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

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

    Google Scholar 

  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.

    Article  Google Scholar 

  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. 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. 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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Google Scholar 

  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.

    Article  Google Scholar 

  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. 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.

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Chapter  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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. 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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

  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. 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. 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.

    Google Scholar 

  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. 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. 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. 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. 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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

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

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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. 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. 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.

    Article  Google Scholar 

  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. 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. 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. 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. 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. 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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

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

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Google Scholar 

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

    MathSciNet  Google Scholar 

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

  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. 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.

    Article  Google Scholar 

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

  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. 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.

    Article  Google Scholar 

  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. 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.

    Article  MathSciNet  MATH  Google Scholar 

  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. 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.

    Article  Google Scholar 

  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. 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. 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. 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. 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. ​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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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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