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.
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.
Channel reciprocity is a very crucial component in establishing a secret key generation scheme. Non-simultaneous measurement conditions and noise cause low channel reciprocity, which is indicated by measurements of channel parameters that are not perfectly identical in both users. The stages of the secret key generation scheme that directly quantifies the channel parameters will have an impact on the high difference in the bits produced. In this paper, we propose the use of Modified Polynomial Regression methods to enhance channel reciprocity that would lower the rate of key disagreement between two users. We also propose a combination of the Modified Polynomial Regression method with multilevel quantization to overcome the trade-off between performance parameters, i.e. the key disagreement rate and key generation rate. The test results conducted in an indoor wireless environment show that our proposed scheme has better performance compared to the existing scheme in terms of increasing reciprocity, key generation rate and decreasing key disagreement rate. The resulting secret key has also fulfilled the randomness requirements set by the National Institutes of Standards and Technology statistical suite.
Limitations of the computational and energy capabilities of IoT devices provide new challenges in securing communication between devices. Physical layer security (PHYSEC) is one of the solutions that can be used to solve the communication security challenges. In this paper, we conducted an investigation on PHYSEC which utilizes channel reciprocity in generating a secret key, commonly known as secret key generation (SKG) schemes. Our research focused on the efforts to get a simple SKG scheme by eliminating the information reconciliation stage so as to reduce the high computational and communication cost. We exploited the pre-processing method by proposing a modified Kalman (MK) and performing a combination of the method with a multilevel quantization, i.e., combined multilevel quantization (CMQ). Our approach produces a simple SKG scheme for its significant increase in reciprocity so that an identical secret key between two legitimate users can be obtained without going through the information reconciliation stage.
Ensuring reliable and secure communications in the increasingly pervasive beyond
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 to
ρ=0.8, the samples excursion qualification threshold is set to
L=3, and GG fading conditions set as defined by
α=2,
ξ=1, and
υ=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).
Shared key generation between two users to exploit the randomness of wireless channels as a source of secret key bits extraction has become an attractive alternative to ensure security in a mobile environment. In this paper, we evaluate the performance of key extraction scheme using measurement results of Received Signal Strength (RSS) on several variations of settings and types of movement. We add the moving average method before the quantization process so our scheme becomes more adaptive to the low variation of RSS, and the use of modified Level Crossing Algorithm to reduce Key Disagreement Rate (KDR) due to half-duplex mode, device limitation, and different types of devices. The results show that our proposed schemes, compared with the existing scheme produce bit stream with the highest entropy, a significant decrease of KDR and passed randomness test from NIST statistical suite.
Secret key generation scheme that utilizesthe randomness of wireless channels is a very promising alternative to establish a secure communication path. Some wireless devices are used to obtain the channel parameters. But the problem that occurs is imprecise measurement results, causinga secret key difference between the two users. To overcome this problem, pre-processing method is used before the data is quantized, to increase the similarity (reciprocity) channel parameter measurement results. In this paper, the effect of the use of one pre-process method, which was hierarchical clustering, on the performance of secret key generation scheme in an indoorenvironment with two variations of scenario was investigated.The results show that the use of the pre-processingmethod can improve the similarity parameter of the channel measurement results as indicated by the increasing of correlation values up to 20%. In addition, the resulting bit mismatch also decreases with the value of key disagreement rate (KDR) maximum of 20%.