报告人：许文盈 教授
报告题目：联合错误数据注入攻击下网络化系统安全性研究
报告时间：2025年05月17日（周六）上午8:30
报告地点：腾讯会议411-195-263
主办单位：数学与统计学院、数学研究院、科学技术研究院
报告人简介：
许文盈，东南大学青年首席教授，博士生导师，入选德国洪堡学者，国家级青年人才。2017年获香港城市大学博士学位，随后在新加坡南洋理工大学、德国洪堡大学-波茨坦大气研究所从事博士后。长期从事网络系统智能协同控制的理论研究。以一作出版英文专著 1部，发表和录用包括《IEEE TAC》长文在内的学术论文 70余篇(第一/通讯作者 40余篇)。主持/参与国家级省部级项目十余项，应邀在国际旗舰会议ICAISC和全国复杂网络会议作大会报告，任国际权威期刊《IEEE Trans. Syst. Man Cybern. Syst.》、《Syst. Control Lett.》 等期刊编委。入选”斯坦福大学全球前2% 顶尖科学家榜单，仲英青年学者，获吴文俊人工智能青年科技奖，江苏省高层次人才培养计划（“333工程”）第三层次培养对象，江苏省数学成就奖，全国仿真创新应用大赛全国优秀指导教师等，指导学生获第十四届亚洲控制会议最佳学生论文、世界华人数学家大会创意本科论文奖等。
报告摘要：
We discuss the security issue in the state estimation problem for a networked control system (NCS). A new model of joint false data injection (FDI) attack is established wherein attacks are injected to both the remote estimator and the communication channels. Such a model is general that includes most existing FDI attack models as special cases. The joint FDI attacks are subjected to limited access and/or resource constraints, and this gives rise to a few attack scenarios to be examined one by one. Our objective is to establish the so-called insecurity conditions under which there exists an attack sequence capable of driving the estimation bias to infinity while bypassing the anomaly detector. By resorting to the generalized inverse theory, necessary and sufficient conditions are derived for the insecurity under different attack scenarios. Subsequently, easy-to-implement algorithms are proposed to generate attack sequences on insecure NCSs with respect to different attack scenarios. In particular, by using a matrix splitting technique, the constraint-induced sparsity of the attack vectors is dedicatedly investigated. Finally, several numerical examples are presented to verify the effectiveness of the proposed FDI attacks.