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Long-term location privacy protection for location-based services in mobile cloud computing

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Abstract

The popularity of mobile devices, especially intelligent mobile phones, significantly prompt various location-based services (LBSs) in cloud systems. These services not only greatly facilitate people’s daily lives, but also cause serious threats that users’ location information may be misused or leaked by service providers. The dummy-based privacy protection techniques have significant advantages over others because they neither rely on trusted servers nor need adequate number of trustworthy peers. Existing dummy-based location privacy protection schemes, however, cannot yet provide long-term privacy protection. In this paper, we propose four principles for the dummy-based long-term location privacy protection (LT-LPP). Based on the principles, we propose a set of long-term consistent dummy generation algorithms for the LT-LPP. Our approach is built on soft computing techniques and can balance the preferred privacy protection and computing cost. Comprehensive experimental results demonstrate that our approach is effective to both long-term privacy protection and fake path generation for LBSs in mobile clouds.

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References

  • Ahmad MW, Ansari MA (2012) A survey: soft computing in intelligent information retrieval systems. In: 12th international conference on computational science and its applications (iccsa), pp 26–34

  • Ardagna C, Cremonini M (2011) An obfuscation-based approach for protecting location privacy. IEEE Trans Depend Secure Comput 8(1):13–27

  • Ardagna CA, Cremonini M, Damiani E (2007) Location privacy protection through obfuscation-based techniques. In: Data and applications security, vol xxi. Springer, Berlin, pp 47–60

  • Bilogrevic I, Jadliwala M, Joneja V (2014) Privacy-preserving optimal meeting location determination on mobile devices. IEEE Trans Inf Forens Secur 9(7):1141–1156

    Article  Google Scholar 

  • Cho WJ, Park Y, Sur C (2013) An improved privacy-preserving navigation protocol in VANETs. J Wire Mob Netw Ubiquitous Comput Depend Appl 4(4):80–92

    Google Scholar 

  • Chow R, Golle P (2009) Faking contextual data for fun, profit, and privacy. In: Proceedings of the 8th acm workshop on privacy in the electronic society. Wpes ’09. ACM, New York, pp 105–108

  • Chow CY, Mohamed MF, Liu X (2006) A peer-to-peer spatial cloaking algorithm for anonymous location-based service. In: Proceedings of gis ’06. ACM, New York, pp 171–178

  • Dewri R (2013) Local differential perturbations: location privacy under approximate knowledge attackers. IEEE Trans Mob Comput 12(12):2360–2372

    Article  Google Scholar 

  • Gedik B, Liu L (2008) Protecting location privacy with personalized k-anonymity: architecture and algorithms. IEEE Trans Mob Comput 7(1):1–18

    Article  Google Scholar 

  • Gruteser M, Grunwald D (2003) Anonymous usage of location-based services through spatial and temporal cloaking. In: Proceedings of mobisys ’03. ACM, New York, pp 31–42

  • Hernández JL, Moreno MV, Jara AJ (2014) A soft computing based location-aware access control for smart buildings. Soft Comput 18(9):1659–1674

  • Kido H, Yanagisawa Y, Satoh T (2005) An anonymous communication technique using dummies for location-based services. In: Proceedings of icps ’05, pp 88–97

  • Kim DJ, Bien Z (2008) Design of personalized classifier using soft computing techniques for personalized facial expression recognition. IEEE Trans Fuzzy Syst 16(4):874–885

    Article  Google Scholar 

  • Krumm J (2009) Realistic driving trips for location privacy. In: Proceedings of pervasive ’09, pp 25–41

  • Leu FY (2009) A novel network mobility handoff scheme using sip and sctp for multimedia applications. J Netw Comput Appl 32(5):1073–1091

    Article  Google Scholar 

  • Leu FY, Liu JC, Hsu YT, Huang YL (2014) The simulation of an emotional robot implemented with fuzzy logic. Soft Comput 18(9):1729–1743

    Article  Google Scholar 

  • Liang H, Cai LX, Huang D, Shen X, Peng D (2012) An smdp-based service model for interdomain resource allocation in mobile cloud networks. IEEE Trans Veh Technol 61(5):2222–2232

    Article  Google Scholar 

  • Lien IT, Lin YH, Shieh JR (2013) A novel privacy preserving location-based service protocol with secret circular shift for k-nn search. IEEE Trans Inf Forens Secur 8(6):863–873

    Article  Google Scholar 

  • Lu H, Jensen CS, Yiu ML (2008) Pad: privacy-area aware, dummy-based location privacy in mobile services. In: Proceedings of mobide ’08. ACM, New York, pp 16–23

