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A Privacy-Preserving Approach to Secure Location-Based Data

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Intelligent Computing and Information and Communication

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 673))

Abstract

There are number of sites that provide location-based services. Those sites use current location of user through the web applications or from the Wi-Fi devices. Sometimes, these sites will get permission to the user private information and resource on the web. These sites access user data without providing clear detail policies and disclosure of strategies. This will be used by the malicious sites or server or adversaries breaches the sensitive data and confidentiality of the user. User shares original context of the location. An adversary learns through the user’s original context. Due to the lack of secure privacy-preserving policies, it has shifted them to specific goals for various hazards. In order to secure or preserve privacy of user, new privacy-preserving technique called FakeIt is proposed. In FakeIt, system works around privacy, security to satisfy privacy requirements and the user decides context before sharing. If the current location context is sensitive to the user, then user decides to share the fake location context to location-based services instead of original. System restricts the adversaries to learn from the shared sensitive location context of the user.

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References

  1. Lichen Zhang, Zhipeng Cai, Xiaoming Wang, “FakeMask: A Novel Privacy Preserving Approach for Smartphones” IEEE Transactions on Network and Service Management, 2016. J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp. 68–73.

    Google Scholar 

  2. X. Liang, K. Zhang, X. Shen, and X. Lin, “Security and privacy in mobile social networks: challenges and solutions,” IEEE Wireless Communications, vol. 21, no. 1, pp. 33–41, 2014.

    Google Scholar 

  3. Y. Najaflou, B. Jedari, F. Xia, L. T. Yang, and M. S. Obaidat, “Safety challenges and solutions in mobile social networks,” IEEE Systems Journal, vol. 9, no. 3, pp. 834–854, 2015.

    Google Scholar 

  4. J. Tsai, P. G. Kelley, L. F. Cranor, and N. Sadeh, “Location sharing technologies: Privacy risks and controls,” I/S: A Journal of Law and Policy for the Information Societ, vol. 6, no. 2, pp. 119–317, 2010.

    Google Scholar 

  5. K. Vu, R. Zheng, and J. Gao, “Efficient algorithms for k-anonymous location privacy in participatory sensing,” in Proceedings of the 31st Annual IEEE International Conference on Computer Communications (INFOCOM’12), Orlando, FL, USA, March 25–30 2012, pp. 2399–2407.

    Google Scholar 

  6. Y. Wang, Z. Cai, G. Ying, Y. Gao, X. Tong, and G. Wu, “An incentive mechanism with privacy protection in mobile crowdsourcing systems,” ComputerNetwork., p. In Press, 2016.

    Google Scholar 

  7. M. Gotz, S. Nath, and J. Gehrke, “Maskit: Privately releasing user context streams for personalized mobile applications,” in Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD’12), Scottsdale, Arizona, USA, May 20–24 2012, pp. 289–300.

    Google Scholar 

  8. W. Wang and Q. Zhang, “A stochastic game for privacy preserving context sensing on mobile phone,” in Proceedings of the 33rd Annual IEEE International Conference on Computer Communications (INFOCOM’14), Toronto, Canada, April 27–May 2 2014, pp. 2328–2336.

    Google Scholar 

  9. J. Cappos, L. Wang, R. Weiss, Y. Yang, and Y. Zhuang, “Blursense: Dynamic fine-grained access control for smartphone privacy,” in Proceedings of the IEEE Sensors Applications Symposium (SAS’14), Queenstown, New Zealand, Febrary 18–20 2014, pp. 329–332.

    Google Scholar 

  10. B. Shebaro, O. Oluwatimi, and E. Bertino, “Context-based access control systems for mobile devices,” IEEE Transactions on Dependable and Secure Computing, vol. 12, no. 2, pp. 150–163, 2015.

    Google Scholar 

  11. Z. Pervaiz, W. G. Aref, A. Ghafoor, and N. Prabhu, “Accuracy constrained privacy preserving access control mechanism for relational data,” IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 4, pp. 795–807, 2014.

    Google Scholar 

  12. Rasika Pattewar and Jyoti Rao, “A Survey on Privacy Preserving Approaches for Location Based Data”, International Journal of Advanced Research in Computer and Communication Engineering, 240–243, Vol. 5, Issue 12, December 2016.

    Google Scholar 

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Acknowledgements

Success is never achieved single-handed. Apart from our humble efforts, this paper is outcome of the help, co-operation, and guidance from various corners. I would like to add a few heartfelt words for the people who were part of this in numerous ways and the people who gave unending support right from the stage of ideas.

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Correspondence to Jyoti Rao .

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Rao, J., Pattewar, R., Chhallani, R. (2018). A Privacy-Preserving Approach to Secure Location-Based Data. In: Bhalla, S., Bhateja, V., Chandavale, A., Hiwale, A., Satapathy, S. (eds) Intelligent Computing and Information and Communication. Advances in Intelligent Systems and Computing, vol 673. Springer, Singapore. https://doi.org/10.1007/978-981-10-7245-1_6

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  • DOI: https://doi.org/10.1007/978-981-10-7245-1_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7244-4

  • Online ISBN: 978-981-10-7245-1

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