To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping samples by using B+ tree and quantizing groups is introduced to improve the balance of distribution of channel measurement values in quantization intervals. Based on the conception, a basic B+ tree quantization algorithm (B-BPTQ) and a compensation-technology-based B+ tree quantization algorithm (C-BPTQ) are designed. A LDPC-based multi-scale information reconciliation algorithm (LDPC-MSIR) is put forward to simplify information reconciliation and reduce its computation complexity. An enhanced randomness post-processing algorithm is formulated to increase statistical randomness of initial key sequence. Finally, the performance of the proposed scheme is validated by numerical simulations and field experiments. The experimental results show that it has better performance in terms of key disagreement rate, key generation rate and key randomness compared with other schemes.
To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping samples by using B+ tree and quantizing groups is introduced to improve the balance of distribution of channel measurement values in quantization intervals. Based on the conception, a basic B+ tree quantization algorithm (B-BPTQ) and a compensation-technology-based B+ tree quantization algorithm (C-BPTQ) are designed. A LDPC-based multi-scale information reconciliation algorithm (LDPC-MSIR) is put forward to simplify information reconciliation and reduce its computation complexity. An enhanced randomness post-processing algorithm is formulated to increase statistical randomness of initial key sequence. Finally, the performance of the proposed scheme is validated by numerical simulations and field experiments. The experimental results show that it has better performance in terms of key disagreement rate, key generation rate and key randomness compared with other schemes.
Secret-key distribution leveraging the fading characteristics of wireless optical channels has attracted significant attention. To address the challenges of high-frequency sampling over slowly varying channels, a turbulence-induced fading scrambling-assisted key distribution scheme is proposed to enhance the randomness of shared keys. Combined with random modulation, the scheme enables legitimate parties to obtain more decorrelated wireless signal sequences. Additionally, a specialized interleave quantization (IQ) method is introduced to improve the statistical properties of the generated keys. The entire observation sequence is processed using IQ to mitigate the impact of large-scale slow channel variations. Simulation and experimental results demonstrate that the proposed scheme generates highly random original key sequences at high sampling frequencies without increasing the key disagreement rate (KDR). The final key sequence, incorporating random modulation and interleaving, is evaluated using the NIST test suite, yielding p-values greater than 0.01. These results confirm the effectiveness of the proposed scheme in generating statistically random shared secret keys under slowly varying wireless optical channels.
Vector quantization is a viable solution to the problem as to full utilization of randomness provided by statistically dependent channel measurements in secret key extraction from randomly fluctuating channels. By aiming at atmospheric optical wireless channels, new vector quantization schemes based on sample grouping (SG) are proposed by using different ways, specifically, theK-dimensionaltree (KDT) partition and random placement, to separate samples of the dimension-reduced channel coefficient vector into a given number of groups, with each containing equal number of samples. Use of the KDT partition leads to both the basic KDT-partition-based quantization (B-KDTPQ) and improved KDT-partition-based quantization (I-KDTPQ) schemes. On the other hand, utilization of the random placement brings forth the random equisized grouping based quantization (REGQ) scheme. Performance evaluation shows that, due to use of quantization symbol modification, the I-KDTPQ scheme always has lower quantization symbol disagreement rate (QSDR) than the B-KDTPQ scheme; compared with the I-KDTPQ scheme, the REGQ scheme has more flexibility in accommodating itself to various conditions of channel coefficient fluctuations and noise levels.
Extracting characteristic information from atmospheric optical channels can be utilized to generate shared keys for communication parties. However, the autocorrelation of channel feature information within the correlation time caused by atmospheric turbulence limits the number of unrelated key bits that can be extracted per second. To address this issue, a shared key extraction scheme for random modulation channels is proposed. The scheme employs a controllable shared random source model with memory (CCRSM) to quantify the observed values of CCRSM to obtain keys. During the quantization phase, an interleave block quantization algorithm is employed. Initially, legitimate parties interleave and group the obtained CCRSM observations to eliminate the impact of temporal autocorrelation; subsequently, the processed CCRSM observations are quantified using a single-threshold method per group to obtain an initial bit sequence; finally, an encoding mapping operation is applied to generate the key sequence. This algorithm ensures that the keys extracted between legitimate communication parties have a low inconsistency rate and good randomness, and the key generation rate is significantly improved. Experimental results indicate that this scheme effectively reduces the key disagreement rate and enhances the key generation rate. Under a signal-to-noise ratio (SNR) of 30dB, the scheme achieves a key disagreement rate of 4.39×10−4and a key generation rate of 2.99×106bits per second, and the generated shared random keys pass the randomness tests of the National Institute of Standards and Technology (NIST).
Due to the reciprocity of wireless channels, the communication parties can directly extract the shared key from channel. This solution were verified through several schemes. However, in real situations, channel sampling of legitimate transceivers might be impacted by noises and other interferences, which makes the channel states obtained by initiator and responder might be obvious different. The efficiency and even availability of physical layer key generation are thus reduced. In this paper, we propose a lightweight and efficient physical layer key generation scheme, which extract shared secret keys from channel state information (CSI). To improve the key generation process, the discrete cosine transform (DCT) is employed to reduce differences of channel states of legitimate transceivers. Then, these outputs are quantified and encoded through multi-bit adaptive quantization(MAQ) quantizer and gray code to generate binary bit sequence, which can greatly reduce the bit error rate. Moreover, the low density parity check (LDPC) code and universal hashing functions are used to achieve information reconciliation and privacy amplifification. By adding preprocessing methods in the key generation process and using the rich information of CSI, the security of communications can be increased on the basis of improving the key generation rate. To evaluate this scheme, a number of experiments in various real environments are conducted. The experimental results show that the proposed scheme can effificiently generate shared secret keys for nodes and protect their communication.
This paper presents a novel group secret key generation (GSKG) protocol for multi-user wireless systems with a star topology. In contrast to conventional methods relying on pairwise key derivation followed by reconciliation, the proposed approach enables the central node to directly select a group secret key uniformly at random across the full quantization space. This eliminates the need for intermediate pairwise keys, significantly reducing computational complexity, communication overhead, and latency. To ensure consistent group key reconstruction, we introduce two lightweight, non-coding reconciliation techniques: One-Sided Centering (OSC) and Quantization Pattern Alternation (QPA). Unlike coding-based reconciliation in conventional schemes, OSC and QPA allow the central node to transmit helper data – derived from adjusted measurements or shifted quantization grids – to peripheral nodes. This helper data not only aligns their channel observations with the selected quantization region, but also implicitly distributes the group key. Thus, reconciliation and distribution are seamlessly integrated into a unified protocol. The proposed GSKG framework supports both fully and partially cooperative scenarios and remains robust against unreliable or compromised nodes by selectively omitting or perturbing helper data. Furthermore, a concatenation-based group key construction method exploits existing bidirectional channel measurements to generate multiple key segments, enhancing throughput without additional channel probing. Extensive simulations validate the scheme’s performance in terms of key disagreement rate, key generation rate, computational efficiency, and robustness against eavesdropping. The results confirm that the protocol offers high scalability and security, making it a practical and efficient solution for group key establishment in IoT and other resource-constrained wireless applications.
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.