Rounding in the Rings

报告时间：2021年2月3日  09:30-11:30

报告平台：腾讯会议 （会议ID ：566 103 038）

主办单位：bevitor伟德官网 网络信息安全团队

报告内容简介：Learning with Rounding (LWR) is an important variant of Learning with Error (LWE) used in post-quantum crypto designs. Toward efficiency, cryptographers proposed to use additional ring structures to improve practical parameters. Yet the additional math structures at the same time might face security subtleties an attacker might exploit. It is therefore important to determine whether we can enjoy the efficiency improvements from rings and still have convincing security guarantees.

In this talk, we will present a comprehensive study on hardness reductions for (Module) Learning with Rounding over rings (RLWR), particularly an overview of existing results and our new results.

报告人简介：汪哲东，美国佛罗里达大西洋大学博士后研究员。2019年获得中国科学院信息工程研究所获得博士学位。汪哲东博士的研究方向包括密码学、理论计算机科学，尤其是在抗泄露公钥密码、基于格的公钥密码方案设计方面做出了出色的工作，其研究成果已经被成功录用和发表于相关领域的顶级会议CRYPTO、Eurocrypt、PKC等。