Achieving security in the wireless networks by extracting secure bits using physical layer key generation is one of the emerging ideas. However, for the networks with the resource constraint nodes, the security algorithm should be less computationally complex. This can be achieved by reducing the number of numerical computations or by reducing the dimensionality of input data. In this work, we propose to apply dimensionality reduction by the principal component analysis on the input vector of received signal strength for key generation. We select the principal components extracted from the input vector based on information content & cross correlation, and instead of considering all the column of input vector we consider the column vectors corresponding to a few dominant principal components only, for secure key generation. The bit disagreement performance of the system is improved along with the reduction in several numerical calculations corresponding to the rejected input vectors at the cost of few extra computations. This reduces the computational power significantly as verified by simulation and experimental results with sufficient key randomness.
Achieving security in the wireless networks by extracting secure bits using physical layer key generation is one of the emerging ideas. However, for the networks with the resource constraint nodes, the security algorithm should be less computationally complex. This can be achieved by reducing the number of numerical computations or by reducing the dimensionality of input data. In this work, we propose to apply dimensionality reduction by the principal component analysis on the input vector of received signal strength for key generation. We select the principal components extracted from the input vector based on information content & cross correlation, and instead of considering all the column of input vector we consider the column vectors corresponding to a few dominant principal components only, for secure key generation. The bit disagreement performance of the system is improved along with the reduction in several numerical calculations corresponding to the rejected input vectors at the cost of few extra computations. This reduces the computational power significantly as verified by simulation and experimental results with sufficient key randomness.
Physical layer key generation exploiting inherent channel randomness is an open research area in securing the networks with resource constraint nodes; therefore reduction of numerical computation is desirable to save battery power. However, the correlated components due to colored noise also affect the system performance. In this work, we consider the correlated colored noise components along with the additive white Gaussian noise (AWGN) in the wireless channel and analyze the effect of these correlated components on the system performance. We further propose a hybrid averaging and dimensionality reduction (AvDR), based received signal strength (RSS) preprocessing which is the combination of moving window averaging (Av) and principal component analysis (PCA) as dimensionality reduction technique (DR) to improve the system performance. Further, the system performance was evaluated by numerical simulations, and it is observed that the same improvement in system performance is achieved by generating keys from a fewer number of points selected after PCA as compared to processing all the points. Picking a few of the points in the data sequence instead of all reduces the total number of numerical calculations and saves system power, which is the primary requirement of resource constraint networks like the IoT.
Data security is one of the prime concerns in wireless networks. PLKG has been emerging as an attractive alternative to traditional cryptographic techniques. PLKG is more computationally efficient than cryptography. Moreover, PLKG using Principal component analysis (PCA) as pre-processing may further save computations. This paper proposes three mechanisms to select components of PCA which are based on Information content, Mean and Histfit. Bit Disagreement Rate (BDR) is compared for each mechanism. Histfit based method is found to be best. Since only two components are supposed to be processed for key generation, it is computationally efficient/ power efficient too.
Modern networking technologies involve the interconnection of smart and intelligent physical objects to provide advanced services. These physical objects may be part of various network technologies like WLAN, wireless sensor network (WSN), Internet of Things (IoT), etc., and share data in wireless mode, which should be secured from threats. These physical devices possess many constraints like power, computational complexity and storage, and are required to have lightweight security algorithms. Traditionally, security is achieved by the higher layers of the communication model, which has high computational complexity and consumes more power. In this chapter, a secure-key-generation scheme from physical layer characteristics is introduced as a possible lightweight security alternative to traditional upper-layer security approaches. The proposed scheme is based on the wiretap-channel model and security is achieved by generating keys at both communicating ends independently, based on inherent common-channel characteristics like randomness. It is mainly based on the principle of spatial decorrelation and channel reciprocity for identical carrier frequency. There is no provision for sharing keys as in public-key cryptography, so physical-layer key generation is not vulnerable to threats like key leakage. The generated key at the transmitter encrypts plain text; the generated cipher is transmitted on the common channel and is decrypted at the receiver end using the key generated by the receiver. Key generation consists of fundamental blocks like channel probing and quantization followed by information reconciliation and privacy amplification. The physical-layer key generation is already a power-efficient security solution; this chapter aims to enhance this capacity further. This is done by introducing low-end signal conditioning in the channel-probing step using moving-window averaging. This solution not only improves system performance but also makes it suitable for limited- power applications. The performance of the key-generation system is characterised in terms of the bit-disagreement rate between the generated key sequences of communicating parties and the key randomness by means of the NIST statistical test suite.
