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International Electronics Symposium (IES)

Performance Analysis of Group Secret Key Generation in an Outdoor Environment Using Channel Estimation Method

Farel Hafiz Mustafa, Mike Yuliana, Amang Sudarsono

Published Aug 5, 2025• 1 citation
Publisher

Abstract

The increasing use of Internet of Things (IoT) also make data security a very importance. Traditional cryptographic methods are often unsuitable for IoT due to limited processing power and memory capacity, creating a need for lightweight yet effective security solutions. Physical Layer Key Generation (PLKG) offers a promising approach by utilizing the unique characteristics of wireless communication channels to generate secret keys without overloaded system demands. This paper show a performance analysis of Group Secret Key Generation in outdoor environments. The challenges are interfrence, physical obstacles, and dynamic changes in the communication channel was also the part of this analysis. The test results show that group secret key generation achieved optimal performance in Scenario 2, which given a correlation coefficient of 63 %, indicating strong channel similarity between nodes and a bit retention rate of 97.9 % after quantization and error correction. Scenarios 1, 3, and 4 also show a good performance, with correlation coefficients of$41 \%, 14 \%$, and 35 %, and corresponding bit retention rates of$93.1 \%, 90.9 \%$, and 95.2 %, on each tests. All scenarios successfully met the entropy thresholds required for cryptographic applications, which include that randomness and security of the generated keys was confirmed.

DOI
10.1109/ies67184.2025.11161318

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The increasing use of Internet of Things (IoT) also make data security a very importance. Traditional cryptographic methods are often unsuitable for IoT due to limited processing power and memory capacity, creating a need for lightweight yet effective security solutions. Physical Layer Key Generation (PLKG) offers a promising approach by utilizing the unique characteristics of wireless communication channels to generate secret keys without overloaded system demands. This paper show a performance analysis of Group Secret Key Generation in outdoor environments. The challenges are interfrence, physical obstacles, and dynamic changes in the communication channel was also the part of this analysis. The test results show that group secret key generation achieved optimal performance in Scenario 2, which given a correlation coefficient of 63 %, indicating strong channel similarity between nodes and a bit retention rate of 97.9 % after quantization and error correction. Scenarios 1, 3, and 4 also show a good performance, with correlation coefficients of41%,14%41 \%, 14 \%41%,14%, and 35 %, and corresponding bit retention rates of93.1%,90.9%93.1 \%, 90.9 \%93.1%,90.9%, and 95.2 %, on each tests. All scenarios successfully met the entropy thresholds required for cryptographic applications, which include that randomness and security of the generated keys was confirmed.
Since the emergence of Internet of Things (IoT) technology on the surface a few years ago, this IoT technology has been advancing. It has attracted the attention of cybercriminals. One of the cybercrime targets is the security of key management systems and their distribution schemes. This paper offers a solution to this issue by using a physical layer key generation (PLKG) scheme which utilizes the received signal strength indicator (RSSI) from a Long Range (LoRa) device as a key extraction source. The proposed scheme utilizes several methods. Polynomial fitting is used for the initial fitting process, 2-Ary quantization for conversion of RSSI to multibit, BCH to correct the difference in bits obtained between the two authorized users, privacy amplification for increased randomness, and AES-128 for encryption of sent messages. The expected outcome of this paper is that the scheme developed can generate keys with high approximate entropy and fulfills randomness requirements so that there is no need to distribute keys between authorized users. Testing the success of the scheme will be carried out in indoor and outdoor environments with static user positions. The test results show that the keys generated in all scenarios meet the randomness requirements with approximate entropy values above 0.01.
Wireless communication systems are becoming increasingly important in our daily lives, especially with the rapid expansion of the Internet of Things (IoT). Secure and reliable communication is essential for the correct functioning of critical applications and use cases such as healthcare, finance, transportation, and industrial automation. However, the growing number of connected devices introduces significant challenges to data security and privacy due to the open nature of wireless networks. While traditional encryption methods are effective, they can be resource-intensive and impractical for resource-constrained IoT environments. Physical layer security (PLS) provides a lightweight alternative by leveraging the inherent characteristics of wireless channels to generate symmetric secret keys without requiring third-party infrastructure. The PLS key generation process involves four main stages: channel sampling, quantization, reconciliation, and privacy amplification. This paper provides a comprehensive survey of existing quantization schemes, as this step plays a crucial role in determining the key generation rate (KGR) and key disagreement rate (KDR). Additionally, the paper classifies quantization methods as either lossless or lossy, providing insights into the trade-offs between security and efficiency.
Internet-of-Things (IoT) networks generally contain resource-constrained devices that require an energy-efficient key generation procedure to producing secure keys at a faster rate. The physical characteristics of the wireless channel can be exploited to secure communication within IoT networks. In particular, secret keys can be generated by leveraging on the randomness of the wireless physical channel between two communicating parties. The conventional mechanism of generating keys at the physical layer, i.e., using channel probing, quantization, information reconciliation, and privacy amplification, may not be preferable for IoT devices. In addition, in some cases IoT devices may be deployed in static environments, wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. This study proposes a mapping table-based key distribution scheme for IoT environments, wherein multiple characteristics of the random channel are combined to improve not only the key generation rate (KGR) but also the key agreement rate (KAR) and bit error rate (BER). In the proposed scheme, both the channel magnitude and the phase are exploited in the key generation process. The proposed scheme is immune to channel estimation errors while providing sufficient randomness in the static environment. Additionally, the scheme is thoroughly investigated for different scenarios including the case of a smarter eavesdropper, which attempts to estimate the channel between the legitimate nodes. This case verifies the robustness of the proposed scheme in different settings and attack models.
With the increasing demands for sharing confidential information among massive Internet of Things (IoT) devices in 5G and beyond wireless networks, many applications require the common secret key generation for a group of IoT devices. However, most of the existing works on physical layer secret key generation (PLKG) only focus on the pairwise key generation between two users, which is a low efficient and high cost to be extended to the scenarios of group key generation. In this work, we propose a new efficient multiple-input–multiple-output (MIMO) physical layer group secret key generation scheme to reduce the consumption of channel probing and improve the efficiency for group key generation. Different from current schemes, in the proposed scheme, the transmitter randomly generates the group secret key and directly broadcasts the downlink data symbols to the group users. At the receiver end, each group user can efficiently “observe” the common group key through the downlink broadcasting data symbols, while keeping perfect secrecy of the shared group key against eavesdroppers. The performance of reliability, security, and the group key generation rate is fully investigated, which shows the advantages of high efficiency, low consumption, and strong robustness of the proposed scheme. Extensive simulations are conducted to validate the effectiveness of the proposed scheme.
With the burgeoning internet of things (IoT), securing communication becomes paramount. Traditional cryptography does not meet computational needs and brute-force attacks. This review explores the state-of-the-art physical layer secret key generation (PLKG) that takes advantage of the inherent reciprocity and randomness of wireless channels. We investigate cutting-edge techniques such as feature extraction networks, domain adversarial training, and deep learning-based approaches, evaluating their effects on the security and efficiency of key generation. In addition to these methods, the review addresses real-world challenges such as multi-user scenarios, reconciliation overhead, and inconsistent channel measurement. We believe that improved key generation rates and security can be achieved through the use of millimeter wave technology and full-duplex communication. To strengthen the robustness of key generation, the paper concludes by suggesting future directions, such as incorporating more random sources, such as physiological signals and sensor data. This comprehensive overview offers deep insights into the state-of-the-art and paves the way for reliable communication in ever more complicated IoT settings.
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.