  • Mahmoud M, Shen XM (2012) A cloud-based scheme for protecting source-location privacy against hotspot-locating attack in wireless sensor networks. IEEE Trans Parallel Distrib Syst 23(10):1805–1818

    Article  Google Scholar 

  • Metre PB, Radhika KR, Gowrishankar G (2012) Survey of soft computing techniques for joint radio resource management. In: 2012 international conference on multimedia computing and systems (icmcs), IEEE. IEEE, New York, pp 562–565

  • Mitra Sushmita, Pal Sankar K, Mitra Pabitra (2002) Data mining in soft computing framework: a survey. IEEE Trans Neural Netw 13(1):3–14

    Article  Google Scholar 

  • Mokbel MF, Chow CY, Aref WG (2006) The new casper: query processing for location services without compromising privacy. In: Proceedings of vldb ’06, pp 763–774

  • Murakami M, Honda N (2008) Performance of the ids method as a soft computing tool. IEEE Trans Fuzzy Syst 16(6):1582–1596

    Article  Google Scholar 

  • Ogiela Marek R, Castiglione Aniello, You Ilsun (2014) Soft computing for security services in smart and ubiquitous environments. Soft Comput 18(8):1655–1658

    Article  Google Scholar 

  • Pan X, Xu JL, Meng XF (2012) Protecting location privacy against location-dependent attacks in mobile services. IEEE Trans Knowl Data Eng 24(8):1506–1519

    Article  Google Scholar 

  • Paulet R, Koasar MG, Yi X (2012) Privacy-preserving and content-protecting location based queries. In: IEEE 28th international conference on data engineering (icde), IEEE. IEEE, New York, pp 44–53

  • Puttaswamy K, Wang S, Steinbauer T (2014) Preserving location privacy in geosocial applications. IEEE Trans Mob Comput 13(1):159–173

    Article  Google Scholar 

  • Samarati P, Sweeney L (1998) Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. In: IEEE symposium on research in security and privacy

  • Shankar P, Ganapathy V, Iftode L (2009) Privately querying location-based services with sybilquery. In: Proceedings of ubicomp ’09. ACM, New York, pp 31–40

  • Shokri R, Freudiger J, Hubaux JP (2010) A unified framework for location privacy. In: In: Proceedings of the 9th International Symposium on Privacy Enhancing Technologies (PETS’10), pp 203–214

  • Tomoya T, Kazuhiro M, Ken M (2014) Evaluating data utility of privacy-preserving pseudonymized location datasets. J Wire Mob Netw Ubiquitous Comput Depend Appl 5(3):63–78

    Google Scholar 

  • Trawiński Krzysztof, Alonso Jose M, Hernández Noelia (2013) A multiclassifier approach for topology-based wifi indoor localization. Soft Comput 17(10):1817–1831

    Article  Google Scholar 

  • Wahab A, Quek C, Tan C (2009) Driving profile modeling and recognition based on soft computing approach. IEEE Trans Neural Netw 20(4):563–582

    Article  Google Scholar 

  • Yager RR, Grichnik AJ, Yager RL (2014) A soft computing approach to controlling emissions under imperfect sensors. IEEE Trans Syst Man Cybern Syst 44(6):687–691

    Article  Google Scholar 

  • You T-H, Peng WC, Lee WC (2007) Protecting moving trajectories with dummies. In: Proceedings of the 2007 international conference on mobile data management, pp 278–282

  • Yu Xinghuo, Kaynak Okyay (2009) Sliding-mode control with soft computing: a survey. IEEE Trans Ind Electron 56(9):3275–3285

    Article  Google Scholar 

  • Zhang X, Zhao L, Zhao W, Xu T (2014) Novel method of flatness pattern recognition via cloud neural network. Soft Comput. doi:10.1007/s00500-014-1445-z

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (NSFC) projects (Nos. 91438121 and 61373156), the Key Basic Research Project (No. 12JC1405400) of the Shanghai Municipality, the Shanghai Pujiang Program (No. 13PJ1404600) the National Basic Research Program of China (No. 2015CB352400), and Shanghai Branch of Southwest Electron and Telecom Technology Research Institute Project (No. 2013008).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Feilong Tang, Jie Li & Minyi Guo

  2. School of Information Science, Korean Bible University, Seoul, South Korea

    Ilsun You

Authors
  1. Feilong Tang
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  2. Jie Li
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  3. Ilsun You
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  4. Minyi Guo
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Corresponding author

Correspondence to Feilong Tang.

Additional information

Communicated by A. Jara, M. R. Ogiela, I. You and F.-Y. Leu.

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Tang, F., Li, J., You, I. et al. Long-term location privacy protection for location-based services in mobile cloud computing. Soft Comput 20, 1735–1747 (2016). https://doi.org/10.1007/s00500-015-1703-8

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