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Performance improvement of wireless secret key generation with colored noise for IoT
Author(s) -
Soni Ankit,
Upadhyay Raksha,
Kumar Abhay
Publication year - 2019
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4124
Subject(s) - computer science , key generation , rss , colored , key (lock) , wireless network , wireless , noise (video) , colors of noise , computer network , real time computing , algorithm , computer security , cryptography , artificial intelligence , telecommunications , white noise , materials science , image (mathematics) , composite material , operating system
Summary Achieving security in the Internet of things (IoT) networks by generating symmetric keys from the wireless channel parameters like received signal strength (RSS) is a promising approach. Despite the easy acquisition of the RSS signal, RSS‐based security is less explored for IoT. In this work, we analyze the performance of RSS‐based wireless physical layer key generation with correlated colored noise components and proposed a low complexity filtering approach to improve the performance for the IoT network. We started with providing a survey of various recent researches related to RSS‐based key generation and also discussed correlated colored noise components with a few of the recent works considering them. Further, we analyze various colored noise components in the time domain by the Allan variance and Ljung‐Box test. Furthermore, we develop a key generation model and proposed a moving window averaging‐based filtering followed by Lloyd max quantization to improve the BDR performance, degraded due to the presence of correlated colored noise components. The simulation results show that the proposed preprocessing technique has a considerable improvement in the BDR performance, and the keys generated have sufficient randomness, which is verified by NIST test.