The growth of IoT in 6G networks necessitates efficient, lightweight security solutions for generating secure symmetric keys in low-power devices, as traditional public-key cryptography is inadequate due to complexity and overhead. In this paper, we propose a novel approach for physical layer key generation using channel reciprocity-based methods. Our contribution lies in the development of a unique feature-extraction method that reduces signal dimensions, enhances computational efficiency, and improves shared key accuracy. Additionally, we introduce an innovative Equalized Fuzzy C-Means (EFCM) vector quantization scheme that ensures clusters of equal size and maximizes entropy and randomness. Existing vector quantization schemes have communication overhead to address high Bit Error Rate (BER) through the exchanging of information over the channel. This can cause information leakage to a potential eavesdropper, which is addressed in our scheme by eliminating this communication overhead. Simulation results demonstrate the superiority of our approach, achieving higher key entropy, lower BER, and improved security compared to traditional scalar quantization and Principal Component Analysis-KMeans (PCA-KM) methods. The proposed scheme offers a promising solution for secure key generation in 6G networks and addresses the challenges posed by IoT devices' limited capabilities.
Abstract Wireless communications between two devices can be protected by secret keys. However, existing key generation schemes suffer from the high bit disagreement rate and low bit generation rate. In this paper, we propose an efficient physical layer key generation scheme by exploring the Received Signal Strength (RSS) of signals. In order to reduce the high mismatch rate of the measurements and to increase the key generation rate, a pair of transmitter and receiver separately apply adaptive quantization algorithm for quantifying the measurements. Then, we implement a randomness extractor to further increase key generation rate and ensure randomness of generated of keys. Several real-world experiments are implemented to verify the effectiveness of the proposed scheme. The results show that compared with the other related schemes, our scheme performs better in bit generation rate, bit disagreement rate, and randomness.
ABSTRACT With the rise of Industry 5.0, smart cities, and the ever‐expanding use of general wireless networks, ensuring seamless communication and robust data security has become a critical challenge. Generating secure secret keys (SKG) through wireless channels is particularly complex in environments where noise and wideband conditions introduce discrepancies and autocorrelation in channel measurements. These issues compromise cross‐correlation and randomness, leading to substantial bit disagreements, distinct keys at the transceivers, and unsuccessful SKG. This research begins by outlining the mathematical model of the signal preprocessing technique called multiscale principal component analysis (MSPCA). Subsequently, it explores the performance of key generation when employing the proposed scheme. A holistic system‐level framework for creating initial shared keys is presented, encompassing quantization methods such as uniform multilevel quantization (UMQ) and encoding methods such as 3‐bit Gray encoding. Monte Carlo‐based simulations in an indoor scenario evaluate system efficacy using metrics like Pearson correlation coefficient, bit disagreement rate (BDR), randomness, and complexity. The proposed scheme achieves a BDR lower than 0.01, a correlation coefficient greater than 0.95, and passes all National Institute of Standards and Technology (NIST) randomness tests, establishing it as a viable solution for securing wireless systems. In the context of Industry 5.0 and smart city infrastructures, where seamless communication and robust data security are paramount, the proposed SKG framework offers significant potential. With its ability to ensure secure and reliable communication, this scheme can underpin the development of advanced wireless systems that cater to the high demands of interconnected ecosystems, enhancing resilience and trust in critical applications.