Trajectory Privacy Protection Model Based on BiLSTM-GAN
[1]YAN Hongcan,ZHAO Yuting,LI Sijia,et al.Trajectory Privacy Protection Model Based on BiLSTM-GAN[J].Journal of Zhengzhou University (Engineering Science),2027,48(XX):1-8.[doi:10.13705/j.issn.1671-6833.2026.04.015]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
48
Number of periods:
2027 XX
Page number:
1-8
Column:
Public date:
2027-12-10
- Title:
- Trajectory Privacy Protection Model Based on BiLSTM-GAN
- Keywords:
- trajectory protection; hierarchical density-based spatial clustering of applications with noise (HDBSCAN); bidirectional long short-term memory network (BiLSTM); generative adversarial network (GAN); hidden Markov model (HMM); trajectory similarity
- CLC:
- TP309.2U495
- Abstract:
- The exponential growth of mobile trajectory data in location-based services has significantly increased the risk of user privacy leakage, making effective privacy protection mechanisms urgently necessary. To enhance the utility of trajectory data while ensuring privacy protection, a trajectory privacy protection model named TCI-BiGAN was constructed based on BiLSTM-GAN. The Bayesian optimization method was used to perform adaptive parameter tuning for hierarchical density-based spatial clustering of applications with noise(HDBSCAN), improving data processing efficiency and reducing trajectory redundancy. BiLSTM was embedded into both the generator and discriminator of the generative adversarial network to efficiently extract spatiotemporal features and capture dependencies of trajectory data through its contextual feature extraction capability, thereby enhancing the similarity between generated and real trajectories. A multivariate discrete hidden Markov model was applied for trajectory interpolation, increasing data completeness and utility. On the Foursquare NYC and T-Drive real-world datasets, the user trajectory linkage accuracy was reduced to 0.243 and 0.198, respectively, and the average Hausdorff distance between generated and real trajectories was decreased to 0.013 and 0.019, respectively.
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Last Update:
2026-04-08
