Secure planar convex hull protocol for large-scaled point sets in semi-honest model

Efficiency and scalability are still the bottleneck for secure multi-party computation geometry (SMCG). In this work a secure planar convex hull (SPCH) protocol for large-scaled point sets in semi-honest model has been proposed efficiently to solve the above problems. Firstly, a novel privacy-preserving point-inclusion (PPPI) protocol is designed based on the classic homomorphic encryption and secure cross product protocol, and it is demonstrated that the complexity of PPPI protocol is independent of the vertex size of the input convex hull. And then on the basis of the novel PPPI protocol, an effective SPCH protocol is presented. Analysis shows that this SPCH protocol has a good performance for large-scaled point sets compared with previous solutions. Moreover, analysis finds that the complexity of our SPCH protocol relies on the size of the points on the outermost layer of the input point sets only. Copyright © by HIGH TECHNOLOGY LETTERS PRESS.