Privacy-Preserving Ridesharing via Probabilistic Matching

Tianye Ma, Yukun Dong, Yidan Hu, Rui Zhang

Abstract: The widespread use of smartphones has made ridesharing a popular transportation option, connecting passengers with drivers seamlessly. However, existing ridesharing models raise privacy concerns as users must disclose their travel plans without assurance of a match. Previous privacy solutions are either impractical or insecure. To address this, we propose a novel privacy-preserving ridesharing mechanism based on probabilistic matching. Our approach ensures robust privacy protection for both drivers and riders while maintaining efficiency.

External IDs:dblp:conf/iwqos/MaDHZ24