.png){kind=icon}
返回
Distributed Joint Attack Detection and Secure State Estimation
.png){kind=icon}
OA
AI
DOI：10.1109/TSIPN.2017.2760804.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The joint task of detecting attacks and securely monitoring the state of a cyber-physical system is addressed over a cluster-based network wherein multiple fusion nodes collect data from sensors and cooperate in a neighborwise fashion in order to accomplish the task. The attack detection-state estimation problem is formulated in the context of random set theory by representing joint information on the attack presence/absence, on the system state, and on the attack signal in terms of a hybrid Bernoulli random set (HBRS) density. Then, combining previous results on HBRS recursive Bayesian filtering with novel results on KullbackLeibler averaging of HBRSs, a novel distributed HBRS filter is developed and its effectiveness is tested on a case study concerning wide-area monitoring of a power network.
Keyword:
Cyber-physical systems
distributed detection and estimation
signal attack
Bayesian state estimation
Bernoulli filter
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.9
论文数:
738
被引数:
1.9K
机构
引用论文
Physical studies of the interaction of a calf thymus helix-destabilizing protein with nucleic acids.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏Corrosion of primed and fully painted precoated automotive steels in atmospheric and scab tests
PREAI
分享收藏
查看更多内容