In today’s world security of information is of utmost importance. Traditionally symmetric and asymmetric cryptographic methods are used to keep information secure. But they face problems of high computational complexity and key management infrastructure. These issues can be resolved by Physical layer key generation (PLKG) schemes which use channel properties to generate a symmetric key. A basic PLKG system consists of probing the wireless channel, quantizing the probed samples and converting them into bits, error detection and correction between the quantized output bits and privacy amplification using secure hash functions. Quantization plays a critical role in PLKG in order to obtain the symmetric secret keys. This paper proposes Vector Quantization with Affinity Propagation Clustering (VQAPC). When the two legitimate users (Alice and Bob) assign a set of samples to different quantization regions, there will be difference in the quantization results which is called as Assignment Disagreement Rate(ADR). Simulation is done using MATLAB software. The proposed quantization method-VQAPC gives very low ADR as compared to the existing methods.
In today’s world security of information is of utmost importance. Traditionally symmetric and asymmetric cryptographic methods are used to keep information secure. But they face problems of high computational complexity and key management infrastructure. These issues can be resolved by Physical layer key generation (PLKG) schemes which use channel properties to generate a symmetric key. A basic PLKG system consists of probing the wireless channel, quantizing the probed samples and converting them into bits, error detection and correction between the quantized output bits and privacy amplification using secure hash functions. Quantization plays a critical role in PLKG in order to obtain the symmetric secret keys. This paper proposes Vector Quantization with Affinity Propagation Clustering (VQAPC). When the two legitimate users (Alice and Bob) assign a set of samples to different quantization regions, there will be difference in the quantization results which is called as Assignment Disagreement Rate(ADR). Simulation is done using MATLAB software. The proposed quantization method-VQAPC gives very low ADR as compared to the existing methods.
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.
Wireless networks get subjected to the different attacks because of it's open nature. Eavesdropping attack, which occurs at the Physical layer of the OSI model, has a great impact on wireless network security. Conventional security in wireless networks depends on the cryptographic techniques. But in wireless sensor networks where a key management infrastructure may not be present and the power resources are also limited, generating a cryptographic key between two mobile entities becomes difficult. Hence Physical layer Security (PLS) has become a novel research solution. In PLS based key generation, a symmetric secret key is obtained at both the ends of the legitimate users using the properties of wireless channel. The key generation process includes four major blocks namely channel measurement, quantization of input samples, error detection and correction and privacy amplification. The output of quantizer has a great effect on the bit mismatch rate (BMR) between the two legitimate users. It also has an impact on key generation rate (KGR). Hence selecting a proper quantizer becomes very essential. In this paper different Quantization schemes are analyzed to achieve effective PLS between the two legitimate users.
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.
This paper proposes a vector-quantization-based secret key generation (SKG) procedure to efficiently extract shared secret keys from correlated channel observations at two communicating terminals, Alice and Bob. Most existing SKG schemes utilize scalar quantization to extract secret key bits separately from each individual channel observation. This approach is simple to implement but yields higher key disagreement probability (or lower key entropy) compared with vector-quantization-based approaches. However, regardless of the quantizer design, quantization for SKG often suffers from the so-called cell-boundary problem, which occurs when the channel observations at Alice and Bob lie close to the quantization cell boundaries, resulting in high probability of key disagreement. In this paper, a general SKG procedure that utilizes sample and quantizer selection techniques to avoid this problem is first proposed. The vector quantizer adopted in the above procedure is designed by minimizing the quadratic distortion between the true channel vector and the noisy observation at Alice (or Bob). Then, by considering the case where the eavesdropper (Eve) may observe a channel vector that is correlated with that observed by Alice and Bob, a clustered key mapping scheme that assigns each secret key to multiple quantization cells in different clusters is also proposed to induce additional randomness at Eve and, thus, maintain high conditional key entropy. The effectiveness of the proposed schemes is demonstrated through computer simulations.
Secure key generation is one of the promising approach to establish secured link between two legitimate nodes for wireless communication. We established a system, which generate the secret key at the both end of the legitimate node. Secure key generation system contain four major block namely channel estimation, quantization, information reconciliation and privacy amplification, in which quantization is one of the important module. In secured key generation, output of the quantizer will affects the bit mismatch rate significantly. The present paper analyses different quantization schemes to make synchronization between two nodes. By applying key generation technique, we analyze effect of quantization bit on the key disagreement rate.
Physical Layer-based Secret Key Generation (PLSKG) between the legitimate nodes from the reciprocal wireless channel is a vastly studied area of Physical Layer Security (PLS). PLSKG aims to secure the wireless link between the legitimate nodes by symmetrically encrypting the wirelessly transmitted information via a secret key that is extracted from the common randomness of the stochastic wireless channel. PLSKG encompasses the intermediate steps of channel sampling, quantization, information reconciliation, and privacy amplification. The PLSKG algorithms are evaluated in terms of quantifiers such as Key Generation Rate (KGR), Key Agreement Probability (KAP), and randomness. The practical PLSKG algorithms (level-crossing algorithms) extract a secret key by analyzing the channel samples and assigning bit sequences to the channel samples lying in different quantization regions. Level-crossing algorithms are lossy and extract a secret key from the central samples of matched excursions between the legitimate nodes. This results in a reduced KGR as there is a scarcity of such matched excursions considering the fast variations of the wireless link between the legitimate nodes. This paper proposes a Two-Round Channel Parsing (TRCP) algorithm that exploits the correlation between the excursion lengths of the channel samples in addition to the sample correlation. TRCP effectively utilize the channel samples by reducing the sample losses incurred by lossy quantizers exploring a new dimension of correlated excursions of the channel samples between legitimate nodes. Simulation results demonstrate that the proposed TRCP scheme enhances the KGR and KAP performance of the secret key and also passes the National Institute of Standards and Technology (NIST) test suite of randomness.