Visualising Personal Data Flows: Insights from a Case Study of Booking.com

Author:

Yuan HaiyueORCID,Boakes MatthewORCID,Ma Xiao,Cao DongmeiORCID,Li ShujunORCID

Publisher

Springer International Publishing

Reference14 articles.

1. Andow, B., et al.: PolicyLint: investigating internal privacy policy contradictions on Google Play. In: Proceedings of USENIX Security 2019, pp. 585–602 (2019). https://www.usenix.org/conference/usenixsecurity19/presentation/andow

2. Communications in Computer and Information Science;V Bracamonte,2022

3. Carlsson, R., et al.: Where does your data go? comparing network traffic and privacy policies of public sector mobile applications. In: Proceedings of WorldCIST 2022, vol. 1. pp. 214–225. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-04826-5_21

4. Fallatah, K.U., et al.: Personal data stores (PDS): a review. Sensors 23(3) (2023). https://doi.org/10.3390/s23031477

5. Harkous, H., et al.: Polisis: automated analysis and presentation of privacy policies using deep learning. In: Proceedings of USENIX Security 2018, pp. 531–548 (2018). https://www.usenix.org/conference/usenixsecurity18/presentation/harkous

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