOM, pages 1–6, 2009.
  8. T. Jiang, H. J. Wang, and Y.-C. Hu. Preserving location privacy in wireless lans. ACM MobiSys., page 246, 2007.
  9. D. Kalui, X. Guo, D. Zhang, Y. Xie, and Z. Yang. Personalized privacy aware framework for moving objects in participatory sensing. pages 191 – 198. IEEE Computer Society, 2015.
  10. D. Kalui, X. Guo, D. Zhang, Y. Xie, and X. Zhang. Trust assurance privacy aware framework for moving objects in participatory sensing. pages 246–251. IEEE, 2016.
  11. L Kazemi and C Shahabi. A privacy-aware framework for participatory sensing. SIGKDD Explorations, 13(1):43–51, 2011.
  12. L. Kazemi and C. Shahabi. Trustworthy privacy-aware participatory sensing. Knowl Inf Syst, 37(3):105– 127, 2012.
  13. K.Puttaswamy, R.Bhagwan, and VN.Padmanabhan. Anonygator: Privacy and integrity preserving data aggregation. Middleware, pages 763–774, 2010.
  14. Hu Ling and C Shahabi. Privacy assurance in mobile sensing networks: go beyond trusted servers. PerCom Workshops, pages 613–619, 2010.
  15. Masanori Mano, Xi Guo, Tingting Dong, and Yoshiharu Ishikawa. Privacy preservation for location based services based on attribute visibility. VLDB CEUR Workshop Insta, 908(4):33–41, 2006.
  16. Hayam Mousaa, Sonia Ben Mokhtara, Omar Hasana, Osama Younesb, Mohiy Hadhoudb, and Lionel Bruniea. Trust management and reputation systems in mobile participatory sensing applications:a survey. Computer Networks the International Journal of Computer Telecommunications Networking, 90.
  17. B Niu, Q Li, X Zhu, G Cao, and Hui Li. Achieving kanonymity in privacy-aware location-based services. Infocom., 978:799–3360., 2014.
  18. Amna Qureshi, David Megas, and Helena Rif-Pous. Framework for preserving security and privacy in peer-to-peer content distribution systems. Expert Systems with Applications, 42:1391 – 1408, 2015.
  19. F. Restuccia, S. K. Das, and J. Payton. Incentive mechanisms for participatory sensing: Survey and research challenges. ACM Trans. Sen. Netw, 12:1 – 38, 2016.
  20. C Shahabi and L Kazemii. Towards preserving privacy in particpatory sensing. PerCom, pages 328– 331, 2011.
  21. C.E. Shannon. A mathematical theory of communication. The Bell System Technical, 27:379–423, 1948.
  22. H. Shin, V. Atluri, and J. Vaidya. A profile anonymization model for privacy in a personalized location based service environment. International Conference on Mobile Data Management (MDM), pages 73–80, 2008.
  23. Sameer Tila. Real-world deployments of participatory sensing applications:current trends and future directions. Sensor Networks.
  24. Bo Wang and Jing Yang. Personalized algorithm based on entropy classification. Computational Information Systems, 8(1):259–266, 2012.
  25. X. O.Wang,W. Cheng, P. Mohapatra, and T. Abdelzaher. Enabling reputation and trust in privacy-preserving mobile sensing. IEEE Transactions on Mobile Computing, 99.
  26. X. Xiao and Y. Tao. Personalized privacy preservation. ACM SIGMOD., pages 229–240, 2006.

Keywords

Privacy, Anonymity, location attacks, profile, Visibility