Comparative Analysis of Quantization Schemes for Physical Layer Key generation

Kadam, Sujata; Gomes, Joanne

doi:10.1109/icast55766.2022.10039641

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…The main goal of quantization method is to generate preliminary key which will have high entropy for security, reduced Bit Mismatch Rate (BMR) between two users using same quantization method so that both the users will have an identical secret key, and higher KGR. Researchers have used lossy and lossless quantizers to convert the probed channel samples into bits [11]. Lossless quantizers are discussed in [12], 19], [21], [23], 24], [25] and lossy quantizers are discussed in [20], [22].…”

Section: Quantizationmentioning

confidence: 99%

“…In the proposed research work, for generation of the secret key, the end users obtain the RSS and CIR samples from the channel. Quantization is performed on these samples using Vector quantization with Affinity propagation clustering (VQAPC) [44]. The research work presented in this paper proposes a novel hybrid, protocol and code related information reconciliation scheme (HPC-IR) by combining the advantages of both cascade protocol and LDPC code.…”

Section: Information Reconciliationmentioning

confidence: 99%

“…By using an error correction procedure, the difference in the key that was received by each user is further eliminated. The reconciled keys are applied to privacy amplification which makes the key secure [11]. The quality of the generated key is measured by parameters such entropy, secrecy, key generation rate, length of the key and so on.…”

Section: Introductionmentioning

confidence: 99%

“…The fundamental components Fig. 1: PLKG system [ 11] of PLKG system have been extensively researched and widely incorporated in the existing literature.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Hybrid Protocol and Code Related Information Reconciliation Scheme for Physical Layer Secret Key Generation

Sujata Kadam

2023

IJRITCC

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Wireless networks are vulnerable to various attacks due to their open nature, making them susceptible to eavesdropping and other security threats. Eavesdropping attack takes place at the physical layer. Traditional wireless network security relies on cryptographic techniques to secure data transmissions. However, these techniques may not be suitable for all scenarios, especially in resource-constrained environments such as wireless sensor networks and adhoc networks. In these networks having limited power resources, generating cryptographic keys between mobile entities can be challenging. Also, the cryptographic keys are computationally complex and require key management infrastructure. Physical Layer Key Generation (PLKG) is an emerging solution to address these challenges. It establishes secure communication between two users by taking advantage of the wireless channel's inherent features. PLKG process involves channel probing, quantization, information reconciliation (IR) and privacy amplification to generate symmetric secret key. The researchers have used various PLKG techniques to get the secret key, sTop of Form till they face problems in the IR scheme to obtain symmetric keys between the users who share the same channel for communication. Both the code based and protocol based methods proposed in the literature have advantages and limitations related to their performance parameters such as information leakage, interaction delay and computation complexity. This research work proposes a novel IR mechanism that combines the protocol and code-based error correction methods to obtain reduced Bit Mismatch Rate (BMR), reduced information leakage, reduced interaction delay, and reduced computational time to enhance physical layer secret key's quality. In the proposed research work, the channel samples are generated using the Received Signal Strength (RSS) and Channel Impulse Response (CIR) parameters. These samples are quantized using Vector Quantization with Affinity Propagation Clustering (VQAPC) method to generate the preliminary key. The samples collected by the two users who wish to communicate, (for example Alice and Bob) will be different due to noise in the channel and hardware limitations. Hence their preliminary keys will be different. Removing this discrepancy between Bob's and Alice's initial keys, using novel Hybrid Protocol and Code related Information Reconciliation (HPC-IR) scheme to generate error corrected key, is the most important contribution of this research work. This key is further encoded by the MD5 hash function to generate a final secret key for exchanging information between two users over the wireless channel. It is observed that the proposed HPC-IR scheme achieves BMR of 19.4%, information leakage is 0.002, interaction delay is 0.001 seconds and computation time is 0.02 seconds.

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Section: Quantizationmentioning

confidence: 99%

Section: Information Reconciliationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The fundamental components Fig. 1: PLKG system [ 11] of PLKG system have been extensively researched and widely incorporated in the existing literature.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Hybrid Protocol and Code Related Information Reconciliation Scheme for Physical Layer Secret Key Generation

Sujata Kadam

2023

IJRITCC

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“…Hence, the preprocessing block is vital in generating a secure key as it reduces noise content and other vulnerabilities in the data set. The data in PLKG is quantized using different quantizers, such as lossy, 14 lossless, 15 uniform, and non‐uniform 16,17 . This process helps reduce the dataset's size, improving power efficiency and reducing computational complexity for PLKG systems or power‐constrained networks like the Internet of Things (IoT).…”

Section: Introductionmentioning

confidence: 99%

Hybrid KuFaI: A novel secure key generation algorithm using fast independent component analysis for physical layer security techniques

Sarsodia,

Bhatt,

Upadhyay

et al. 2024

Security and Privacy

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Many real‐world applications, such as smart cities, industrial automation, health care, and so forth, utilize IoT‐enabled devices as a part of wireless networks. IoT devices must have low power and low computation complexity requirements with proper measures of security challenges. Since traditional cryptography techniques are not computationally efficient, other alternatives, such as physical layer key generation (PLKG), is one of the attractive means to achieve security. In this paper, we propose to use a fast independent component analysis (FICA) based KuFaI (Kurtosis and FICA) algorithm for a secured PLKG system. This method reduces data dimensions and improves system performance regarding Bit Disagreement Rate (BDR) and randomness. In KuFaI, we rearrange the received signal strength indicator (RSSI) data set using FICA and then select components based on the kurtosis function. Results demonstrate that the performance of the proposed algorithm is far better than the previously used PCA‐based algorithm.

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