Establishing robust cybersecurity for Internet of Things (IoT) ecosystems poses significant challenges for system operators due to IoT resource constraints, trade-offs between security and performance, diversity of applications, and their security requirements, usability, and scalability. This article introduces a physical-layer security (PLS) approach that enables IoT devices to maintain specified levels of information confidentiality against wireless channel eavesdropping threats. This work proposes applying PLS active defense mechanisms utilizing spectrum-sharing schemes combined with fair scheduling and power management algorithms to mitigate the risk of eavesdropping attacks on resource-constrained IoT environments. Specifically, an IoT device communicating over an insecure wireless channel will utilize intentional noise signals transmitted alongside the actual IoT information signal. The intentional noise signal will appear to an eavesdropper (EVE) as additional noise, reducing the EVE’s signal-to-interference-plus-noise ratio (SINR) and increasing the EVE’s outage probability, thereby restricting their capacity to decode the transmitted IoT information, resulting in better protection for the confidentiality of the IoT device’s transmission. The proposed communication strategy serves as a complementary solution to existing security methods. Analytical and numerical analyses presented in this article validate the effectiveness of the proposed strategy, demonstrating that IoT devices can achieve the desired levels of confidentiality.
Establishing robust cybersecurity for Internet of Things (IoT) ecosystems poses significant challenges for system operators due to IoT resource constraints, trade-offs between security and performance, diversity of applications, and their security requirements, usability, and scalability. This article introduces a physical-layer security (PLS) approach that enables IoT devices to maintain specified levels of information confidentiality against wireless channel eavesdropping threats. This work proposes applying PLS active defense mechanisms utilizing spectrum-sharing schemes combined with fair scheduling and power management algorithms to mitigate the risk of eavesdropping attacks on resource-constrained IoT environments. Specifically, an IoT device communicating over an insecure wireless channel will utilize intentional noise signals transmitted alongside the actual IoT information signal. The intentional noise signal will appear to an eavesdropper (EVE) as additional noise, reducing the EVE’s signal-to-interference-plus-noise ratio (SINR) and increasing the EVE’s outage probability, thereby restricting their capacity to decode the transmitted IoT information, resulting in better protection for the confidentiality of the IoT device’s transmission. The proposed communication strategy serves as a complementary solution to existing security methods. Analytical and numerical analyses presented in this article validate the effectiveness of the proposed strategy, demonstrating that IoT devices can achieve the desired levels of confidentiality.
As Internet of Things (IoT) has boomed in recent years, many security issues have also been exposed. Focusing on physical layer security in wireless Internet of Things network communication, a series of security methods have been widely studied. Nevertheless, cooperative jamming methods in physical layer security to fight against collusive eavesdroppers have not been thoroughly studied yet. In this article, we study a cooperative-jamming-based physical layer secure transmission scheme for Internet of Things wireless networks in the presence of collusive eavesdroppers. We design a cooperative jamming strategy without knowing the channel state information of eavesdroppers. Considering the cooperation of multiple nodes with multiple antennas, this strategy can maximize the signal-to-interference-plus-noise ratio at an actuator (legitimate receiver). Meanwhile, the generated cooperative jamming signals can reduce the signal-to-interference-plus-noise ratio at eavesdroppers. To explore the theoretical security performance of our strategy, we perform a secrecy outage probability analysis and an asymptotic analysis. In the cases of cooperative jamming and without cooperative jamming, the closed-form expressions of the secrecy outage probability are deduced, and the influence of system parameters on the secrecy outage probability becomes more intuitive through a strict mathematical asymptotic behavior analysis. In addition, considering the energy limitation of Internet of Things devices, we propose a power allocation algorithm to minimize the total transmission power given the security requirements. The numerical results show the effectiveness of our schemes and are consistent with the theoretical analysis.
Physical-layer security (PLS) has become an intriguing technology to address eavesdropping issues in Internet of Things (IoT) systems owing to its low complexity and latency. As wireless communication technology and computing capabilities advance by leaps and bounds, eavesdroppers have enhanced eavesdropping capabilities. They can analyse the environment and move to find better locations for eavesdropping. To mitigate the significant impact of multiple intelligent eavesdroppers extremely close to the device-constrained transmitters in the uplink multiple-input-multiple-output IoT systems, we exploit time-domain artificial noise (AN) in the PLS design and formulate a game problem against the intelligent eavesdroppers. First, we derive the optimal closed-form solution for eavesdroppers and propose a low complexity difference of the convex (LCDC) algorithm to obtain the optimal strategy of the legitimate users and the access point equipped with a zero-forcing receiver. For general linear receivers, we propose a successive convex approximation (SCA) algorithm for the game problem. Simulations are conducted to verify the convergence and effectiveness of our proposed algorithms. The system secrecy performance of the time-domain AN is much better than that of the frequency-domain AN with single-antenna transmitters.
