学术报告

学术报告

您当前所在位置: 首页 > 学术报告 > 正文
报告时间 2023年11月19日上午9:00-10:30 报告地点 腾讯会议650981416
报告人 来齐齐

报告题目:Ring/Module Learning with Errors under Linear Leakage -- Hardness and Applications

报告人:来齐齐 副教授 陕西师范大学

邀请人:李雪莲

报告时间:2023年11月19日上午9:00-10:30

报告地点:腾讯会议650981416

报告人简介:来齐齐,陕西师范大学计算机科学学院,副教授,硕士生导师。研究方向为后量子安全的公钥密码方案的设计与分析。2015年获得best365网页版登录官网密码学专业博士学位。目前,在国际密码学会顶级会议Eurocrypt,PKC等发表多篇论文。主持国家自然科学基金面上项目、青年项目各一项、ISN重点实验室开放课题一项、密码科学技术国家重点实验室开放课题一项、河南省网络密码技术重点实验室研究课题一项。获党政机要密码科学技术奖三等奖一项。

报告摘要:This work studies the hardness of decision Module Learning with Errors (MLWE) under linear leakage, which has been used as a foundation to derive more efficient lattice-based zero-knowledge proofs in a recent paradigm of Lyubashevsky, Nguyen, and Seiler (PKC 21), Lyubashevsky, Nguyen, and Plancon (CRYPTO 22). Unlike in the plain LWE setting, it was unknown whether this problem remains provably hard in the module/ring setting.

This work shows a reduction from the search MLWE to decision MLWE with linear leakage. Thus, the main problem remains hard asymptotically as long as the non-leakage version of MLWE is hard. Additionally, we also refine the paradigm of Lyubashevsky, Nguyen, and Seiler (PKC 21), Lyubashevsky, Nguyen, and Plancon (CRYPTO 22) by showing a more fine-grained tradeoff between efficiency and leakage. This can lead to further optimizations of lattice proofs under the paradigm.。

主办单位:best365网页版登录官网

上一篇:Generalized Homogenization of Linear Controllers: Theory and Experiments

下一篇:Convergence analysis on the particle systems with centralized control

关闭

Baidu
sogou