Privacy-Preserving Cooperative Scientific Computations
CSFW '01 Proceedings of the 14th IEEE workshop on Computer Security Foundations
Secure two-party computational geometry
Journal of Computer Science and Technology
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
An Efficient Protocol for Secure Two-Party Computation in the Presence of Malicious Adversaries
EUROCRYPT '07 Proceedings of the 26th annual international conference on Advances in Cryptology
Efficient Robust Private Set Intersection
ACNS '09 Proceedings of the 7th International Conference on Applied Cryptography and Network Security
On the geometry of differential privacy
Proceedings of the forty-second ACM symposium on Theory of computing
Privacy-preserving data-oblivious geometric algorithms for geographic data
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
A two-party protocol with trusted initializer for computing the inner product
WISA'10 Proceedings of the 11th international conference on Information security applications
A privacy preserving efficient protocol for semantic similarity join using long string attributes
Proceedings of the 4th International Workshop on Privacy and Anonymity in the Information Society
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Intersection and union of convex polygons are basic issues in computational geometry, they can settle lots of matters such as economy and military affairs. To solve the problem that traditional method of making the polygons public could not satisfy the requirements of personal privacy, the protocol to compute intersection and union of convex polygons in secure two-party computation(STC) model was investigated. Along with the scan line algorithm and secret comparison protocol, the protocol completes the calculation without leaking so much information. The security and complexity analysis of the protocol are also given.