Physical layer security (PLS) has emerged as a new concept and powerful alternative that can complement and may even replace encryption-based approaches, which entail many hurdles and practical problems for future wireless systems. The basic idea of PLS is to exploit the characteristics of the wireless channel and its impairments including noise, fading, interference, dispersion, diversity, etc. in order to ensure the ability of the intended user to successfully perform data decoding while preventing eavesdroppers from doing so. Thus, the main design goal of PLS is to increase the performance difference between the link of the legitimate receiver and that of the eavesdropper by using well-designed transmission schemes. In this survey, we propose a conceptual, generic, and expandable framework for classifying the existing PLS techniques against wireless passive eavesdropping. In this flexible framework, the security techniques that we comprehensively review in this treatise are divided into two primary approaches: signal-to-interference-plus-noise ratio-based approach and complexity-based approach. The first approach is classified into three major categories: first, secrecy channel codes-based schemes; second, security techniques based on channel adaptation; third, schemes based on injecting interfering artificial (noise/jamming) signals along with the transmitted information signals. The second approach (complexity-based), which is associated with the mechanisms of extracting secret sequences from the shared channel, is classified into two main categories based on which layer the secret sequence obtained by channel quantization is applied on. The techniques belonging to each one of these categories are divided and classified into three main signal domains: time, frequency and space. For each one of these domains, several examples are given and illustrated along with the review of the state-of-the-art security advances in each domain. Moreover, the advantages and disadvantages of each approach alongside the lessons learned from existing research works are stated and discussed. The recent applications of PLS techniques to different emerging communication systems such as visible light communication, body area network, power line communication, Internet of Things, smart grid, mm-Wave, cognitive radio, vehicular ad-hoc network, unmanned aerial vehicle, ultra-wideband, device-to-device, radio-frequency identification, index modulation, and 5G non-orthogonal multiple access based-systems, are also reviewed and discussed. The paper is concluded with recommendations and future research directions for designing robust, efficient and strong security methods for current and future wireless systems.
An increasing number of devices exchanges data via the wireless medium into large scale, decentralized, and heterogeneous networks, leading to the concept of Internet of Things (IoT). This PhD work proposes a new practical scheme to perform physical layer security (PLS) in this IoT context.Wireless communications in IoT networks are prone to passive eavesdropping. Therefore, this work introduces a scheme that guarantees the reliability of a communication from a transmitter (Alice) towards a legitimate user (Bob), while preventing multiple passive eavesdroppers (Eve) to correctly decode the data in a worst-cases scenario, thereby considering i) Eve to be noiseless, ii) Eve equipped with an arbitrarily large number of antennas, iii) Alice imperfectly estimating Bob's channel state information (CSI). To do so, a frequency domain time-reversal (TR) precoder is proposed using orthogonal frequency-division multiplexing (OFDM) and artificial noise (AN) injection. The scheme exploits the frequency diversity selective behaviour in multipath channels, and can be incorporated into existing standards, such as in LTE or 5G networks. Different configurations are investigated, namely, single-input single-output (SISO), multiple-input single-output (MISO), and single-input multiple-output (SIMO) systems.The handshake procedures between Alice and Bob are described, both in time-division duplexing (TDD) and frequency-division duplexing (FDD) systems, highlighting the amount of CSI acquisition at Eve, which influences the secrecy performances. Depending on the handshake procedures, different decoding structures are investigated at Eve for each system configuration, considering a block-fading environment. Closed-form approximations of the signal-to-noise ratio required at Bob and the maximal CSI error that can be made at Alice, in order to guarantee a communication ergodic secrecy rate (ESR), are derived. Furthermore, the optimal amount of AN energy to inject, as well as the maximal number of eavesdropper's antennas allowed, considering imperfect CSI, are also given as closed-form expressions. A trade-off on the choice of the spreading factor of the TR precoder is established between maximizing the ESR and decreasing the percentage of outage, leading to information leaked to Eve. Finally, thanks to these results, Alice can be a-priori aware of the ESR over which she can establish a secure communication, assuming worst-case assumptions regarding the eavesdroppers. The PLS scheme presented in this PhD work therefore emerges as a promising solution to secure wireless communications in IoT networks.
With the great-leap-forward development of Internet of Things (IoT), it is extremely important to study secure wireless transmission for IoT systems. A cooperative jamming (CJ) strategy has been extensively studied to enhance physical layer security in IoT systems. However, CJ's secrecy performance has not been well studied in the scenario of collusive eavesdroppers. In this paper, we propose a CJ scheme for IoT systems to fight against multiple passive and collusive eavesdroppers of unknown channel state information. Considering nodes with multi-antenna in an IoT system, we design beamforming vectors to maximize signal-to- interference-plus-noise ratio (SINR) of the wireless link from a controller (transmitter) to an actuator (receiver). Under the worst-case assumption that eavesdroppers can aggregate all signals to enhance their eavesdropping abilities, we derive the closed- form expressions of the secrecy outage probability (SOP) with and without CJ. In addition, we employ a strict mathematical asymptotic analysis to provide insights into the effects of various system parameters on the SOP. Numerical results verify that the CJ scheme can effectively prevent eavesdropping and the effects of system parameters on SOP is consistent with theoretical analytical results.
The Internet of Behaviour (IoB) extends the capabilities of the Internet of Things (IoT) by analysing and influencing human behaviour through behavioural data collected from connected devices. This evolution presents critical privacy concerns, especially for resource-constrained IoB devices where traditional cryptographic techniques may be impractical. Physical Layer Security (PLS) emerges as a lightweight, channel-aware solution that leverages the inherent characteristics of the wireless medium to safeguard data confidentiality. This paper examines the application of adaptive noise injection and cooperative jamming—two promising PLS techniques—for improving privacy in IoB networks. We propose concrete algorithms for both methods, supported by mathematical formulations and theoretical guarantees. Additionally, we assess their applicability, effectiveness, and implementation challenges in real-world IoB environments. Our findings provide a pathway for integrating PLS into privacy-preserving IoB architectures, enabling robust protection against passive eavesdropping without imposing heavy computational burdens on the devices.