報告人：許文盈 教授
報告題目：聯合錯誤數據注入攻擊下網絡化系統安全性研究
報告時間：2025年05月17日（周六）上午8:30
報告地點：騰訊會議411-195-263
主辦單位：數學與統計學院、數學研究院、科學技術研究院
報告人簡介：
許文盈，東南大學青年首席教授，博士生導師，入選德國洪堡學者，國家級青年人才。2017年獲香港城市大學博士學位，隨后在新加坡南洋理工大學、德國洪堡大學-波茨坦大氣研究所從事博士后。長期從事網絡系統智能協同控制的理論研究。以一作出版英文專著 1部，發表和錄用包括《IEEE TAC》長文在內的學術論文 70余篇(第一/通訊作者 40余篇)。主持/參與國家級省部級項目十余項，應邀在國際旗艦會議ICAISC和全國復雜網絡會議作大會報告，任國際權威期刊《IEEE Trans. Syst. Man Cybern. Syst.》、《Syst. Control Lett.》 等期刊編委。入選”斯坦福大學全球前2% 頂尖科學家榜單，仲英青年學者，獲吳文俊人工智能青年科技獎，江蘇省高層次人才培養計劃（“333工程”）第三層次培養對象，江蘇省數學成就獎，全國仿真創新應用大賽全國優秀指導教師等，指導學生獲第十四屆亞洲控制會議最佳學生論文、世界華人數學家大會創意本科論文獎等。
報告摘要：
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.