Secure and efficient multiparty private set intersection cardinality

In the field of privacy preserving protocols, Private Set Intersection (PSI) plays an important role. In most cases, PSI allows two parties to securely determine intersection their private input sets, and no other information. this paper, employing a Bloom filter, we propose Multiparty Cardinality (MPSI-CA), where number participants in is not limited two. The security our scheme achieved standard model under Decisional Diffie-Hellman (DDH) assumption against semi-honest adversaries. Our flexible sense that set size one participant independent from others. We consider modular exponentiations order computational complexity. construction, communication computation overheads each \begin{document}$ O(v_{\sf max}k) $\end{document} except complexity designated party id="M2">\begin{document}$ O(v_1) $\end{document}, id="M3">\begin{document}$ v_{\sf max} maximum size, id="M4">\begin{document}$ v_1 denotes id="M5">\begin{document}$ k parameter. Particularly, MSPI-CA first incurs linear terms namely id="M6">\begin{document}$ O(nv_{\sf id="M7">\begin{document}$ n participants. Further, extend MPSI-CA MPSI retaining all attributes properties. As far as are aware of, there so individual cost Unlike MPSI-CA, does require any kind broadcast channel it uses star network topology communicates with everyone else.