PRIVACY-PRESERVING DISTRIBUTED PRECODER DESIGN FOR DECENTRALIZED ESTIMATION

We study privacy-preserving precoder design for decentralized estimation in wireless sensor networks where the sensor nodes want their local information such as the channel state information, observation matrices, and observation covariance matrices to be private. We propose a distributed algorithm...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP) s. 1311 - 1315
Hlavní autoři: Venkategowda, Naveen K. D., Werner, Stefan
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.11.2018
Témata:
Covariance matrices
Estimation error
Nickel
Privacy
Security
Wireless sensor networks
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:We study privacy-preserving precoder design for decentralized estimation in wireless sensor networks where the sensor nodes want their local information such as the channel state information, observation matrices, and observation covariance matrices to be private. We propose a distributed algorithm with closed form expressions to design the precoders and fusion rule that minimize the estimation error by exchanging messages which do not reveal the local information. We derive the privacy limits offered by the proposed algorithm and prove that the algorithm is privacy-preserving. Simulation results illustrate the trade-off between privacy and estimation accuracy of the proposed algorithm.
DOI:10.1109/GlobalSIP.2018.8646374