In this paper we develop a simple, yet effective, secure communication protocol based on linear algebra that allows messages to be transmitted securely, without the need to encrypt them through computationally demanding approaches or to consider integer-valued plain messages, except during an initialization phase. The scheme is composed by several layers of protection and is applied to a scenario involving a networked Kalman filter fed by measurements sent by a sensor through a public network. Specifically, the two actors interact at initialization by exchanging suitably encrypted matrices; then, each message is split in two parts and is altered via a linear non-invertible transformation. Notably, each message is guaranteed to correspond to an unobservable measurement, while the receiver is provided with a strategy to reconstruct the message through simple calculations based on the information exchanged during the initialization phase. To further mask the messages, Gaussian noise with statistics known to both parties is artificially added to the messages. A simulation campaign completes the paper and demonstrates its effectiveness experimentally.

A Secure Communication Protocol with Application to Networked Kalman Filtering

Fioravanti, C;Oliva, G;
2022-01-01

Abstract

In this paper we develop a simple, yet effective, secure communication protocol based on linear algebra that allows messages to be transmitted securely, without the need to encrypt them through computationally demanding approaches or to consider integer-valued plain messages, except during an initialization phase. The scheme is composed by several layers of protection and is applied to a scenario involving a networked Kalman filter fed by measurements sent by a sensor through a public network. Specifically, the two actors interact at initialization by exchanging suitably encrypted matrices; then, each message is split in two parts and is altered via a linear non-invertible transformation. Notably, each message is guaranteed to correspond to an unobservable measurement, while the receiver is provided with a strategy to reconstruct the message through simple calculations based on the information exchanged during the initialization phase. To further mask the messages, Gaussian noise with statistics known to both parties is artificially added to the messages. A simulation campaign completes the paper and demonstrates its effectiveness experimentally.
2022
978-1-6654-5196-3
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/73565
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 0
social impact