Physical layer key generation is one of the promising candidate technology schemes for communication network encryption as it promises to solve the difficulties in traditional cryptographic mechanisms. However, due to the existence of unequal key bits in the process of key generation, the practical application of physical layer key generation is greatly hindered. In this paper, in order to eliminate the key inconsistency problem, we propose a Polar code-based information reconciliation scheme (PIRS) by combining the design mechanism of the 5th generation (5G) physical control channel processing flow in the 5G physical layer protocol. The Monte Carlo simulation results show that our proposed method can significantly reduce the key disagreement rate (KDR) and increase the key generation rate (KGR) for both parties in communication, even when the signal-to-noise ratio is low.
Physical layer key generation is one of the promising candidate technology schemes for communication network encryption as it promises to solve the difficulties in traditional cryptographic mechanisms. However, due to the existence of unequal key bits in the process of key generation, the practical application of physical layer key generation is greatly hindered. In this paper, in order to eliminate the key inconsistency problem, we propose a Polar code-based information reconciliation scheme (PIRS) by combining the design mechanism of the 5th generation (5G) physical control channel processing flow in the 5G physical layer protocol. The Monte Carlo simulation results show that our proposed method can significantly reduce the key disagreement rate (KDR) and increase the key generation rate (KGR) for both parties in communication, even when the signal-to-noise ratio is low.
Physical layer key generation (PLKG) offers a lightweight and low-complexity key management solution for future emerging wireless communication networks. However, current PLKG schemes face challenges in effective integration with practical communication systems, hindering their practical deployment. To solve this problem, this paper proposes a key generation scheme integrated with the 5 G physical layer protocol, leveraging the Demodulation Reference Signal (DM-RS) to extract channel estimation for PLKG, enabling efficient key generation. Furthermore, a soft-decision quantization method based on Multibit Adaptive Quantization is proposed which makes key reconciliation input compatible with the soft-decision input requirements of the Low-Density Parity-Check (LDPC) decoder in 5G channel coding module. Simulation results demonstrate that the proposed scheme successfully integrates into the 5G standard communication framework while still maintaining favorable key disagreement rate (KDR) performance, the key reconciliation using keys derived by soft-decision quantization method can achieve better key agreement performance than using keys derived by binary quantization.
Physical-layer based secret key generation (SKG) becomes a research focus as it solves key distribution problem which is difficult in traditional cryptographic mechanism. To remove the disagreements caused by imperfect reciprocity of communicating parties, information reconciliation is a critical process in SKG to obtain symmetric keys. Various reconciliation schemes are proposed, e.g. BBBSS, Cascade, BCH code and Turbo code. Reconciliation efficiency is a common evaluation index which takes reconciliation success rate and information leakage rate into account. However, time delay caused by information interaction and computation overhead may affect reconciliation performance under specific scenarios. Therefore, a comprehensive evaluation metric is required to compare existing schemes. Besides, channel condition changes all the time in real mobile communication systems, and most existing reconciliation schemes only work well in certain channel conditions. Hence, a reconciliation scheme which can adapt to time-varying channel condition is required. In this paper, we introduce a novel comprehensive reconciliation efficiency index (CREI) to evaluate existing reconciliation schemes and propose an adaptive information reconciliation scheme selection (AIRSS) protocol to maximize CREI. The simulation results show the superiority of AIRSS and present recommendations of reconciliation scheme selection in different scenarios.
Wireless networks are vulnerable to various attacks due to their open nature, making them susceptible to eavesdropping and other security threats. Eavesdropping attack takes place at the physical layer. Traditional wireless network security relies on cryptographic techniques to secure data transmissions. However, these techniques may not be suitable for all scenarios, especially in resource-constrained environments such as wireless sensor networks and adhoc networks. In these networks having limited power resources, generating cryptographic keys between mobile entities can be challenging. Also, the cryptographic keys are computationally complex and require key management infrastructure. Physical Layer Key Generation (PLKG) is an emerging solution to address these challenges. It establishes secure communication between two users by taking advantage of the wireless channel's inherent features. PLKG process involves channel probing, quantization, information reconciliation (IR) and privacy amplification to generate symmetric secret key. The researchers have used various PLKG techniques to get the secret key, sTop of Form till they face problems in the IR scheme to obtain symmetric keys between the users who share the same channel for communication. Both the code based and protocol based methods proposed in the literature have advantages and limitations related to their performance parameters such as information leakage, interaction delay and computation complexity. This research work proposes a novel IR mechanism that combines the protocol and code-based error correction methods to obtain reduced Bit Mismatch Rate (BMR), reduced information leakage, reduced interaction delay, and reduced computational time to enhance physical layer secret key's quality. In the proposed research work, the channel samples are generated using the Received Signal Strength (RSS) and Channel Impulse Response (CIR) parameters. These samples are quantized using Vector Quantization with Affinity Propagation Clustering (VQAPC) method to generate the preliminary key. The samples collected by the two users who wish to communicate, (for example Alice and Bob) will be different due to noise in the channel and hardware limitations. Hence their preliminary keys will be different. Removing this discrepancy between Bob's and Alice's initial keys, using novel Hybrid Protocol and Code related Information Reconciliation (HPC-IR) scheme to generate error corrected key, is the most important contribution of this research work. This key is further encoded by the MD5 hash function to generate a final secret key for exchanging information between two users over the wireless channel. It is observed that the proposed HPC-IR scheme achieves BMR of 19.4%, information leakage is 0.002, interaction delay is 0.001 seconds and computation time is 0.02 seconds.
