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Physical layer authentication of off‐body channels by probabilistic neural networks
Author(s) -
Raida Zbynek
Publication year - 2019
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.2628
Subject(s) - computer science , probabilistic logic , authentication (law) , computer network , probabilistic neural network , channel (broadcasting) , artificial neural network , physical layer , key (lock) , wireless , telecommunications , artificial intelligence , computer security , time delay neural network
A probabilistic neural network (PNN) for the authentication of an off‐body channel of a wireless body area network is discussed in this paper. The off‐body channel is authenticated by radio‐frequency fingerprints of on‐body channels. Thanks to a relatively high stationarity of on‐body channels, a reasonable probability of radio‐frequency fingerprinting identification is reached. Radio‐frequency fingerprints are used to train a probabilistic neural network playing the role of an authentication key. The authentication process can be efficiently controlled by setting tolerance zones of the network. Functionality of the concept was proven by computer simulations.