Physical-Layer Cooperative Key Generation with Correlated Eavesdropping Channels in IoT

Xu, Peng; Hu, Dongyang; Chen, Gaojie

doi:10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00025

Cited by 12 publications

(5 citation statements)

References 21 publications

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“…In order to overcome these shortcomings, some studies have used multiantenna [27,28], multibit quantization [29,30], or adaptive quantization methods [31,32] to improve the secret key generation rate, but these methods still lose a lot of useful information, which is not conducive to the secret key generation. ere are also some studies which start from the wireless channel characteristic information and improve the key generation ability by sending artificial noise [33,34] and introducing wireless cooperative nodes [35,36], but these ways add extra cost and are also more complex to implement. In addition, some research studies start from the dimension of wireless channel characteristics, improving the one-dimensional characteristics of the channel and extracting the secret key through the channel multicharacteristic information to overcome the problems of the abovementioned secret key generation scheme.…”

Section: Introductionmentioning

confidence: 99%

A Method for Detecting Amplitude-Phase Joint Characteristic Parameters of Wireless Channel for Generating Key Parameters

2021

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Aiming at the problems of poor adaptability and low secret key generation rate of secret key generation scheme based on single characteristic parameter of wireless channel, a secret key generation method based on joint characteristic parameters of amplitude and phase of wireless channel is proposed. This method is based on the single-eavesdropping wireless fading channel model; the joint characteristic model of amplitude and phase of wireless fading channel is established; it detects and extracts the joint characteristic parameters of amplitude and phase of channel, and then the proposed characteristics are quantified by using the equal probability joint quantization strategy of amplitude and phase to generate the secret key random parameters. In this paper, the amplitude and phase joint feature parameter detection method of wireless channel can not only improve the generation rate of random secret key parameters but also make the eavesdropping party’s eavesdropping error rate closer to 0.5. The test results show that the proposed scheme can significantly improve the rate, reliability, and security of generating key random parameters.

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Section: Introductionmentioning

confidence: 99%

A Method for Detecting Amplitude-Phase Joint Characteristic Parameters of Wireless Channel for Generating Key Parameters

2021

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“…However, the proposed scheme assumes that Eve is located near Bob, and considers the eavesdropping channel between Alice and Eve to be correlated with the legitimate channel, which is not a realistic assumption. Also under the same channels correlation assumption, in Reference 27, the key agreement process in the proposed key generation scheme is performed over three consecutive phases. First, the channel difference between each legitimate relay node's channel and the eavesdropping channel is utilized to generate a secret key.…”

Section: Related Workmentioning

confidence: 99%

Phase‐assisted NOMA based key distribution for IoT networks

Alshamaseen

Althunibat

Qaraqe

et al. 2023

Trans Emerging Tel Tech

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Internet of Things (IoT) technology has recently been adopted in different fields and applications. An IoT network allows for a large set of physical objects (or devices) with various technologies to work together and exchange a large amount of information. This, however, raises different security and privacy concerns, including the confidentiality of the exchanged data. Usually, data confidentiality is maintained in wireless networks utilizing data encryption using a pre-shared secret key. Thus, protecting the key distribution process is essential to maintaining a secure network. However, due to the typically large size of IoT networks, conventional secret key distribution schemes are unsuitable and lead to resource inefficiency. Therefore, in this paper, an efficient key distribution scheme is proposed by using physical-layer security concepts. Specifically, non-orthogonal multiple access (NOMA) is utilized to distribute the key to multiple nodes in a resource-efficient manner. Moreover, the instantaneous channel phase is also used to attain a secure distribution in which each node can obtain its own key only. The performance of the proposed scheme is analyzed in terms of the key error rate at both a legitimate node and an eavesdropper under different channel fading models, where closed form mathematical expressions are derived and verified via simulation results. INTRODUCTIONThe Internet of Things (IoT) describes the network of physical objects or devices that are equipped with sensors, processors, software, transceivers, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. 1 The use of IoT networks has spread across many fields to improve quality of life and reduce human efforts such as smart agriculture, smart home applications, forest management, industrial sector, tourism, military, security, and many other applications. 2 IoT networks suffer from several challenges which include energy efficiency, spectrum and bandwidth management, regulatory issues, compatibility, and security. Among them, security occupies an advanced position in some applications. Actually, IoT networks face numerous challenges to reach decent security levels 3 such as active and passive eavesdropping, intrusion, message forging, and key generation, whereby numerous works aimed at tackling such concerns such as References 4-7.

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“…The BS and the nodes wish to agree on secret keys based on the characteristics of wireless channels. IoT nodes can be deployed at any location, and some nodes may be deployed close to each other, such as node 1 and node 2, which leads to channel correlation between nodes [15]. The BS is equipped with M antennas, while all the nodes are equipped with a single antenna.…”

Section: Proposed Ris Aided Skg Scheme a System Modelmentioning

confidence: 99%

RIS aided Physical Layer Key Generation of IoT network in Static Environments

Yang¹,

Ji²,

Huang³

et al. 2022

Preprint

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Physical layer secret key generation schemes can provide lightweight encryption for resource constrained Inter?net of Things (IoT) devices. However, many IoT devices are stationary and the environment is usually static, which leads to ultra-low/zero secret key rates. To circumvent this problem, a novel secret key generation scheme based on Reconfigurable Intelligent Surface (RIS) is proposed for Multiple-Input Single?Output IoT communications. The RIS is introduced into the network, and the phase shifts at RIS are tuned randomly in each frame, which superimpose time-varying reflection channels on the orginal channels. And then the secret key capacity of all nodes within the cell coverage area can be remarkably improved. The closed-form expressions of secret key capacity taking into account eavesdropping are first derived for the case studies of independent and correlated channels. We can conclude that sharing the same phase shifts randomness will not bring key information leakage. Compared with three benchmark schemes, the proposed scheme can both maintain good performance whenever eavesdropping nodes exist. Further, the impact of parameters, such as the number of reflecting units, the transmit antennas and the Rician factor, on secret key performance are analyzed respectively, which can offer guidelines for system design. Finally, simulation results verify the theoretical analysis.

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Physical-Layer Cooperative Key Generation with Correlated Eavesdropping Channels in IoT

Cited by 12 publications

References 21 publications

A Method for Detecting Amplitude-Phase Joint Characteristic Parameters of Wireless Channel for Generating Key Parameters

A Method for Detecting Amplitude-Phase Joint Characteristic Parameters of Wireless Channel for Generating Key Parameters

Phase‐assisted NOMA based key distribution for IoT networks

RIS aided Physical Layer Key Generation of IoT network in Static Environments

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