Multiple Correlated Attributes Based Physical Layer Authentication in Wireless Networks

Xia, Shida; Tao, Xiaofeng; Li, Na; Wang, Shiji; Sui, Tengfei; Wu, Huici; Xu, Jin; Han, Zhu

doi:10.1109/tvt.2021.3055563

Cited by 27 publications

(4 citation statements)

References 49 publications

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“…In this way, the proposed solution can efficiently capture important features of high-dimensional channel impulse responses for better authentication performance. The authors then show that the proposed solution can improve the authentication performance by 17.18% compared to a conventional ML approach in [105]. Due to the ability of generating synthetic data that is similar to real data, GAI can also be used by adversaries to perform different types of physical layer attacks [83], [84], [98], [103].…”

Section: Channel Equalizationmentioning

confidence: 99%

Effect of heavy metals on duckweed growth

Nguyen¹,

Hoang²,

Pham³

et al. 2022

CTUJS

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In this study, three clones of the duckweed genus Lemna, collected from three different regions of Vietnam Binh Thuan Bac Giang and Ben Tre were used to evaluate the growth and development in a culture medium containing different concentrations of As3+, Cd2+, or Pb2+. During 14 days of incubation, the growth rate was determined daily by measuring the surface area of all plants of each sample. Experimental results show that the three Lemna clones could grow in nutrient medium contaminated by heavy metal at a concentration of 0.3-0.5 mg/L for As3+, 0.15-0.3 mg/L for Cd2+, and 0.15 mg/L for Pb2+. At these concentrations, the division rate of the treated clones was several times higher than that of the controls. The highest increase in the surface area was recorded for Lemna BTN (68.47 times higher when cultured in medium supplemented in 0.3 mg/L Pb2+ than under control conditions). The surface area of Lemna BTR cultured in a medium supplemented with 0.3 mg/L As3+ was 54.65 times higher than in medium without arsenic. The obtained results showed that Lemna BGG and Lemna BTR can tolerate arsenic and cadmium pollution while Lemna BTN tolerates lead pollution.

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Section: Channel Equalizationmentioning

confidence: 99%

Effect of heavy metals on duckweed growth

Nguyen¹,

Hoang²,

Pham³

et al. 2022

CTUJS

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show abstract

“…A group of classifiers is used for security authentication between authorized and unauthorized devices in the IPCS network [25,26]. In [27,28], different learning-assisted authentication algorithms based on multiple features were used to offer various levels of authorization. The algorithms in [29] were designed to meet diverse security needs by incorporating a set of appropriate features.…”

Section: Prior Art and Motivationmentioning

confidence: 99%

Intelligent Security Authentication for Connected and Autonomous Vehicles: Attacks and Defenses

Qiu,

Yu,

Jiang

et al. 2024

Electronics

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The emergence of integrated positioning, communication, and sensing technologies has paved the way for a surge in connected and autonomous vehicles. The control system has been successful in reliable and fast transmission. However, practical applications face security risks, especially data tampering and spoofing attacks. To improve the resilience of the system against potential attacks, we attempt to leverage a generative adversarial network learning-assisted authentication framework (GAF). In addition to proposing a new method for validating vehicles, we also introduce a new architectural innovation in the generator–discriminator pair to achieve improved results. The generator sub-network is constructed using an advanced convolutional neural network, whereas the discriminator is designed to leverage global and local information to determine whether a signal is real or fake. On this basis, we propose a signal enhancement-based authentication method, a deep convolutional generative adversarial network (DCGAN). Experimental results using the National Institute of Standards and Technology (NIST) dataset show that the proposed method is effective in denoising and improving the detection performance.

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“…The limited dynamic range of the specific attributes could also be insufficient to provide a guaranteed authentication result, when the number of devices to be authenticated increases [31]. Ultimately, observing and analyzing multiple attributes and devices at the same instance may create a bottleneck, which may further lead to single-point authentication failure and reduced application traffic [32].…”

Section: Intermittent Transmissionmentioning

confidence: 99%

GALAMC: Guaranteed Authentication Level at Minimized Complexity Relying on Intelligent Collaboration

Wang

Fang

et al. 2023

IEEE Trans. Commun.

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Conventional centralized authentication techniques based on both digital cryptography and physical-layer attributes are prone to single-point failure due to either compromised digital security keys or an abrupt change in the physical communication environment. Although these particular challenges could be mitigated by the joint use of decentralized authentication and physical-layer attributes, such schemes often exhibit unpredictable performance. Simultaneously, the necessary involvement of multiple parties and the imperfect observation of the physical communication environment can also significantly increase the latency and computational complexity. As a remedy, a decentralized authentication scheme is proposed in this paper to achieve Guaranteed Authentication Level at Minimized Complexity (GALAMC) based on the intelligent use of distributed collaboration and available distributive physical-layer attributes. Specifically, we aim for minimizing the complexity of the proposed collaborative authentication process by harnessing the minimum number of collaborative nodes and the selected authentication attributes at each node across the different environments while guaranteeing the required authentication level. The related physical-layer authentication scheme is implemented at each collaborative node where different physical-layer attributes can be selected based on their usefulness which is time-varying. The simulation results demonstrate that our scheme maintains the target level of authentication and it is more immune to sudden environmental changes than the conventional centralized physical-layer authentication scheme. It can also be observed that our proposed scheme can adaptively select the minimum number of collaborative nodes for adaptively minimizing the computational cost.

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Multiple Correlated Attributes Based Physical Layer Authentication in Wireless Networks

Cited by 27 publications

References 49 publications

Effect of heavy metals on duckweed growth

Effect of heavy metals on duckweed growth

Intelligent Security Authentication for Connected and Autonomous Vehicles: Attacks and Defenses

GALAMC: Guaranteed Authentication Level at Minimized Complexity Relying on Intelligent Collaboration

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