The bloom of 5G communication and beyond serves as a catalyst for physical layer key generation techniques. In 5G communications systems, many challenges in traditional physical layer key generation schemes, such as co-located eavesdroppers, the high bit disagreement ratio, and high temporal correlation, could be overcome. This article lists the key enabling techniques in 5G wireless networks, which offer opportunities to address existing issues in physical layer key generation. We survey the existing key generation methods and introduce possible solutions for the existing issues. The new solutions include applying the high signal directionality in beamforming to resist co-located eavesdroppers, utilizing the sparsity of millimeter-wave channel to achieve a low bit disagreement ratio under low signal-to-noise ratio, and exploiting hybrid precoding to reduce the temporal correlation among measured samples. Finally, the future trends of physical layer key generation in 5G and beyond communications are discussed.
As an alternative and appealing approach to providing information security in wireless communication systems, secret key generation at physical layer has demonstrated its potential in terms of efficiency and reliability over traditional cryptographic methods. Without the necessity of a management centre for key distribution or reliance on computational complexity, physical layer key generation protocols enable two wireless entities to extract identical and dynamic keys from the randomness of the wireless channels associated with them.\nIn this thesis, the reliability of secret key generation at the physical layer is examined in practical wireless channels with imperfect channel state information (CSI). Theoretical analyses are provided to relate key match rate with channel's signal-to-noise ratio (SNR), degrees of channel reciprocity, and iterations of information reconciliation.\nIn order to increase key match rate of physical layer secret key generation, improved schemes in the steps of channel estimation and sample quantization are proposed respectively. In the channel estimation step, multiple observations of the wireless channels are integrated with a linear processor to provide a synthesized and more accurate estimation of the wireless channel. In the sample quantization step, a magnitude based quantization method with two thresholds is proposed to quantize partial samples, where specific quantization areas are selected to reduce cross-over errors. Significant improvements in key match rate are proven for both schemes in theoretical analysis and numerical simulations. Key match rate can even achieve 100% in both schemes with the assistance of information reconciliation process.\nIn the end, a practical application of physical layer secret key generation is presented, where dynamic keys extracted from the wireless channels are utilized for securing secret data transmission and providing efficient access control.
Secure communication in Internet of Things (IoT) devices can be improved through physical-layer secret key generation. In secret key generation, an information reconciliation process is required to match the bit sequences between the two communicating devices. However, this process often involves complex statistical computations that increase system overhead and require the transmission of bits over an insecure public channel. Therefore, this research presents a lightweight reconciliation algorithm based on minimal bit syndrome to reduce overhead and improve key security. The proposed method processes quantized Received Signal Strength (RSS) values into 8-bit block syndrome-based reconciliation mechanism and only the 8-bit syndromes from mismatched block are transmitted over the public channel. System testing was conducted under both static and dynamic scenarios in an indoor area using Raspberry Pi nodes. The results show that the proposed scheme demonstrates an improvement in the Key Generation Rate (KGR) by 2.2% and reduces the processing time by 11.6% in dynamic scenario and 8.3% in the static scenario. Also, the proposed scheme reduce the quantization and reconciliation time by 50% compared to previous research. Furthermore, the proposed method maintained a Key Disagreement Rate (KDR) of 0% across all block size and successfully passed the NIST randomness and complexity test, with all test parameters achieving p-values above 0.01. These result indicate that the proposed scheme improve the performance of existing secret key generation methods and it is suitable for implementation in IoT devices.