Physical-layer key generation has emerged as a promising avenue for establishing secret keys using reciprocal channel measurements between wireless devices. However, channel reciprocity may suffer degradation from ambient noise and cause mismatched secret bits, while existing methods mitigating this issue may yet face limitations in key efficiency. The root cause behind such limitations is the heavy reliance on channel measurements, which can be naturally susceptible to channel non-reciprocity attributed to environmental factors. Instead of direct key extraction from channel measurements, we seek to share a pre-defined key and utilize channel measurements as a bearer to facilitate key transmission. We propose an accurate and efficient key generation method (KeyCome) to ensure secure key sharing by encapsulating it with channel state information (CSI) obfuscation matrices through circulant convolution. To this end, we develop a reliable key derivation through a quadratic programming method with matrix equilibration, ensuring stable and rapid solutions. Notably, the transmitter can control the key beforehand for enhanced communication efficiency and combine it with an error correction mechanism for accurate key derivation. Furthermore, a lightweight reconciliation scheme is designed to minimize mismatched bits caused by occasional non-reciprocity. Comprehensive experiments demonstrate KeyCome's high accuracy and efficiency in key generation.
Physical-layer key generation has emerged as a promising avenue for establishing secret keys using reciprocal channel measurements between wireless devices. However, channel reciprocity may suffer degradation from ambient noise and cause mismatched secret bits, while existing methods mitigating this issue may yet face limitations in key efficiency. The root cause behind such limitations is the heavy reliance on channel measurements, which can be naturally susceptible to channel non-reciprocity attributed to environmental factors. Instead of direct key extraction from channel measurements, we seek to share a pre-defined key and utilize channel measurements as a bearer to facilitate key transmission. We propose an accurate and efficient key generation method (KeyCome) to ensure secure key sharing by encapsulating it with channel state information (CSI) obfuscation matrices through circulant convolution. To this end, we develop a reliable key derivation through a quadratic programming method with matrix equilibration, ensuring stable and rapid solutions. Notably, the transmitter can control the key beforehand for enhanced communication efficiency and combine it with an error correction mechanism for accurate key derivation. Furthermore, a lightweight reconciliation scheme is designed to minimize mismatched bits caused by occasional non-reciprocity. Comprehensive experiments demonstrate KeyCome's high accuracy and efficiency in key generation.
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.
Key generation is essential for protecting wireless networks. Based on wireless channel reciprocity, transceivers can generate shared secret keys by measuring their communicating channels. However, due to non-simultaneous measurements, asymmetric noises and other interferences, channel measurements collected by different transceivers are highly correlated but not identical and thus might have some discrepancies. Further, these discrepancies might lead to mismatches of bit sequences after quantization. The referred mismatches significantly affect the efficiency of key generation. In this paper, an efficient key generation scheme leveraging wireless channel reciprocity is proposed. To reduce the bit mismatch rate and enhance the efficiency of key generation, the involved transceivers separately apply discrete cosine transform (DCT) and inverse discrete cosine transform (IDCT) to pre-process their measurements. Then, the outputs of IDCT are quantified and encoded to establish the bit sequence. With the implementations of information reconciliation and privacy amplification, the shared secret key can be generated. Several experiments in real environments are conducted to evaluate the proposed scheme. During each experiment, the shared key is established from the received signal strength (RSS) of heterogeneous devices. The results of experiments demonstrate that the proposed scheme can efficiently generate shared secret keys between transceivers.
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.
Physical layer encryption is a promising solution to provide transmission security for Internet-of-Things (IoT). To realize physical layer encryption, channel state information (CSI) as a random source to generate secret keys should be exploited. The reciprocity of wireless channel between legitimate communication nodes which is typically assumed for time division duplex (TDD) systems, is of critical importance to ensure the consistency in generated keys at two nodes. However, in practical TDD systems, due to the asynchronous measurement of CSI, the receiver noise and the the difference in hardware, etc., the reciprocity of channel measurements between legitimate parties is hard to be guaranteed, which makes physical layer key generation approach infeasible. To address this issue, we propose a wireless key generation scheme based on deep learning techniques. Firstly, a feature extraction network, which consists of two auto-encoders trained jointly, is developed to extract the common feature from the different yet correlated channel observations at two legitimate nodes, which will be used as the source to generate keys. Then a quantizer with an adaptive guard band width is devised to output a binary secret-key sequence from the feature vector. Numerical results show that the proposed scheme achieves remarkable improvement in terms of key disagreement rate (KDR) and key generation rate (KGR) compared existing counterparts in the literature.
Secret key generation exploiting inherent channel randomness stands as an important paradigm for physical-layer security in wireless networks. However, existing work relying on quantization has some difficulties in eliminating inconsistent key bits due to the impact of ambient noise. Recent studies propose to match the segmented channel samples (i.e., channel episodes) of similar variation patterns between legitimate peers to achieve error-free key generation, but they also suffer from high computational overhead and reduced accuracy for large key lengths. This work proposes a secret key generation method based on sorted indices matching (SIM-SKG), aiming at efficient and error-free key generation. Specifically, we sort the channel samples to ensure each channel episode with a unique variation pattern for accurate matching. To avoid the impact of half-duplex communication mode and ambient noise, we propose to match the indices instead of the channel samples as in existing studies. We also develop a noise perturbation scheme that further mitigates the ambiguity during indices matching. Extensive experimental studies demonstrate the high efficiency and accuracy of SIM-SKG under various scenarios for both RSS and CSI channel measurements. Specifically, SIM-SKG achieves error-free key generation with a length of 2048 bits within as little as 1.7msec. Moreover, theoretical analyses and experiments also confirm the security of the SIM-SKG method against various attacks.
Generating keys and keeping them secret is critical in secure communications. Due to the "open-air" nature, key distribution is more susceptible to attacks in wireless communications. An ingenious solution is to generate common secret keys by two communicating parties separately without the need of key exchange or distribution, and regenerate them on needs. Recently, it is promising to extract keys by measuring the random variation in wireless channels, e.g., RSS. In this paper, we propose an efficient Secret Key Extraction protocol without Chasing down Errors, SKECE. It establishes common cryptographic keys for two communicating parties in wireless networks via the realtime measurement of Channel State Information (CSI). It outperforms RSS-based approaches for key generation in terms of multiple subcarriers measurement, perfect symmetry in channel, rapid decorrelation with distance, and high sensitivity towards environments. In the SKECE design, we also propose effective mechanisms such as the adaptive key stream generation, leakage resilient consistence validation, and weighted key recombination, to fully exploit the excellent properties of CSI. We implement SKECE on off-the-shelf 802.11n devices and evaluate its performance via extensive experiments. The results demonstrate that SKECE achieves a more than 3x throughput gain in the key generation from one subcarrier in static scenarios, and due to its high efficiency, a 50% reduction on the communication overhead compared to the state-of-the-art RSS based approaches.