Abstract
To achieve the privacy protection on trajectory processing in outsourced environments, in this paper, we propose and demonstrate a Secure Trajectory Similarity Search System (SeTS\(^3\)) to process the similarity search on encrypted trajectories. We design our system with four layers following the non-colluded dual-cloud model. Based on our previous work, three secure trajectory similarity search algorithms, which support different similarity metrics, are implemented. To assist the secure computations on encrypted trajectories, we develop a cryptographic toolkit in SeTS\(^3\) based on Paillier cryptosystem. To achieve a better demonstration, we apply map APIs to visualize the trajectories, and the search performance of the implemented algorithms can be displayed.
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The code of this paper can be found in https://github.com/zfy1412/zzsource.
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References
Cui, N., Yang, X., Wang, B., Li, J., et al.: SVkNN: efficient secure and verifiable k-nearest neighbor query on the cloud platform. In: ICDE, pp. 253–264. IEEE (2020)
Liu, A., Zheng, K., Li, L., Liu, G., Zhao, L., Zhou, X.: Efficient secure similarity computation on encrypted trajectory data. In: ICDE, pp. 66–77. IEEE (2015)
Teng, Y., Shi, Z., Zhao, F., Ding, G., Xu, L., Fan, C.: Signature-based secure trajectory similarity search. In: IEEE TrustCom (2021, to appear)
Toohey, K., Duckham, M.: Trajectory similarity measures. ACM Sigspatial Spec. 7(1), 43–50 (2015)
Ta, N., Li, G., **e, Y., Li, C., Hao, S., Feng, J.: Signature-based trajectory similarity join. IEEE Trans. Knowl. Data Eng. 29(4), 870–883 (2017)
Ni, L.M., Chen, L., et al.: SHH-Taxi data (2007). https://www.cse.ust.hk/scrg/
Zheng, Y.: T-drive trajectory data (2011). https://www.microsoft.com/en-us/research/publication/t-drive-trajectory-data-sample/
Acknowledgement
The work is supported by National Natural Science Foundation of China (61902260), Scientific Research Project of Education Department of Liaoning Province (JYT2020026) and College Students’ Innovative Entrepreneurial Training Project of Shenyang Aerospace University (Z202110143136).
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Teng, Y., Zhao, F., Liu, J., Zhang, M., Duan, J., Shi, Z. (2022). SeTS\(^3\): A Secure Trajectory Similarity Search System. In: Bhattacharya, A., et al. Database Systems for Advanced Applications. DASFAA 2022. Lecture Notes in Computer Science, vol 13247. Springer, Cham. https://doi.org/10.1007/978-3-031-00129-1_48
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DOI: https://doi.org/10.1007/978-3-031-00129-1_48
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