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Comprehensive Review: Privacy Protection of User in Location-Aware Services of Mobile Cloud Computing

Abstract

One of the recent trends of networking and mobile technology is mobile cloud computing (MCC) that provides rich computational, storage resources and services in clouds to mobile users. MCC applications provide a variety of services to users and one of them is the location-based services (LBS) applications that are widely spread. By using mobile applications and LBS, mobile devices act as a thin client where the abundant data locations are collected and stored at the mobile cloud to provide corresponding services. Privacy of the user’s location has been a renewed research interest and extensively studied in recent years. However, privacy is one of the most important challenges in MCC because the user’s location on mobile devices is offloaded from mobile devices to cloud providers which can be utilized by third parties. Since protecting the privacy of the user is the key to maintain the trust on the mobile environment. LBS faces issues in protecting privacy such as, the privacy of user’s current location, which may contain private information. In case, if the user’s current location is compromised through unauthorized access, it possibly results in severe consequences. Therefore, protecting location privacy of the user while achieving precise location is still a challenge in MCC. This comprehensive research review will provide the challenge of protecting the privacy of user’s location in MCC; analyze several related works regarding the issue. In addition, it suggests possible solutions related to the issue, in lighted few shortcomings which still needs attention with few related case studies.

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References

  1. 1.

    Othman, M. (2017). Mobile computing and communications: An introduction. Malaysian Journal of Computer Science,12(02), 71–78.

  2. 2.

    Bouazzouni, M. A., Conchon, E., & Peyrard, F. (2018). Trusted mobile computing: An overview of existing solutions. Journal of Future Generation Computer Systems,80, 596–612.

  3. 3.

    Sivakumaran, M. Iacopino, P. (2018). The mobile economy 2018. Retrieved April 21, 2018, from https://www.gsmaintelligence.com/research/2018/02/the-mobile-economy-2018/660/.

  4. 4.

    Statista. (2015). Mobile phone users worldwide 2013–2019. Retrieved April 21, 2018, from https://www.statista.com/statistics/274774/forecast-of-mobile-phone-users-worldwide/.

  5. 5.

    Mollah, M. B., Azad, M. A. K., & Vasilakos, A. (2017). Security and privacy challenges in mobile cloud computing: Survey and way ahead. Journal of Network and Computer Applications,84, 38–54.

  6. 6.

    Paranjothi, A., Khan, M. S., & Nijim, M. (2017). Survey on three components of mobile cloud computing: Offloading, distribution, and privacy. Journal of Computer and Communications,05(06), 1–31.

  7. 7.

    Sharma, M., & Kumari, R. (2018). Survey on mobile cloud computing: Applications, techniques, and issues. International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT),03(01), 933–940.

  8. 8.

    Weng, W. H., & Lin, W. T. (2015). A mobile computing technology foresight study with scenario planning approach. International Journal of Electronic Commerce Studies,06(02), 223–232.

  9. 9.

    Moghaddam, F. F., Ahmadi, M., Sarvari, S., Eslami, M., & Golkar, A. (2015). Cloud Computing Challenges and Opportunities: A survey. In IEEE 1st international conference on telematics and future generation networks (TAFGEN), 2015 (pp. 34–38).

  10. 10.

    Goyal, S. (2014). Public vs private vs hybrid vs community-cloud computing: A critical review. International Journal of Computer Network and Information Security,06(03), 20–29.

  11. 11.

    Moura, J., & Hutchison, D. (2016). Review and analysis of networking challenges in cloud computing. Journal of Network and Computer Applications,60, 113–129.

  12. 12.

    Ahmed, A. A., & Wendy, K. (2017). Mutual authentication for mobile cloud computing: Review and suggestion. In IEEE conference on application, information and network security (AINS), 2017 (pp. 75–80).

  13. 13.

    Stamford, Conn. (2016). Gartner says by 2020 “cloud shift” will affect more than $1 trillion in IT spending. Retrieved April 22, 2018, from http://www.gartner.com/newsroom/id/3384720.

  14. 14.

    Sadiku, M. N., Musa, S. M., & Momoh, O. D. (2014). Cloud computing: Opportunities and challenges. IEEE Potentials,33(01), 34–36.

  15. 15.

    Puthal, D., Sahoo, B. P. S., Mishra, S., & Swain, S. (2015). Cloud computing features, issues, and challenges: A big picture. In IEEE international conference on computational intelligence and networks (CINE), 2015 (pp. 116–123).

  16. 16.

    Xiao, Z., & Xiao, Y. (2013). Security and privacy in cloud computing. IEEE Communications Surveys & Tutorials,15(02), 843–859.

  17. 17.

    Wang, S., Liu, Z., Sun, Q., Zou, H., & Yang, F. (2014). Towards an accurate evaluation of quality of cloud service in service-oriented cloud computing. Journal of Intelligent Manufacturing,25(02), 283–291.

