Abstract
Location-based services (LBSs) are widely deployed in commercial services. These services always depend on a service provider, e.g., a cloud server, to store the enormous amounts of geospatial data and to process various queries. For example, a Yelp user can retrieve a list of recommended cafés by submitting her/his current location to the service provider. While LBSs offer tremendous benefits, it is vital to safeguard users’ privacy against untrusted service providers. However, no prior secure k nearest neighbor query processing schemes satisfy the three security requirements of one-time, oblivious, and unlinkable. In particular, we are concerned with the problem of item exclusion: how to match one data query with each item on the cloud no more than once in an oblivious and unlinkable manner. In this paper, we propose the first secure k nearest neighbor query processing scheme, Obaq, that satisfies the above requirements. Obaq first introduces an item identifier into an existing secure k nearest neighbor query processing scheme. Each data owner inserts an item identifier and her/his location information into a secure index, and each data user transfers the identifier of a previously received data item and location information into a specific range. Then, Obaq excludes corresponding items via privacy-preserving range querying. We define strong index privacy and strong token privacy and formally prove the security of Obaq in the random oracle model. We further evaluate the performance of Obaq using a prototype and a real-world dataset. The experimental results show that Obaq is highly efficient and practical in terms of computational cost, communication overhead, and response delay.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhu, L., Li, M., Zhang, Z., Qin, Z.: ASAP: An anonymous smart-parking and payment scheme in vehicular networks. IEEE Trans. Dependable Secure Comput. (TDSC) PP(99), 1–12 (2018). https://doi.org/10.1109/TDSC.2018.2850780
Li, M., Zhu, L., Lin, X.: Efficient and privacy-preserving carpooling using blockchain-assisted vehicular fog computing. IEEE Internet Things J. (IoTJ) 6(3), 4573–4584 (2019). https://doi.org/10.1109/JIOT.2018.2868076
Li, M., Zhu, L., Lin, X.: Privacy-preserving traffic monitoring with false report filtering via fog-assisted vehicular crowdsensing. IEEE Trans. Serv. Comput. (TSC) PP(99), 1–11 (2019). https://doi.org/10.1109/TSC.2019.2903060
Zhu, L., Li, M., Zhang, Z., Du, X., Guizani, M.: Big data mining of users’ energy consumption pattern in wireless smart grid. IEEE Wirel. Commun. 25(1), 84–89 (2018)
Li, M., Hu, D., Lal, C., Conti, M., Zhang, Z.: Blockchain-enabled secure energy trading with verifiable fairness in Industrial Internet of Things. IEEE Trans. Ind. Inf. (TII) PP(99), 1–13 (2020). https://doi.org/10.1109/TII.2020.2974537
Zhu, L., Li, M., Zhang, Z.: Secure fog-assisted crowdsensing with collusion resistance: from data reporting to data requesting. IEEE Internet Things J. (IoTJ) 6(3), 5473–5484 (2019). https://doi.org/10.1109/JIOT.2019.2902459
Yang, C., Wang, J., Tao, X., Chen, X.: Publicly verifiable data transfer and deletion scheme for cloud storage. In: Proceedings of 20th International Conference on Information and Communications Security (ICICS), Lille, France, pp. 445–458, October 2018
Zhao, Z., Luo, W., Shen, Q., Ruan, A.: CloudCoT: a blockchain-based cloud service dependency attestation framework. In: Proceedings of 21st International Conference on Information and Communications Security (ICICS), Beijing, China, December 2019
Danger within: defending cloud environments against insider threats (2018). https://www.cloudcomputing-news.net/news/2018/may/01/danger-within-defen ding-cloud-environments-against-insider-threats
7 Most Infamous Cloud Security Breaches (2017). https://blog.storagecraft.com/7-infamous-cloud-security-breaches
Wong, W.K., Cheung, D.W., Kao, B., Mamoulis, N.: Secure kNN computation on encrypted databases. In: Proceedings of 35th ACM SIGMOD International Conference on Management of Data (SIGMOD), Providence, USA, pp. 139–152, June 2009
Elmehdwi, Y., Samanthula, B.K., Jiang, W.: Secure k-nearest neighbor query over encrypted data in outsourced environment. In: Proceedings of IEEE 30rd International Conference on Data Engineering (ICDE), Chicago, USA, pp. 664–675, March 2014
