Physical layer secret-key generation with discreet cosine transform for the Internet of Things

Margelis, George; Fafoutis, Xenofon; Oikonomou, George; Piechocki, Robert J.; Tryfonas, Theo; Thomas, Paul

doi:10.1109/icc.2017.7997419

Cited by 29 publications

(13 citation statements)

References 20 publications

(17 reference statements)

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“…Using Equation (12) in which the frequency correlation of the sub-channels is considered, a more accurate model for the KGR can be presented. It is worthwhile to point out that the correlation between the measured sub-channel coefficients of data can be eliminated by a signal preprocessing procedure such as the PCA [15], DCT [16,17] and WT [18,19]. In [9], a new pre-coding method is addressed and it is also demonstrated that PCA-based pre-coding achieves a higher KGR than both the DCT and the WT.…”

Section: The Proposed Svd-based Pre-coding Methodsmentioning

confidence: 99%

“…In [9], efficient signal pre-coding is addressed and it is demonstrated that Principal Component Analysis (PCA)-based pre-coding achieves a higher KGR than Discrete Cosine Transform (DCT) and Wavelet Transform (WT). In other words, the channel correlation can be eliminated by a signal pre-processing procedure such as PCA [15], DCT [16,17], and WT [18,19].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Singular Value Decomposition Based Pre-coding for Secret Key Extraction from Correlated Orthogonal Frequency Division Multiplexing Sub-channels

Aliabadian

Zahabi

Mobini

2020

IJE

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Secret key extraction is a crucial issue in physical layer security and a less complex and, at the same time, a more robust scheme for the next generation of 5G and beyond. Unlike previous works on this topic, in which Orthogonal Frequency Division Multiplexing (OFDM) sub-channels were considered to be independent, the effect of correlation between sub-channels on the secret key rate is addressed in this paper. As an assumption, a realistic model for dependency among sub-channels is considered. Benchmarked by simulation, the result shows that the key exchange rate may decline by up to 72% due to the correlation of sub-channels. A new approach for efficient key extraction is used in this study. To do this, a Singular Value Decomposition based (SVD-based) pre-coding is utilized to alleviate the subchannels correlation and the channel noise. The low computational complexity of our proposed approach makes it a promising candidate for developing secure and high-speed networks. Results obtained through simulation indicate that applying pre-coding on the measured correlated data resulted in a minimum gain of 9 dB. In addition, the result also depicts the advantage of SVD versus other pre-coding techniques, namely PCA, DCT, and WT.

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Section: The Proposed Svd-based Pre-coding Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Singular Value Decomposition Based Pre-coding for Secret Key Extraction from Correlated Orthogonal Frequency Division Multiplexing Sub-channels

Aliabadian

Zahabi

Mobini

2020

IJE

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“…As another innovative technique, a real-time transform based on the time-invariant nature of hardware imbalance was proposed for time-varying TDD channels without involving any calibration [112]. • Interference, noise and autocorrelation reduction are usually addressed by transform domain algorithms, relying on principal component analysis (PCA) [62], [65], [110], discrete cosine transform (DCT) [113], [114] and wavelet transform (WT) [115], [116]. These preprocessing schemes are summarized and compared in [117].…”

Section: ) Signal Preprocessingmentioning

confidence: 99%

A New Frontier for IoT Security Emerging From Three Decades of Key Generation Relying on Wireless Channels

et al. 2020

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The Internet of Things (IoT) is a transformative technology, which is revolutionizing our everyday life by connecting everyone and everything together. The massive number of devices are preferably connected wirelessly because of the easy installment and flexible deployment. However, the broadcast nature of the wireless medium makes the information accessible to everyone including malicious users, which should hence be protected by encryption. Unfortunately, the secure and efficient provision of cryptographic keys for low-cost IoT devices is challenging; weak keys have resulted in severe security breaches, as evidenced by numerous notorious cyberattacks. This paper provides a comprehensive survey of lightweight security solutions conceived for IoT, relying on key generation from wireless channels. We first introduce the key generation fundamentals and protocols. We then examine how to apply this emerging technique to secure IoT and demonstrate that key generation relying on the randomness of wireless channels is eminently suitable for IoT. This paper reviews the extensive research efforts in the areas of theoretical modelling, simulation based validation and experimental exploration. We finally discuss the hurdles and challenges that key generation is facing and suggest future work to make key generation a reliable and secure solution to safeguard the IoT.

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“…As the vast numbers of nodes are communicating in the open wireless channel, data communication security is one of the open fields in IoT security. 8,9 White noise is a Gaussian noise and exhibits equal intensities at different frequencies, whereas the colored noise may have different characteristics at different frequency bands. It is also possible to achieve data security at the physical (PHY) layer by different physical layer security (PLS) techniques.…”

Section: Introductionmentioning

confidence: 99%

“…So it is required to account for all these effects while processing the received radio signals like RSS. 8,9 White noise is a Gaussian noise and exhibits equal intensities at different frequencies, whereas the colored noise may have different characteristics at different frequency bands. White noise is considered as uncorrelated random variables with zero mean and finite variance, ie, it has unity autocorrelation coefficient at zero lag and zeroes elsewhere, and while the correlated colored noise components have their autocorrelation value at some other lags, also.…”

Section: Introductionmentioning

confidence: 99%

Performance improvement of wireless secret key generation with colored noise for IoT

Soni

Upadhyay

Kumar

2019

Int J Communication

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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.

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Physical layer secret-key generation with discreet cosine transform for the Internet of Things

Cited by 29 publications

References 20 publications

Optimal Singular Value Decomposition Based Pre-coding for Secret Key Extraction from Correlated Orthogonal Frequency Division Multiplexing Sub-channels

Optimal Singular Value Decomposition Based Pre-coding for Secret Key Extraction from Correlated Orthogonal Frequency Division Multiplexing Sub-channels

A New Frontier for IoT Security Emerging From Three Decades of Key Generation Relying on Wireless Channels

Performance improvement of wireless secret key generation with colored noise for IoT

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