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Transactions on Emerging Telecommunications Technologies

A Multiscale Principal Component Analysis Approach to Physical Layer Secret Key Generation in Indoor Environments

Megha Santhosh Kumar, R. Ramanathan

Published Mar 1, 2025• 2 citations
Publisher

Abstract

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.

DOI
10.1002/ett.70100

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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.
The Secret Key Generation (SKG) scheme that exploits the reciprocity and uniqueness of wireless channel between two users plays a significant part in a new increasing distributed security system. The scheme performance can be distinguished based on the low value of Key disagreement Rate (KDR), the high value of Key Generation Rate (KGR), as well as the fulfillment of the NIST randomness standard. The previous SKG scheme has a high KDR due to a direct quantization of a measurement result of the Received Signal Strength (RSS). To overcome the above issue, we conduct a pre-processing of measurement result before quantization with the Kalman method. The pre-process is carried out to improve the channel reciprocity between two legitimate users with the objective to reduce the bit mismatch. Through an experiment, we propose a new quantization scheme called a Modified Multi-Bit (MMB) that uses a multi-bit system on every level of quantization. The test results show that the proposed combination of preprocessing and the MMB scheme has a better performance compared to the existing schemes in terms of KDR and KGR. The Secret Key generated by our scheme also fulfills the NIST randomness standard.
Ensuring reliable and secure communications in the increasingly pervasive beyond5th5{^{\text {th}}}5thgeneration (B5G) wireless networks is one of the key research challenges. Within the physical layer security (PLS) paradigm, the secret key generation (SKG) technique exploits the wireless channel’s randomness to generate symmetric secret keys for message encryption/decryption by legitimate communication nodes. The SKG procedure involves various steps such as wireless channel probing, quantization, information reconciliation, and privacy amplification to render effective symmetric secret key bits. This work proposes a novel multi-level channel quantization scheme, which for the given distribution of the channel envelopes’ gain, ensures an identical likelihood of the envelope samples falling into each quantization interval. Inspired by the classical companding transform (CT), the proposed probability integral transform (PIT)–based quantization scheme works in three sequential steps. First, average contiguous duration (ACD), a second-order fading statistics metric, is considered to select and bias the channel samples that are more likely to fall in the same quantization interval. Subsequently, by using an invertible transform the envelope values are transformed into samples drawn from a uniform distribution, which are then processed through a uniform quantizer. The proposed PIT-based transformation and quantization scheme aims to enhance the trade-offs between the SKG performance metrics namely the key generation rate (KGR), key disagreement rate (KDR), and the key randomness properties. A comprehensive performance analysis of the proposed PIT-based quantization scheme for generalized gamma (GG) fading channels is conducted and its performance is evaluated in relation to several channel and system parameters. Moreover, a comparative analysis of the proposed scheme with its counterparts in the literature is also provided to demonstrate its relative performance gains, where our proposed scheme is observed to outperform the existing schemes. Notably, when the correlation of the reciprocal channel is set toρ=0.8\rho =0.8ρ=0.8, the samples excursion qualification threshold is set toL=3L=3L=3, and GG fading conditions set as defined byα=2\alpha =2α=2,ξ=1\xi =1ξ=1, andυ=1\upsilon =1υ=1, the proposed algorithm, which employs sample biasing and transformation, offers an average improvement of 0.02% in KGR and 0.15% in KDR performance compared to the conventional UQ scheme. Additionally, the algorithm demonstrates superior performance in all considered eight the National Institute of Standards and Technology (NIST) randomness tests, exemplified by an average P-value of 0.78 in the frequency monobit test. Furthermore, for the considered system and channel parameters the proposed algorithm provides an average improvement of 0.06% in KDR compared to cumulative distribution function (CDF)-based non-uniform quantization (CDF-NUQ).
Physical layer security (PLS) techniques hold promise for augmenting secure communications in the 5thgeneration of mobile wireless networks. Secret key generation (SKG) is a PLS technique which exploits the wireless propagation channel's randomness to generate symmetric key bits for information encryption and decryption. This work proposes symmetric key generation based on non-uniform quantization of the received signal strength (RSS) samples of a Nakagami-mmm fading channel. The proposed strategy for non-uniform quantization for SKG aims to set quantization thresholds for maximal key randomness and high values of key generation rate (KGR) and key agreement probability (KAP). Finally, a framework is proposed to use single node RSS measurements, readily available in the literature, to generate RSS samples at the other link end. This framework facilitates the testing of new SKG algorithms that require simultaneous RSS measurements by the legitimate nodes, which are not readily available in the open literature. The effectiveness of the proposed SKG scheme is validated through Monte Carlo methods and the National Institute of Standards and Technology (NIST) test suite for assessing the randomness of the generated key sequence.