  18. 18.

    Toosi, A. N., Calheiros, R. N., & Buyya, R. (2014). Interconnected cloud computing environments: Challenges, taxonomy, and survey. ACM Computing Surveys (CSUR),47(01), 1–47.

  19. 19.

    Shawish, A., & Salama, M. (2014). Cloud computing: paradigms and technologies. In: F. Xhafa, N. Bessis (Eds.), Inter-cooperative collective intelligence: Techniques and applications (pp. 39–67). Heidelberg: Springer.

  20. 20.

    Alam, M. I., Pandey, M., & Rautaray, S. S. (2015). A comprehensive survey on cloud computing. International Journal of Information Technology and Computer Science,2, 68–79.

  21. 21.

    Durao, F., Carvalho, J. F. S., Fonseka, A., & Garcia, V. C. (2014). A systematic review on cloud computing. The Journal of Supercomputing,68(03), 1321–1346.

  22. 22.

    Nandgaonkar, S. V., & Raut, A. B. (2014). A comprehensive study on cloud computing. International Journal of Computer Science and Mobile Computing,03(04), 733–738.

  23. 23.

    Branch, R., Tjeerdsma, H., Wilson, C., Hurley, R., & McConnell, S. (2014). Cloud computing and big data: A review of current service models and hardware perspectives. Journal of Software Engineering and Applications.,07(08), 686–693.

  24. 24.

    Chen, M. H., Dong, M., & Liang, B. (2018). Resource sharing of a computing access point for multi-user mobile cloud offloading with delay constraints. IEEE Transactions on Mobile Computing, 17(12), 2868–2881.

  25. 25.

    Chen, M. H., Liang, B., & Dong, M. (2017). Joint offloading and resource allocation for computation and communication in mobile cloud with computing access point. In IEEE conference on INFOCOM 2017-computer communications, IEEE (pp. 1–9).

  26. 26.

    Li, R., Shen, C., He, H., Xu, Z., & Xu, C. Z. (2017). A lightweight secure data sharing scheme for mobile cloud computing. IEEE Transactions on Cloud Computing, 06(02), 344–357.

  27. 27.

    Rahimi, M. R., Ren, J., Liu, C. H., Vasilakos, A. V., & Venkatasubramanian, N. (2014). Mobile cloud computing: A survey, state of art and future directions. Journal of Mobile Networks and Applications.,19(02), 133–143.

  28. 28.

    Kumar, G., Jain, E., Goel, S., & Panchal, V. K. (2014). Mobile cloud computing architecture, application model, and challenging issues. In IEEE international conference on computational intelligence and communication networks (CICN), 2014 (pp. 613–617).

  29. 29.

    Yan, Z., Li, X., & Kantola, R. (2017). Heterogeneous data access control based on trust and reputation in mobile cloud computing. In Advances in mobile cloud computing and big data in the 5G era (pp. 65–113). Cham: Springer.

  30. 30.

    Wu, X. (2018). Context-aware cloud service selection model for mobile cloud computing environments. Hindawi Journal of Wireless Communications and Mobile Computing, 1–14.

  31. 31.

    Fernando, N., Loke, S. W., & Rahayu, W. (2013). Mobile cloud computing: A survey. Journal of Future Generation Computer Systems,29(01), 84–106.

  32. 32.

    Marcelino, L., & Silva, C. (2018). Location privacy concerns in mobile applications. In Developments and advances in intelligent systems and applications (pp. 241–249). Cham: Springer.

  33. 33.

    Andrés, M. E., Bordenabe, N. E., Chatzikokolakis, K., & Palamidessi, C. (2013). Geo-indistinguishability: Differential privacy for location-based systems. In ACM proceedings of the 2013 ACM SIGSAC conference on computer & communications security (pp. 901–914).

  34. 34.

    Singhal, M., & Shukla, A. (2012). Implementation of location based services in android using GPS and web services. IJCSI International Journal of Computer Science Issues,09(01), 237–242.

  35. 35.

    Shankar, P., Huang, Y. W., Castro, P., Nath, B., & Iftode, L. (2012). Crowds replace experts: Building better location-based services using mobile social network interactions. In IEEE international conference on pervasive computing and communications (PerCom), 2012 (pp. 20–29).

  36. 36.

    Li, X. Y., & Jung, T. (2013). Search me if you can: Privacy-preserving location query service. In IEEE proceedings of INFOCOM, 2013 (pp. 2760–2768).

  37. 37.

    Shao, J., Lu, R., & Lin, X. (2014, April). Fine: A fine-grained privacy-preserving location-based service framework for mobile devices. In IEEE proceedings of INFOCOM, 2014 (pp. 244–252).

  38. 38.

