Secret Key Generation for Intelligent Reflecting Surface Assisted Wireless Communication Networks

Ji, Zijie; Yeoh, Phee Lep; Zhang, Deyou; Chen, Gaojie; Zhang, Yan; He, Zhiyuan; Yin, Hao; li, Yonghui

doi:10.1109/tvt.2020.3045728

Cited by 97 publications

(90 citation statements)

References 12 publications

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“…Leveraging this, the work in [36] randomly selects IRS phases from a discrete set, and provides a theoretical high SKR in the face of a single Eve. The work in [39] further designs a selection of random IRS phase, by maximizing the SKR against multiple non-colluded Eves. However, none of them considers the colluded Eve cases.…”

Section: A Literature Reviewmentioning

confidence: 99%

Random Matrix based Physical Layer Secret Key Generation in Static Channels

Wei¹,

Guo²

2021

Preprint

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Physical layer secret key generation exploits the reciprocal channel randomness for key generation and has proven to be an effective addition security layer in wireless communications. However, static or scarcely random channels require artificially induced dynamics to improve the secrecy performance, e.g., using intelligent reflecting surface (IRS). One key challenge is that the induced random phase from IRS is also reflected in the direction to eavesdroppers (Eve). This leakage enables Eve nodes to estimate the legitimate channels and secret key via a globally known pilot sequence. To mitigate the secret key leakage issue, we propose to exploit random matrix theory to inform the design of a new physical layer secret key generation (PL-SKG) algorithm. We prove that, when sending appropriate random Gaussian matrices, the singular values of Alice's and Bob's received signals follow a similar probability distribution. Leveraging these common singular values, we propose a random Gaussian matrix based PL-SKG (RGM PL-SKG), which avoids the usages of the globally known pilot and thereby prevents the aforementioned leakage issue. Our results show the following: (i) high noise resistance which leads to superior secret key rate (SKR) improvement (up to 300%) in low SNR regime, and (ii) general improved SKR performance against multiple colluded Eves. We believe our combination of random matrix theory and PL-SKG shows a new paradigm to secure the wireless communication channels.

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Section: A Literature Reviewmentioning

confidence: 99%

Random Matrix based Physical Layer Secret Key Generation in Static Channels

Wei¹,

Guo²

2021

Preprint

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“…Since IRS can configure the wireless channel through passive reflection, it has great potential in improving key extraction performance [10]. In terms of applying IRS to optimize key extraction over a low-entropy channel, some papers have recently proposed corresponding schemes [11]. A low-cost IRS-assisted channel key extraction prototype system was also recently designed in [12], which proved that using IRS for key extraction is a feasible solution.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Reflecting Surface Assisted Multi-User Robust Secret Key Generation for Low-Entropy Environments

Gao

Guo

Xiong

et al. 2021

Entropy

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Channel secret key generation (CSKG), assisted by the new material intelligent reflecting surface (IRS), has become a new research hotspot recently. In this paper, the key extraction method in the IRS-aided low-entropy communication scenario with adjacent multi-users is investigated. Aiming at the problem of low key generation efficiency due to the high similarity of channels between users, we propose a joint user allocation and IRS reflection parameter adjustment scheme, while the reliability of information exchange during the key generation process is also considered. Specifically, the relevant key capability expressions of the IRS-aided communication system is analyzed. Then, we study how to adjust the IRS reflection matrix and allocate the corresponding users to minimize the similarity of different channels and ensure the robustness of key generation. The simulation results show that the proposed scheme can bring higher gains to the performance of key generation.

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“…Ji et al [3] randomly change the phase of RIS to introduce artificial randomness and increase the key generation rate (KGR). In their other work [4], RIS reflecting coefficients are optimized to maximize the lower bound of secret key rate in multiple eavesdroppers scenario. Moreover, Lu et al [5] adjusted the placement of RIS to maximize the key rate capacity.…”

Section: Introductionmentioning

confidence: 99%

On the RIS Manipulating Attack and Its Countermeasures in Physical-layer Key Generation

Hu¹,

Li²,

Luo³

et al. 2021

Preprint

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Reconfigurable Intelligent Surface (RIS) is a new paradigm that enables the reconfiguration of the wireless environment. Based on this feature, RIS can be employed to facilitate Physical-layer Key Generation (PKG). However, this technique could also be exploited by the attacker to destroy the key generation process via manipulating the channel features at the legitimate user side. Specifically, this paper proposes a new RISassisted Manipulating attack (RISM) that reduces the wireless channel reciprocity by rapidly changing the RIS reflection coefficient in the uplink and downlink channel probing step in orthogonal frequency division multiplexing (OFDM) systems. The vulnerability of traditional key generation technology based on channel frequency response (CFR) under this attack is analyzed. Then, we propose a slewing rate detection method based on path separation. The attacked path is removed from the time domain and a flexible quantization method is employed to maximize the Key Generation Rate (KGR). The simulation results show that under RISM attack, when the ratio of the attack path variance to the total path variance is 0.17, the Bit Disagreement Rate (BDR) of the CFR-based method is greater than 0.25, and the KGR is close to zero. In addition, the proposed detection method can successfully detect the attacked path for SNR above 0 dB in the case of 16 rounds of probing and the KGR is 35 bits/channel use at 23.04MHz bandwidth.

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Secret Key Generation for Intelligent Reflecting Surface Assisted Wireless Communication Networks

Cited by 97 publications

References 12 publications

Random Matrix based Physical Layer Secret Key Generation in Static Channels

Random Matrix based Physical Layer Secret Key Generation in Static Channels

Intelligent Reflecting Surface Assisted Multi-User Robust Secret Key Generation for Low-Entropy Environments

On the RIS Manipulating Attack and Its Countermeasures in Physical-layer Key Generation

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