An efficient secure sum of multi-scalar products protocol base on elliptic curve

Tóm tắt

Lượt tải theo tháng

Cách trích dẫn

Vu Thi Van, Luong The Dung, Hoang Van Quan, Tran Thi Luong (2021). An efficient secure sum of multi-scalar products protocol base on elliptic curve. Tạp chí Khoa học và Công nghệ trong lĩnh vực An toàn thông tin, 2(14), 18-25. https://doi.org/10.54654/isj.v14i2.196

Tài liệu tham khảo

1. 1.David Evans, Vladimir Kolesnikov and Mike Rosulek, A Pragmatic Introduction to Secure Multi-Party Computation, NOW Publishers, 2018.
2. 2.O. Goldreich., The Foundations of Cryptography, volume 2, Cambridge University Press, 2004.
3. 3.Dong, Changyu and Chen, Liqun, "A Fast Secure Dot Product Protocol with Application to Privacy Preserving Association Rule Mining," in Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2014.
4. 4.Y. Zhu,T. Takagi, "Efficient scalar product protocol and its privacypreserving application," in International J. of Electronic Security and Digital Forensics, Vol. 7, No. 1, 2015.
5. 5.Clifton, Chris and Kantarcioglu, Murat and Vaidya, Jaideep and Lin, Xiaodong and Zhu, Michael Y, "Tools for privacy preserving distributed data mining," ACM Sigkdd Explorations Newsletter, vol. 4, no. 2, pp. 28-34, 2002.
6. 6.Goethals, Bart and Laur, Sven and Lipmaa, Helger and Mielikäinen, Taneli, "On private scalar product computation for privacy-preserving data mining," in International Conference on Information Security and Cryptology, 2004.
7. 7.Atallah M J, Du W, "Secure multiparty computational geometry," in Proc. the 7th International Workshop on Algorithms, 2011.
8. 8.Yang B, Sun A D, Zhang W Z, "Secure two-party protocols on planar circles," Journal of Information & Computational, vol. 8, no. 1, pp. 29-40, 2011.
9. 9.Babak Siabi, Mehdi Berenjkoub, Willy Susilo, "Optimally Efficient Secure Scalar Product With Applications in Cloud Computing," IEEE Access, vol. 7, no. 1, pp. 42798 - 42815, 29 3 2019.
10. 10.Zhang J, Li L, Tang Y, Luo S, Yang Y, Xin Y, "Secure two-party computation of solid triangle area and tetrahedral volume based on cloud platform," PLoS One, Public Library of Science, vol. 14, no. 1, pp. 1-22, 2019.
11. 11.Y. Rahulamathavan, S. Dogan, X. Shi, R. Lu, M. Rajarajan and A. Kondoz, "Scalar Product Lattice Computation for Efficient Privacy-preserving Systems," IEEE Internet of Things Journal, vol. 8, no. 3, pp. 1417-1427, 2021.
12. 12.Mehnaz, Shagufta and Bellala, Gowtham and Bertino, Elisa, "A secure sum protocol and its application to privacy-preserving multi-party analytics," in Proceedings of the 22nd ACM on Symposium on Access Control Models and Technologies, 2017.
13. 13.Duy-Hien, Vu and The-Dung, Luong and Tu-Bao, Ho, "An Efficient Approach for Secure Multi-party Computation without Authenticated Channel," Information Science, 2019.
14. 14.The-Dung, Luong and Tu-Bao, Ho, "Privacy preserving frequency mining in 2-part fully distributed setting," IEICE TRANSACTIONS on Information and Systems, vol. 93, no. 10, pp. 2702-2708, 2010.
15. 15.Thi Van Vu, The Dung Luong, Van Quan Hoang, "An Elliptic Curve-based Protocol for Privacy Preserving Frequency Computation in 2-Part Fully Distributed Setting," in 12th International Conference on Knowledge and Systems Engineering (KSE), Can Tho, 2020.
16. 16.Luong The Dung, Vu Duy Hien, Vu Thi Van, "A new Approach for secure multi-party computation protocol," Journal of Military Science and Technology, vol. Information security special, 2019.

Bài viết liên quan

• Một số cải tiến cho các kiểm tra thống kê tính ngẫu nhiên sử dụng so khớp mẫu
• Algorithm for detecting attacks on Web applications based on machine learning methods and attributes queries
• Các ma trận MDS truy hồi hiệu quả cho thực thi từ mã Reed-Solomon và phép lũy thừa trực tiếp
• Static Feature Selection for IoT Malware Detection
• Bài viết #447
• Privacy-Preserving Decision Tree Solution in the 2-Part Fully Distributed Setting