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IET Communications

Physical‐layer security in Internet of Things based on compressed sensing and frequency selection

Ning Wang, Ting Jiang, Weiwei Li, Shichao Lv

Published Mar 25, 2017• 41 citations
Publisher

Abstract

Information security is a vital concern in Internet of Things (IoT). Traditional security method based on public or private key encryption scheme is limited by the trade‐off between low cost and high level of security. Among different security solutions, utilising compressed sensing (CS) in combination with the physical‐layer security to achieve the security is a remarkable method. However, in the current literatures, little attention has been given to the area of static environment, which will lead the risk of information leakage in the CS security model. In this study, the authors propose a new CS security model, in which circulant matrix is exploited to improve the generation efficiency of the measurement matrix, and binary resilient functions are utilised to enhance the security. Furthermore, considering the practical application, they present a feasible framework, named CS security scheme based on frequency‐selective, where the frequency‐selective feature of the wireless channel is applied to support the static environment. To verify the effectiveness of the proposed scheme, they conducted experiments and numerical simulations to evaluate the performance, and the results are satisfactory.

DOI
10.1049/iet-com.2016.1088

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Information security is a vital concern in Internet of Things (IoT). Traditional security method based on public or private key encryption scheme is limited by the trade‐off between low cost and high level of security. Among different security solutions, utilising compressed sensing (CS) in combination with the physical‐layer security to achieve the security is a remarkable method. However, in the current literatures, little attention has been given to the area of static environment, which will lead the risk of information leakage in the CS security model. In this study, the authors propose a new CS security model, in which circulant matrix is exploited to improve the generation efficiency of the measurement matrix, and binary resilient functions are utilised to enhance the security. Furthermore, considering the practical application, they present a feasible framework, named CS security scheme based on frequency‐selective, where the frequency‐selective feature of the wireless channel is applied to support the static environment. To verify the effectiveness of the proposed scheme, they conducted experiments and numerical simulations to evaluate the performance, and the results are satisfactory.
The Internet of Things (IoT) features pervasive sensing and control capabilities by deploying a massive machine-type communication (MTC) devices. However, low hardware complexity, low processing capacity and constrained energy of MTC devices raise lots of challenges to communication and security. Therefore, physical layer security (PLS) appears to be a promising method for securing wireless communication in which orthogonal frequency division multiplexing (OFDM) is widely used. However, most existing OFDM-based PLS schemes possess little dynamicity for their secret keys derived from pre-extracted information. The combination of OFDM and compressed sensing (CS) is a remarkable approach to address the weakness. So, with compressed sensing, we propose a physical layer security scheme for OFDM-based IoT systems, named PLSSCS. It can address the demerit of key extraction by channel measuring instead of pre-extracted information. To evaluate the performance of PLSSCS, the simulation is carried out in MATLAB, and PLSSCS provides better performance with dynamic property.
Compressive sensing (CS) has become a popular signal processing technique and has extensive applications in numerous fields such as wireless communications, image processing, magnetic resonance imaging, remote sensing imaging, and analogy to information conversion, since it can realize simultaneous sampling and compression. In the information security field, secure CS has received much attention due to the fact that CS can be regarded as a cryptosystem to attain simultaneous sampling, compression and encryption when maintaining the secret measurement matrix. Considering that there are increasing works focusing on secure wireless communications based on CS in recent years, we produce a detailed review for the state-of-the-art in this paper. To be specific, the survey proceeds with two phases. The first phase reviews the security aspects of CS according to different types of random measurement matrices such as Gaussian matrix, circulant matrix, and other special random matrices, which establishes theoretical foundations for applications in secure wireless communications. The second phase reviews the applications of secure CS depending on communication scenarios such as wireless wiretap channel, wireless sensor network, Internet of Things, crowd-sensing, smart grid, and wireless body area networks. Finally, some concluding remarks are given.
Many Internet of things application scenarios have the characteristics of limited hardware resources and limited energy supply, which are not suitable for traditional security technology. The security technology based on the physical mechanism has attracted extensive attention. How to improve the key generation rate has always been one of the urgent problems to be solved in the security technology based on the physical mechanism. In this paper, superlattice technology is introduced to the security field of Internet of things, and a high-speed symmetric key generation scheme based on superlattice for Internet of things is proposed. In order to ensure the efficiency and privacy of data transmission, we also combine the superlattice symmetric key and compressive sensing technology to build a lightweight data transmission scheme that supports data compression and data encryption at the same time. Theoretical analysis and experimental evaluation results show that the proposed scheme is superior to the most closely related work.
In this paper, we investigate the physical layer security of single amplify-and-forward (AF) relay communication system based on compressed sensing (CS). Different to the traditional method by compressing the source data with a specific measurement matrix (e.g. Gaussian matrix)to achieve security, we first demonstrate that the combination matrix of the compression measurement matrix and cooperative AF channel matrix between legitimate nodes (source, relay, and destination) can be considered as a secure measurement matrix for physical layer security. Compared with CS scenario without AF (CS Non-AF), the eavesdropper in the proposed scheme can hardly decode the original data correctly even when it has a perfect knowledge of eavesdropper channel state information (ECSI). The robustness of the scheme in the presence of one eavesdropper is also investigated.
Compressive sensing (CS) encryption has attracted increasing attention as a lightweight encryption technique for the Internet of things (IoT) and wireless sensor networks (WSNs). Since devices and sensors may have limited hardware, it might be needed to consider quantization for CS encryption. In this paper, we consider a 1-bit CS encryption using artificial noise and a retransmission strategy with interleaving to mitigate degradation of detection performance at a legitimate receiver caused by the quantization errors. Through the analysis and simulation results, we demonstrate that the retransmission strategy can improve the detection performance at a legitimate receiver, while it slightly improves decision performance to estimate a measurement matrix at an eavesdropper. In addition, the proposed 1-bit CS encryption has a better performance than the existing CS encryption in terms of security, while mitigating the performance degradation caused by quantization errors of detection probability at a legitimate receiver.
The security of the Internet of Things (IoT) is receiving considerable interest as the low power constraints and complexity features of many IoT devices are limiting the use of conventional cryptographic techniques. This article provides an overview of recent research efforts on alternative approaches for securing IoT wireless communications at the physical layer, specifically the key topics of key generation and physical layer encryption. These schemes can be implemented and are lightweight, and thus offer practical solutions for providing effective IoT wireless security. Future research to make IoT-based physical layer security more robust and pervasive is also covered.