Semantic Privacy Inference Preservation Algorithm for Indoor Trajectory

Indoor location services have become an increasingly important part of our everyday lives in recent years. Despite the numerous benefits these services offer, serious concerns have arisen about the privacy of users’ locations. Adversaries can monitor user-requested locations in order to obtain sensitive information such as shopping patterns. Many users of indoor spaces want their movements and locations to be kept private so as not to reveal their visit to a particular zone inside buildings. Research on semantic indoor trajectory-based human movement data has primarily focused on finding routes without taking into account the protection of privacy. Hence, the servers on which trajectory data is stored are not completely secure. In this paper, we propose a semantic privacy inference preservation algorithm for an indoor trajectory that can issue path finding and navigation instructions while achieving good privacy protection of moving entities by generating ambiguous trajectory. The simulation of the proposed semantic indoor privacy algorithm was implemented in MATLAB.

@article{Alamri2023,
  title     = {Semantic Privacy Inference Preservation Algorithm for Indoor Trajectory},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {7},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Abdullah Alamri},
  doi       = {10.14569/IJACSA.2023.0140794},
  url       = {https://doi.org/10.14569/IJACSA.2023.0140794}
}