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.
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.
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.
Device-to-device communication is increasingly important for emerging wireless applications, including the Internet of Things and industry mobile networks. To establish a secure communication channel between multiple legitimate devices, key agreement is an essential first step. Physical layer channel information is a promising technology for achieving communication security by generating a shared channel key. In this paper, we propose an efficient and random method for generating channel keys based on channel state information (CSI). Firstly, we preprocess the available subcarriers to reduce the correlation of adjacent subcarriers. Secondly, we propose a novel quantization process to generate random and secure channel keys. The part consists of two phases: the quantization phase and the inconsistency removal phase. In the quantization stage, CSI sub carriers are grouped into small blocks, and appropriate thresholds are generated. Then, wireless users quantize the CSI subcarriers into initial bit streams of 0 and 1 with different thresholds. In the inconsistency removal phase, we design an error correction mechanism where wireless users exchange the discarded index sequences in the initial bit streams to achieve key sequence consistency. We implement the proposed scheme using off-the-shelf wireless devices and evaluate its performance. The experimental results show that each CSI packet can produce 30 bits, which have passed the NIST randomness tests.
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.
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.
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.
Physical-layer key generation (PKG) leverages the reciprocity of wireless channel to distribute a symmetric secret key between two legitimate transceivers. This paper proposes an efficient and standard-compliant PKG scheme in 802.11 MIMO-OFDM (multiple-input multiple-output, orthogonal frequency division multiplexing) networks. Firstly, we propose to extract secret keys from a novel feature referred to relative channel state information (RCSI), which can eliminate the non-reciprocity caused by transceiver mismatch and synchronization errors. Specifically, the RCSIs are derived through dividing the channel state informations (CSIs) of non-reference antennas by those of reference antennas. By setting the spatial mapping matrices of the sounding packets as permutation matrices, the reference antennas are determined implicitly without the need for information exchange. Secondly, based on the 802.11 low-density parity-check code (LDPC), we propose an adaptive information reconciliation algorithm, which is flexible to fit the various scenarios with different key lengths and bit disagreement ratios. At last, the overall PKG procedure with detailed frame format design is provided. The proposed scheme is evaluated through an 802.11ax link-level simulation. Numerical results show that the key generation rate of the proposed scheme can achieve 0.47~14Mbps for practical settings.