Li, R., Liu, A., Wang, A.L., Bruhadeshwar, B.: Fast range query processing with strong privacy protection for cloud computing. In: Proceedings of 40th International Conference on Very Large Data Bases (VLDB), Hangzhou, China, pp. 1953–1964, September 2014
Li, R., Liu, A.X.: Adaptively secure conjunctive query processing over encrypted data for cloud computing. In: Proceedings of IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, USA, pp. 697–708, April 2017
Secure KNN queries over encrypted data: dimensionality is not always a curse. In: Proceedings of IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, USA, pp. 231–234, April 2017
Lei, X., Liu, A.X., Li, R., Tu, G.-H.: SecEQP: a secure and efficient scheme for SkNN query problem over encrypted geodata on cloud. In: Proceedings of 35th IEEE International Conference on Data Engineering (ICDE), Macao, China, pp. 662–673, April 2019
Wang, B., Hou, Y., Li, M.: Practical and secure nearest neighbor search on encrypted large-scale data. In: Proceedings of 35th Annual IEEE International Conference on Computer Communications (INFOCOM), San Francisco, USA, pp. 1–9, April 2016
Kornaropoulos, E.M., Papamanthou, C., Tamassia, R.: Data recovery on encrypted databases with k-nearest neighbor query leakage. In: Proceedings of 40th IEEE Symposium on Security and Privacy (SP), San Francisco, USA, pp. 1033–1050, May 2019
Liu, A.X., Chen, F.: Collaborative enforcement of firewall policies in virtual private networks. In: Proceedings of 27th ACM Symposium on Principles of Distributed Computing (PODC), Canada, Toronto, pp. 95–104, August 2008
Canetti, R., Feige, U., Goldreich, O., Naor, M.: Adaptively secure multi-party computation. In: Proceedings of 28th ACM Symposium on Theory of Computing (STOC), Philadelphia, USA, pp. 639–648, May 1996
Song, D.X. Wagner, D., Perrig, A.: Practical techniques for searches on encrypted data. In: Proceedings of 21st IEEE Symposium on Security and Privacy (S&P), San Francisco, USA, pp. 44–55, May 2000
Boldyreva, A., Chenette, N., O’Neill, A.: Order-preserving encryption revisited: improved security analysis and alternative solutions. In: Proceedings of 31st Annual Cryptology Conference (CRYPTO), Santa Barbara, USA, pp. 578–595, August 2011
Kamara, S., Papamanthou, C., Roeder, T.: Dynamic searchable symmetric encryption. In: Proceedings of 19th ACM Conference on Computer and Communications Security (CCS), Raleigh, USA, pp. 965–976, October 2012
Cash, D., et al.: Dynamic searchable encryption in very-large databases: data structures and implementation. In: Proceedinhs of 21st Annual Network and Distributed System Security Symposium (NDSS), San Diego, USA, pp. 1–16, February 2014
Curtmola, R., Garay, J., Kamara, S., Ostrovsky, R.: Searchable symmetric encryption: improved definitions and efficient constructions. In: Proceedings of 13th ACM Computer and Communications Security Conference (CCS), Alexandria, USA, pp. 79–88, November 2006
Katz, J., Lindell, Y.: Introduction to Modern Cryptography, 2nd edn. CRC Press, Boca Raton (2015)
Openstreetmap. http://www.openstreetmap.org
The Java Pairing Based Cryptography Library (JPBC). http://gas.dia.unisa.it/projects/jpbc/index.html
Acknowledgements
This work is supported by Anhui Provincial Natural Science Foundation under the grant No. 2008085MF196, National Natural Science Foundation of China (NSFC) under the grant No. 62002094, Anhui Science and Technology Key Special Program under the grant No. 201903a05020016, and National Natural Science Foundation of China (NSFC) under the grant No. U1836102. It is partially supported by EU LOCARD Project under Grant H2020-SU-SEC-2018-832735.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Chen, Y., Li, M., Zheng, S., Hu, D., Lal, C., Conti, M. (2020). One-Time, Oblivious, and Unlinkable Query Processing Over Encrypted Data on Cloud. In: Meng, W., Gollmann, D., Jensen, C.D., Zhou, J. (eds) Information and Communications Security. ICICS 2020. Lecture Notes in Computer Science(), vol 12282. Springer, Cham. https://doi.org/10.1007/978-3-030-61078-4_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-61078-4_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-61077-7
Online ISBN: 978-3-030-61078-4
eBook Packages: Computer ScienceComputer Science (R0)