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IET Communications

Secret key generation based on signal power allocation optimisation

Xinjin Lu, Jing Lei, Wei Li

Published May 17, 2022• 1 citation
Publisher

Abstract

Abstract With the rapid development of wireless communication, the use of the inherent features of wireless channels to enhance and supplement existing security mechanisms has attracted widespread attention. In this work, a key generation scheme based on power allocation optimisation is proposed. The subchannel state information obtained from channel probing is employed to allocate signal power. Furthermore, an improved channel probing process is designed to implement the optimisation scheme of power allocation. Theoretical analysis and simulation results show that this optimisation scheme can obtain higher key capacity, and the superiority is more prominent when the signal‐to‐noise ratio is low. Besides, the key bits mismatch rate of the proposed optimisation scheme is decreased and the corresponding key generation rate is higher compared with the benchmark.

DOI
10.1049/cmu2.12422

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IEEE Conference on Communications and Network Security•Jun 1, 2020•21 citations
Abstract With the rapid development of wireless communication, the use of the inherent features of wireless channels to enhance and supplement existing security mechanisms has attracted widespread attention. In this work, a key generation scheme based on power allocation optimisation is proposed. The subchannel state information obtained from channel probing is employed to allocate signal power. Furthermore, an improved channel probing process is designed to implement the optimisation scheme of power allocation. Theoretical analysis and simulation results show that this optimisation scheme can obtain higher key capacity, and the superiority is more prominent when the signal‐to‐noise ratio is low. Besides, the key bits mismatch rate of the proposed optimisation scheme is decreased and the corresponding key generation rate is higher compared with the benchmark.
Summary Extracting secret keys from the common randomness of wireless channels has attracted prominent attention recently. Orthogonal frequency‐division multiplexing (OFDM) systems can provide extra randomness in view of the use of multiple subchannels. So far, the secret key capacity of OFDM systems is still an open issue. In this paper, the secret key capacity of OFDM systems based on the subchannel state information is analyzed, and an expression of the secret key capacity is derived under the assumption that the subchannels are independent. To increase the secret key capacity, a power allocation scheme based on geometric program is proposed. Furthermore, an underlying propagation protocol is designed to realize the power allocation scheme. Performance simulations show that the proposed scheme achieves greater secret key capacity in comparison with equal power allocation scheme, especially at low signal‐to‐noise ratio region. Besides, the secret key bits mismatch rate during the secret key generation based on the power allocated subchannels is decreased.
Pilot power allocation is investigated under the framework of physical layer secure communications in time‐division duplex systems, where the secret keys are generated from the estimates of sparse wireless channels. The joint optimisation of secret key capacity and sparse channel estimation performance based on pilot power allocation is formulated as a convex optimisation problem. Considering the fairness between these two sides, a scaling factor is introduced. Then, a scheme is proposed to fast solve the problem by looking up a table and using existing optimisation solvers. Simulation results show that a proper scaling factor can make a trade‐off between the secret key capacity and sparse channel estimation performance.
As an alternative and appealing approach to providing information security in wireless communication systems, secret key generation at physical layer has demonstrated its potential in terms of efficiency and reliability over traditional cryptographic methods. Without the necessity of a management centre for key distribution or reliance on computational complexity, physical layer key generation protocols enable two wireless entities to extract identical and dynamic keys from the randomness of the wireless channels associated with them.\nIn this thesis, the reliability of secret key generation at the physical layer is examined in practical wireless channels with imperfect channel state information (CSI). Theoretical analyses are provided to relate key match rate with channel's signal-to-noise ratio (SNR), degrees of channel reciprocity, and iterations of information reconciliation.\nIn order to increase key match rate of physical layer secret key generation, improved schemes in the steps of channel estimation and sample quantization are proposed respectively. In the channel estimation step, multiple observations of the wireless channels are integrated with a linear processor to provide a synthesized and more accurate estimation of the wireless channel. In the sample quantization step, a magnitude based quantization method with two thresholds is proposed to quantize partial samples, where specific quantization areas are selected to reduce cross-over errors. Significant improvements in key match rate are proven for both schemes in theoretical analysis and numerical simulations. Key match rate can even achieve 100% in both schemes with the assistance of information reconciliation process.\nIn the end, a practical application of physical layer secret key generation is presented, where dynamic keys extracted from the wireless channels are utilized for securing secret data transmission and providing efficient access control.
The basis of generating secret key from the common wireless channel at two communication parties is reciprocity. However, due to non-simultaneous measurements and unavoidable estimation error, bias always exists and key disagreement occurs. In this paper, performance analysis and improvements for key generation exploiting imperfect channel statement information (CSI) is studied. Firstly, the closed-form expression for key disagreement rate (KDR) is derived to evaluate the key mismatch caused by time delay and estimation error. Secondly, the energy efficiency involving power allocation between key generation and private data transmission is presented. After that, a neural network based prediction (NNBP) algorithm is proposed to improve the key consistency. Simulation results verify the theoretical analysis and show that NNBP achieves significant improvements. And it's interesting to find that NNBP algorithm achieves a higher performance gain in low signal-to-noise ration (SNR) and high delay condition, which is different from other methods, like guard band based quantizer (GBBQ).
The basis of generating secret key from the common wireless channel at two communication parties is reciprocity. However, due to non-simultaneous measurements and unavoidable estimation error, bias always exists and key disagreement occurs. In this paper, performance analysis and improvements for key generation exploiting imperfect channel statement information (CSI) is studied. Firstly, the closed-form expression for key disagreement rate (KDR) is derived to evaluate the key mismatch caused by time delay and estimation error. Secondly, the energy efficiency involving power allocation between key generation and private data transmission is presented. After that, a neural network based prediction (NNBP) algorithm is proposed to improve the key consistency. Simulation results verify the theoretical analysis and show that NNBP achieves significant improvements. And it's interesting to find that NNBP algorithm achieves a higher performance gain in low signal-to-noise ration (SNR) and high delay condition, which is different from other methods, like guard band based quantizer (GBBQ).
We investigate group secret key generation in 5G mmWave Massive MIMO networks and intend to improve the efficiency of channel probing for group key generation. In this paper, a new channel probing strategy for star-topology networks is proposed, which relies on the multiplexing of downlink probing signals, enabled by the hybrid precoding. To improve the group key rates per channel probing, a genetic algorithm (GA) based power allocation algorithm is also proposed. What’s more, to estimate the group key rates based on the probing samples, we propose a scheme for the estimation of group key rates based on the maximum likelihood estimator (MLE). The performance of the proposed scheme on group key rates and bits disagreement ratio (BDR) are provided. The numerical results show that the GA-based downlink channel probing scheme can increase the efficiency of channel probing and have higher group key rates compared with the existing channel probing schemes. When the SNR is 25dB, the key rates of GA-based power allocation scheme are 20% higher than the scheme with the conventional channel probing strategy.