This paper aims to develop and evaluate a lightweight and secure Secret Key Generation (SKG) system for static multi-user indoor wireless communication using Received Signal Strength Indicator (RSSI) data. The proposed system integrates fading interpolation, 5-bit multi-bit quantization, Cascade reconciliation, and SHA-128 hashing for privacy amplification. Experiments were conducted at5 m,15 m5 ~\mathrm{m}, 15 ~\mathrm{m}5 m,15 m, and 25 m in a star topology with three legitimate users and one eavesdropper. At 5 m and 15 m, the system achieved high Key Generation Rates (KGR) of13.96%\mathbf{1 3. 9 6 \%}13.96%and14.52%\mathbf{1 4. 5 2 \%}14.52%, with Bit Mismatch Rates (BMR) of 86.73 % and 86.02 %. Cascade reconciliation retained up to 4120 bits from 5000-bit sequences, and SHA-128 ensured all keys were compressed to 128 -bit. NIST testing confirmed strong randomness (entropy 0.93) for legitimate users, while eavesdropper entropy remained low (0.81-0.84). AES-128 encryption successfully decrypted messages for valid pairs and failed for Eve, confirming system security. These results highlight the system's potential for secure and scalable communication in indoor IoT environments.
As Beyond 5thGeneration (B5G) networks expand, securing communication links remains a challenge. Physical Layer Security (PLS) is a promising paradigm, and this work explores wireless channel-based Secret Key Generation (SKG) by proposing an Extended Huffman Coding (EHC) framework to enhance quantization stage. While non-uniform coding is common in Analog-to-Digital (A2D) conversion, it remains largely unexplored in SKG due to key mismatch risks. To address this, we propose a Huffman Coding (HC)-inspired framework that generates binary codes using reversed HC principles and extends them by sequentially altering the Least Significant Bit (LSB), ensuring equal-length unique codes for quantization levels while enhancing generation rate, agreement, and randomness. Additionally, histogram/ Probability Density Function (PDF) matching aligns quantization level probabilities at legitimate nodes to minimize mismatches while exchanging minimal statistical information without compromising secrecy. Unlike conventional quantization, which relies on predetermined codes vulnerable to eavesdropping, our scheme dynamically computes quantization codes at runtime, adding an extra layer of security. Moreover, while conventional HC avoids codes of a level to be a subcode of another level, SKG benefits when one code is a subcode of another, making detection harder. Instead of compression, as desired in conventional A2D conversion, SKG requires longer and random keys that reliably match at legitimate nodes, which our scheme ensures. Simulations are conducted under Rice-fading conditions that evaluate the impact of variations in the Rician K-factor on SKG performance. The proposed method is assessed using key SKG metrics named: Key Agreement Rate (KAR), Key Generation Rate (KGR), and Key Randomness Rate (KRR) (employing the NIST test suite). The obtained results demonstrate the potential of our proposed scheme for secure and scalable SKG solutions in future networks.
The necessity for secured communication devices that has limited computing power has encouraged the development of key generation scheme. The generation of a symmetric key scheme that utilizes randomness of wireless channels offers a most promising solution as a result of the easy distribution of secret key mechanisms. In the last few years, various schemes have been proposed, but there are trade-offs between the performance parameters used. The expected parameters are the low Key Disagreement Rate (KDR), the high Key Generation Rate (KGR), and the fulfillment of standard of randomness. In this paper, we propose the use of a combination of pre-processing methods with multilevel lossy quantization to overcome the trade-off of performance parameters of the Secret Key Generation (SKG) scheme. Pre-process method used to improve reciprocity so as to reduce KDR, whereas multilevel quantization is used to improve the KGR. We use Kalman as the pre-processing method and Adaptive Quantization, Modified Multi-Bit (MMB), and 2-ary Quantization as the multilevel lossy quantization. Testing is conducted by comparing the performance between direct quantization with the addition of the pre-processing method in various multilevel lossy quantization schemes. The test results show that the use of Kalman as pre-processing methods and multilevel lossy quantization can overcome the trade-off performance parameters by reducing KDR and increasing KGR, with the best performance, was obtained when we use adaptive quantization. The resulting secret key has also fulfilled 6 random tests with p values greater than 0.01.