On low-power, low-cost Internet of Things (IoT) edges, coarse-grained entropy source-based physical-layer key generation (PKG) is often used, which results in a very low bit generation rate (BGR). In this paper, a novel PKG scheme, Hinge, designed to adapt to varying environmental conditions is introduced to optimize the trade-off between the bit mismatch rate (BMR) and BGR using fine-grained entropy sources on IoT devices. Hinge predicts channel reciprocity levels from one side and dynamically adjusts the quantization strategy, maintaining a low BMR while maximizing BGR. Compared with existing PKG solutions on Bluetooth devices, Hinge yields significant improvements in BGR, with a comparable BMR. Through extensive experiments, Hinge showcases its potential for providing a secure and efficient key generation mechanism for IoT devices in complex real-world scenarios.
On low-power, low-cost Internet of Things (IoT) edges, coarse-grained entropy source-based physical-layer key generation (PKG) is often used, which results in a very low bit generation rate (BGR). In this paper, a novel PKG scheme, Hinge, designed to adapt to varying environmental conditions is introduced to optimize the trade-off between the bit mismatch rate (BMR) and BGR using fine-grained entropy sources on IoT devices. Hinge predicts channel reciprocity levels from one side and dynamically adjusts the quantization strategy, maintaining a low BMR while maximizing BGR. Compared with existing PKG solutions on Bluetooth devices, Hinge yields significant improvements in BGR, with a comparable BMR. Through extensive experiments, Hinge showcases its potential for providing a secure and efficient key generation mechanism for IoT devices in complex real-world scenarios.
Abstract In quasi-static environment, the performance of physical-layer key generation (PKG) is limited by low entropy. Deploying reconfigurable intelligent surface (RIS) is a mainstream method to solve this problem. However, the secret key performance (SKP) is generally insufficient at low signal-to-noise ratio (SNR). In this paper, we propose an RIS-assisted adaptive PKG scheme. Specifically, we design phase based uniform quantization to enhance the randomness of the RIS channel while simplifying computations. Then, we present an RIS phase shift matrix design based on rejection sampling to adapt the quantization algorithm, which can reduce bit disagreement rate (BDR) and improve key generation rate (KGR). Furthermore, to balance the system’s requirements for low BDR and high KGR, we derive a theoretical model for estimating the BDR probability. By computing the theoretical BDR, we determine the maximum quantization order for different SNRs. Combined with a discard strategy, this enables adaptive selection of the quantization order. Simulation results demonstrate that the proposed scheme achieves lower BDR and higher KGR than existing approaches. Moreover, it does not require complex algorithms, making it suitable for resource-constrained internet of things scenarios. (RIS_Assist_PKG: https://github.com/GQQ1206/RIS_Assist_PKG )
Devices in the Internet of Things (IoT) are usually limited in computing resources and energy capacity, which means that encryption schemes with higher complexity are not suitable for them to ensure secure communication. As a promising solution to this problem, physical layer key generation suggests that shared secret keys can be generated from noisy wireless channel measurements to enhance the security of wireless communications. In this article, we propose a key generation scheme with extremely low implementation complexity, which allows physical layer key generation to be implemented on IoT nodes. First, we preprocess the channel measurements with simple moving average filtering before quantization to improve channel reciprocity. Next, a bidirectional difference quantization scheme is proposed to realize reliable quantization of channel measurements, which is ingenious in that the quantization process does not depend on quantization thresholds, and thus, the mismatched key bits caused by measurements close to quantization thresholds can be effectively avoided. Then, we propose an improved Cascade protocol to achieve lightweight and efficient information reconciliation. The simulation results show that our scheme can well balance the reliability and efficiency of key generation, and has excellent performance in terms of implementation complexity and key randomness.
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.
Physical layer key generation has emerged as a promising solution to secure communications in LoRa networks. However, existing LoRa-based key generation systems suffer from low efficiency and limited security due to their reliance on coarse-grained channel measurements. To overcome the limitation, this paper proposes FineLorKey, the first systematic physical layer key generation framework for LoRa that leverages fine-grained Channel Impulse Response (CIR). FineLorKey introduces a novel CIR extraction method tailored to LoRa Chirp Spread Spectrum (CSS) modulation. This method can be seamlessly integrated into the demodulation process without incurring additional computational overhead. Theoretical analysis demonstrates that the extracted CIR maintains high reliability under the low signal-to-noise ratio (SNR) conditions typical of LoRa environments. Furthermore, to address the dynamic SNR variations inherent in LoRa scenarios, this paper designs an SNR aware quantization scheme based on quantitative bit error rate analysis. The scheme dynamically adjusts the quantization order to maximize entropy extraction. Extensive experiments were conducted in diverse scenarios, including indoor and outdoor environments, line-of-sight and non-line-of-sight conditions, as well as both static and mobile settings. The results show that compared with RSSI-based methods, FineLorKey achieves a more than 10× improvement in key generation rate, reduces the key disagreement rate to below 5%, decreases channel information eavesdropping rate by over 60%, and exhibits strong robustness under large-scale deployment scenarios. These findings underscore the effectiveness and security of FineLorKey and mark a substantial advancement in wireless key generation for long-range, low-SNR wireless environments.
Physical-layer key generation (PKG) relying on wireless channel reciprocity has become a potential research topic as it can provide information-theoretic security guarantees. Various PKG protocols have been proposed to improve key generation rate. However, as a key generation scheme, key rate is not the only important feature. Availability in practical scenario and security resistance are also valuable to be focused on. In order to achieve the availability under quasi-static environment and nearby attack, a scheme named loop-one-block-back key (LOBBY) key generation is proposed. Compared with algorithms raised before, LOBBY only needs one time-frequency block to transmit signal back which saves a quarter energy than conventional algorithms, but still has a powerful bit generation rate (BGR) as before. The simulation of LOBBY shows that correlation of subsequent keys keeps flat near 0.5 in quasi-static environment. As for bit disagreement ratio (BDR) between authorized users, it is less than 0.05 when SNR is 15dB.
The fifth-generation mobile communication technology (5G) supports wireless data transmission across civil, commercial, industrial, and even military networks, where vast amounts of privacy data are constantly transmitted. However, the open nature of the air interface in 5G systems makes them vulnerable to various attacks. Physical-layer key generation (PKG) has been recognized as a highly promising technology for ensuring data security in 5G systems, while existing PKG schemes achieve low key entropy (i.e., low key randomness) due to poor channel probing and quantization. In this paper, we propose a PKG scheme with high key entropy, tailored to the unique characteristics of 5G systems. First, we design a channel probing method based on the demodulation reference signal in accordance with 5G standards, enhancing the similarity between channel measurements. Next, we introduce a quantization method based on local increment and monotonicity, which effectively leverages channel characteristics to achieve high-speed key generation and improve key entropy. Finally, we use both MATLAB simulation and real-world channel measurements to achieve comprehensive verification of the proposed scheme. The simulation results showed that the proposed scheme increases the key entropy by at least 25% with nearly the same key generation rate compared with existing PKG schemes for 5G systems. The experiment using real-world channel measurements also confirmed that the proposed scheme has higher key entropy.