    Zhu, Y., Ma, D., Huang, D., & Hu, C. (2013). Enabling secure location-based services in mobile cloud computing. In ACM proceedings of the second ACM SIGCOMM workshop on mobile cloud computing, (pp. 27–32).

  39. 39.

    Tang, F., Li, J., You, I., & Guo, M. (2016). Long-term location privacy protection for location-based services in mobile cloud computing. Journal of Soft Computing,20(05), 1735–1747.

  40. 40.

    He, T., Ciftcioglu, E. N., Wang, S., & Chan, K. S. (2017). Location privacy in mobile edge clouds: A chaff-based approach. IEEE Journal on Selected Areas in Communications,35(11), 2625–2636.

  41. 41.

    Wang, S., Hu, Q., Sun, Y., & Huang, J. (2018). Privacy preservation in location-based services. IEEE Communications Magazine,56(03), 134–140.

  42. 42.

    Wang, T., Zeng, J., Bhuiyan, M. Z. A., Tian, H., Cai, Y., Chen, Y., et al. (2017). Trajectory privacy preservation based on a fog structure for Cloud location services. IEEE Access,05, 7692–7701.

  43. 43.

    Sun, G., Xie, Y., Liao, D., Yu, H., & Chang, V. (2017). User-defined privacy location-sharing system in mobile online social networks. Journal of Network and Computer Applications,86, 34–45.

  44. 44.

    Wernke, M., Skvortsov, P., Dürr, F., & Rothermel, K. (2014). A classification of location privacy attacks and approaches. Pers Personal and Ubiquitous Computing,18(01), 163–175.

  45. 45.

    Niu, B., Li, Q., Zhu, X., Cao, G., & Li, H. (2014). Achieving k-Anonymity in Privacy-Aware Location-Based Services. In IEEE Proceedings of INFOCOM, 2014 (pp. 754–762).

  46. 46.

    Abbas, F., Hussain, R., Son, J., & Oh, H. (2013). Privacy preserving cloud-based computing platform (PPCCP) for using location based services. IEEE Computer Society. In Proceedings of the 2013 IEEE/ACM 6th international conference on utility and cloud computing, 2013 (pp. 60–66).

  47. 47.

    Paulet, R., Kaosar, M. G., Yi, X., & Bertino, E. (2014). Privacy-preserving and content-protecting location based queries. IEEE Transactions on Knowledge and Data Engineering,26(05), 1200–1210.

  48. 48.

    Jagwani, P., & Kaushik, S. (2017). Privacy in location based services: Protection strategies, attack models and open challenges. In International conference on information science and applications, 2017 (pp. 12–21). Berlin: Springer.

  49. 49.

    Puttaswamy, K. P., & Zhao, B. Y. (2010). Preserving privacy in location-based mobile social applications. In ACM proceedings of the eleventh workshop on mobile computing systems & applications, 2010 (pp. 1–6).

  50. 50.

    Chen, Y. J., & Wang, L. C. (2011). A security framework of group location-based mobile applications in cloud computing. In IEEE 40th international conference on parallel processing workshops (ICPPW), 2011 (pp. 184–190).

  51. 51.

    Jagwani, P., & Kaushik, S. (2012). Defending location privacy using zero knowledge proof concept in location based services. In IEEE 13th international conference on mobile data management (MDM), 2012 (pp. 368–371).

  52. 52.

    Li, W., Jiao, W., & Li, G. (2012, October). A location privacy preserving algorithm for mobile LBS. In IEEE 2nd international conference on cloud computing and intelligent systems (CCIS), 2012, 02, (pp. 548–552).

  53. 53.

    Yao, L., Wu, G., Wang, J., Xia, F., Lin, C., & Wang, G. (2012). A clustering K-anonymity scheme for location privacy preservation. IEICE Transactions on Information and Systems,95(01), 134–142.

  54. 54.

    Sun, Y., Chen, M., Hu, L., Qian, Y., & Hassan, M. M. (2017). ASA: Against statistical attacks for privacy-aware users in location based service. Journal of Future Generation Computer Systems,70, 48–58.

  55. 55.

    Xiao, X., Chen, C., Sangaiah, A. K., Hu, G., Ye, R., & Jiang, Y. (2017). CenLocShare: A centralized privacy-preserving location-sharing system for mobile online social networks. Elsevier Journal of Future Generation Computer Systems.

  56. 56.

    Peng, T., Liu, Q., & Wang, G. (2017). Enhanced location privacy preserving scheme in location-based services. IEEE Systems Journal,11(01), 219–230.

  57. 57.

    Rohilla, A., Khurana, M., & Singh, L. (2017). Location privacy using homomorphic encryption over cloud. Proquest International Journal of Computer Network and Information Security,09(08), 32–40.

  58. 58.

    Wu, H., Wang, L., & Jiang, T. (2018). Secure and efficient k-nearest neighbor query for location-based services in outsourced environments. Science Journal of China Information Sciences, 61(03), 1–3.

