Secret key generation based on channel characteristics is an effective physical-layer security method for 5G wireless networks. The issues of how to ensure the high key generation rate and correlation of the secret key under active attack are needed to be addressed. In this paper, a new practical secret key generation scheme with high rate and correlation is proposed. In our proposed scheme, Alice and Bob transmit independent random sequences instead of known training sequences or probing signals; neither Alice nor Bob can decode these random sequences or estimate the channel. User's random sequences together with the channel effects are used as common random source to generate the secret key. With this solution, legitimate users are able to share secret keys with sufficient length and high security under active attack. We evaluate the proposed scheme through both analytic and simulation studies. The results show that our proposed scheme achieves high key generation rate and key security, and is suitable for 5G wireless networks with resource-constrained devices.
Secret key generation based on channel characteristics is an effective physical-layer security method for 5G wireless networks. The issues of how to ensure the high key generation rate and correlation of the secret key under active attack are needed to be addressed. In this paper, a new practical secret key generation scheme with high rate and correlation is proposed. In our proposed scheme, Alice and Bob transmit independent random sequences instead of known training sequences or probing signals; neither Alice nor Bob can decode these random sequences or estimate the channel. User's random sequences together with the channel effects are used as common random source to generate the secret key. With this solution, legitimate users are able to share secret keys with sufficient length and high security under active attack. We evaluate the proposed scheme through both analytic and simulation studies. The results show that our proposed scheme achieves high key generation rate and key security, and is suitable for 5G wireless networks with resource-constrained devices.
Wireless sensor networks are indispensable across various applications, from environmental surveillance to indus-trial automation, owing to their ability to collect and transmit data autonomously. However, due to the broadcast nature of wireless systems, these systems are vulnerable to eavesdropping attacks. Recently, channel-based secret key generation methods have been widely used in the literature. In these methods, Alice and Bob generate random signals and share these signals with each other. Then, using the secret key paired multiplication with the channel between them, a secret key is shared between legitimate users, while illegitimate nodes cannot access the key. However, these methods consider only two users. This paper proposes a novel method for multiple users. Extensive simulation proves the effectiveness of the proposed method. However, when the number of users increases, the performance of the proposed method decreases.
Channel characteristics-based secret key generation is an effective physical-layer security method.The issues of how to remove the effect of random noise and to balance the key generation rate (KGR) and the bit mismatch rate (BMR) are needed to be addressed.In this paper, to reduce the effect of random noise and extract more secret bits, a new quantization scheme with high key generation rate and low bit mismatch rate is proposed.In our proposed scheme, we try to use all measurements and correct the differences caused by noise at the boundary regions instead of simply dropping them.We evaluate and discuss the improvements of our proposed scheme.The results show that our proposed scheme achieves lower bit mismatch rate as well as remaining high key generation rate.
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.
5G wireless networks are evolving to meet the rapid increase in the demand of the users to get high-quality broadband services with high-speed data rate. This advance development came up with a lot of challenges such as coverage region, security, energy efficiency, spectrum utilization, cost, latency, and data rate. To ensure the security, there are many conventional key exchange algorithms that need complex infrastructure. In recent times, physical layer-based security has gained a lot of attention since it offers the simple and efficient way of key exchange by exploiting wireless channel characteristics. In this project, for secret key sharing between the two legitimate users through the correlated channel that is shared with eavesdropper, a pre-equalization transmit filter that inverts the main channel is employed. Further to decrease the probability of interception by eavesdropper while permitting successful decoding by the legitimate user. Low-Density Parity Check (LDPC) code is used to assure reliable communication. Modulation schemes such as basic QPSK and 64,128 and 256- QAM are used to achieve higher bit rates. To achieve high secrecy between the legitimate users zero forcing algorithm is used to invert the channel. Through simulations, the effect of channel correlation will be studied to analyze the low secret key mismatch between the Bob and Eve. Here Eve having high Bit Error Rate(BER) so that eve could not obtain the original bits. The simulation will be done using Matlab.
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.
Abstract: Physical layer key generation, leveraging the reciprocity and randomness of wireless fading channels, has garnered significant research interest in recent years. While theoretical studies have demonstrated its potential to generate informationtheoretically secure keys, challenges remain in translating theory into practice. This paper provides an overview of the physical layer key generation process and discusses its practical challenges. Various passive and active attacks are analyzed and evaluated through numerical studies. A new key generation scheme using random probing signals and combining usergenerated randomness with channel randomness is introduced to counteract active attacks. Numerical results demonstrate that the proposed scheme achieves higher security strength than existing schemes using constant probing signals under active attacks. Secret-key generation relying on wireless channel reciprocity is an intriguing solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this paper, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS).