Demand of minimal hardware requirement and low energy consumption for internet of things (IoT) has gained the importance of techniques enhancing the physical layer security. Looking at this, we propose a channel-based mapping diversity (CBMD) scheme for a source (S), destination (D) pair to increase the average bit error rate (ABER) at an eavesdropper (E). CBMD leads to an ABER of 0.5 at E when the channels between S - D and S - E are independent. In the case where S - D and S - E are correlated (due to the proximity of E at D), we derive an optimal strategy at E which leads to the best performance at E. We also derive an optimal strategy at S, assuming E uses its optimal strategy, thereby, considering the worst case scenario. A sub-optimal strategy is also proposed at S which does not require any statistical information about the link S - E and hence, has low implementation complexity. We analyze the variation of ABER at E with the signal to noise ratio (SNR) and the channel correlation coefficient. Our simulation results demonstrate that CBMD indeed leads to significant performance degradation at E even at moderate channel correlation for a properly chosen strategy.
Demand of minimal hardware requirement and low energy consumption for internet of things (IoT) has gained the importance of techniques enhancing the physical layer security. Looking at this, we propose a channel-based mapping diversity (CBMD) scheme for a source (S), destination (D) pair to increase the average bit error rate (ABER) at an eavesdropper (E). CBMD leads to an ABER of 0.5 at E when the channels between S - D and S - E are independent. In the case where S - D and S - E are correlated (due to the proximity of E at D), we derive an optimal strategy at E which leads to the best performance at E. We also derive an optimal strategy at S, assuming E uses its optimal strategy, thereby, considering the worst case scenario. A sub-optimal strategy is also proposed at S which does not require any statistical information about the link S - E and hence, has low implementation complexity. We analyze the variation of ABER at E with the signal to noise ratio (SNR) and the channel correlation coefficient. Our simulation results demonstrate that CBMD indeed leads to significant performance degradation at E even at moderate channel correlation for a properly chosen strategy.
Application of Internet of Things (IoT) in health, defense, banking, and other confidential information transfer urges the need for secure IoT. As most of the IoT devices are resource-limited (antennas, bandwidth, energy), securing the information transfer has always been a challenge. Looking at a solution for enhancing the security of single antenna, single carrier, energy efficient devices, we propose a novel scheme, channel-based mapping diversity. This scheme uses the inherent randomness of the wireless channel and multiple mappings available for an M-ary phase shift keying constellation in confusing an eavesdropper. When the legitimate and the eavesdropper channels are independent of each other, it is shown that a symbol error rate (SER) of (M-1)/ M is induced at the eavesdropper. Whereas, when the channels are correlated, optimal and suboptimal strategies at source and eavesdropper are derived for their respective optimal performances. Further, a closed-form expression for a lower-bound on the SER at the eavesdropper is derived. Simulation results show that for the correlated case, as SNR at the eavesdropper increases, SER initially decreases, later saturates to a relatively high SER, hence making the job of the eavesdropper difficult in getting the legitimate data. Furthermore, the effect of the correlation is more pronounced on SER at higher levels of correlation. This indicates that for practical correlation scenarios, SER is high enough to confuse the eavesdropper.
Security has become an increasingly important issue in wireless communications for the IoT (Internet of Things) environments, to which physical layer approaches can contribute by differentiating desired transceiver and wiretap channels for security of confidential data. In this paper, we propose an optimal power allocation strategy for practical physical-layer security, based on friendly jamming with cancellation for anti-eavesdropping. In particular, secrecy outage probability is evaluated in scenarios involving a pair of transmitter-receiver and a passive eavesdropper near the receiver. We derive the optimal power allocation strategy and the required cancellation capability to enhance secrecy performance. Numerical results verify the tradeoff between jamming power ratio and cancellation capability. Furthermore, our proposed scheme can achieve the improved secrecy rate regardless of availability of eavesdropper channel information.
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.
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.
Internet-of-Things (IoT) networks generally contain resource-constrained devices that require an energy-efficient key generation procedure to producing secure keys at a faster rate. The physical characteristics of the wireless channel can be exploited to secure communication within IoT networks. In particular, secret keys can be generated by leveraging on the randomness of the wireless physical channel between two communicating parties. The conventional mechanism of generating keys at the physical layer, i.e., using channel probing, quantization, information reconciliation, and privacy amplification, may not be preferable for IoT devices. In addition, in some cases IoT devices may be deployed in static environments, wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. This study proposes a mapping table-based key distribution scheme for IoT environments, wherein multiple characteristics of the random channel are combined to improve not only the key generation rate (KGR) but also the key agreement rate (KAR) and bit error rate (BER). In the proposed scheme, both the channel magnitude and the phase are exploited in the key generation process. The proposed scheme is immune to channel estimation errors while providing sufficient randomness in the static environment. Additionally, the scheme is thoroughly investigated for different scenarios including the case of a smarter eavesdropper, which attempts to estimate the channel between the legitimate nodes. This case verifies the robustness of the proposed scheme in different settings and attack models.