  59. 59.

    Rivest, R. L., Adleman, L., & Dertouzos, M. L. (1978). On data banks and privacy homomorphisms. Foundations of Secure Computation,04(11), 169–180.

  60. 60.

    Gentry, C. (2009). A fully homomorphic encryption scheme. Ph.D. Thesis Stanford University.

  61. 61.

    Fang, S. H., Lai, W. C., & Lee, C. M. (2012). Privacy considerations for cloud-based positioning. In IEEE 2012 12th international conference on ITS telecommunications (ITST), 2012 (pp. 527–531).

  62. 62.

    Zhu, H., Lu, R., Huang, C., Chen, L., & Li, H. (2016). An efficient privacy-preserving location-based services query scheme in outsourced cloud. IEEE Transactions on Vehicular Technology,65(09), 7729–7739.

  63. 63.

    Sahai, A., & Waters, B. (2005). Fuzzy identity-based encryption. In Advances in cryptology- eurocrypt, Volume 3494 of LNCS, (pp. 457–473). Berlin: Springer.

  64. 64.

    Goyal, V., Pandey, O., Sahai, A., & Waters, B. (2006). Attribute-based encryption for fine-grained access control of encrypted data. In ACM proceedings of the 13th ACM conference on computer and communications security, 2006 (pp. 89–98).

  65. 65.

    Bethencourt, J., Sahai, A., & Waters, B. (2007). Ciphertext-policy attribute-based encryption. In IEEE symposium on security and privacy, 2007 (pp. 321–334).

  66. 66.

    Baseri, Y., Hafid, A., & Cherkaoui, S. (2016). K-anonymous location-based fine-grained access control for mobile cloud. In 13th IEEE annual consumer communications & networking conference (CCNC), 2016 (pp. 720–725).

  67. 67.

    Jung, T., Li, X. Y., Wan, Z., & Wan, M. (2015). Control cloud data access privilege and anonymity with fully anonymous attribute-based encryption. IEEE Transactions on Information Forensics and Security,10(01), 190–199.

  68. 68.

    Xie, Q., & Wang, L. (2016). Efficient privacy-preserving processing scheme for location-based queries in mobile cloud. In IEEE international conference on data science in cyberspace (DSC), 2016 (pp. 424–429).

  69. 69.

    Rivest, R. L., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM.,21(02), 120–126.

  70. 70.

    Patil, V., Parikh, S., Singh, P., & Atrey, P. K. (2017). GeoSecure: Towards secure outsourcing of GPS data over cloud. In IEEE conference on communications and network security (CNS), 2017 (pp. 495–501).

  71. 71.

    Baseri, Y., Hafid, A., & Cherkaoui, S. (2018). Privacy preserving fine-grained location-based access control for mobile cloud. Journal of Computers & Security,73, 249–265.

  72. 72.

    Zhu, X., Ayday, E., & Vitenberg, R. (2018). A privacy-preserving framework for outsourcing location-based services to the cloud. Research report http://urn. nb.no/URN: NBN: no-35645.

  73. 73.

    Ou, L., Yin, H., Qin, Z., Xiao, S., Yang, G., & Hu, Y. (2018). An efficient and privacy-preserving multiuser cloud-based lbs query scheme. In Security and communication networks, (pp. 1–11).

  74. 74.

    Almusaylim, Z. A., & Zaman, N. (2018). A review on smart home present state and challenges: linked to context-awareness internet of things (IoT). Journal of Wireless Networks, 1–12.

  75. 75.

    Almusaylim, Z. A., Zaman, N., & Jung, L. T. (2018, August). Proposing a data privacy aware protocol for roadside accident video reporting service using 5G in Vehicular Cloud Networks Environment. In IEEE In 2018 4th International Conference on Computer and Information Sciences (ICCOINS) (pp. 1–5).

  76. 76.

    Iu, D., Gao, X., & Wang, H. (2017). Location privacy breach: Apps are watching you in background. In IEEE 37th international conference on distributed computing systems (ICDCS), 2017 (pp. 2423–2429).

  77. 77.

    ​Kiess, K. (2017). Mappenstance: Snap map is more than just a map. Retrieved May 23, 2018, from https://blog.richmond.edu/livesofmaps/2017/11/03/snap-map-is-more-than-just-a-map/.

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Correspondence to Zahrah A. Almusaylim.

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A. Almusaylim, Z., Jhanjhi, N. Comprehensive Review: Privacy Protection of User in Location-Aware Services of Mobile Cloud Computing. Wireless Pers Commun 111, 541–564 (2020). https://doi.org/10.1007/s11277-019-06872-3

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Keywords

  • Mobile computing
  • Cloud computing
  • Mobile cloud computing
  • LBS
  • Location-aware
  • Privacy
  • Encryptions