%0 Journal Article %1 8060538 %A Forti, N. %A Battistelli, G. %A Chisci, L. %A Li, S. %A Wang, B. %A Sinopoli, B. %D 2018 %J IEEE Transactions on Signal and Information Processing over Networks %K myown %N 1 %P 96-110 %R 10.1109/TSIPN.2017.2760804 %T Distributed Joint Attack Detection and Secure State Estimation %U https://ieeexplore.ieee.org/document/8060538/ %V 4 %X 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 Kullback- Leibler 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.

@article{8060538, abstract = {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 Kullback- Leibler 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.}, added-at = {2019-02-20T11:02:18.000+0100}, author = {{Forti}, N. and {Battistelli}, G. and {Chisci}, L. and {Li}, S. and {Wang}, B. and {Sinopoli}, B.}, biburl = {https://www.bibsonomy.org/bibtex/27f1fe12957a3f33452cbc6457d2ab1c9/nforti}, doi = {10.1109/TSIPN.2017.2760804}, interhash = {17616aa78309fcb9985d2d18ced2e537}, intrahash = {7f1fe12957a3f33452cbc6457d2ab1c9}, issn = {2373-776X}, journal = {IEEE Transactions on Signal and Information Processing over Networks}, keywords = {myown}, month = {March}, number = 1, pages = {96-110}, timestamp = {2019-02-20T11:02:18.000+0100}, title = {Distributed Joint Attack Detection and Secure State Estimation}, url = {https://ieeexplore.ieee.org/document/8060538/}, volume = 4, year = 2018 }