Performance Analysis of Loss Multilevel Quantization on the Secret Key Generation Scheme in Indoor Wireless Environment

Abstract

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.

MAPI: Key Generation Scheme for Security in V2V Communication Environment based RSS

“…The measurement results show that the MAPI scheme can reduce KDL M values up to 100% compared to the existing schemes in almost all scenarios. The average value of KDL M in the quiet condition of the scheme [19] is 0.42%, in the scheme [20] is 0.275%, in the scheme [17] is 3.06%, and in the scheme [21] is 18%. For all measurement scenarios, the proposed MAPI scheme has the smallest average KDL M value compared to other comparison schemes.…”

“…Several studies have modified the conventional SKG scheme by adding a signal pre-processing stage to increase wireless channels' reciprocity [16], [21]. Scheme [16], [20] discards the information reconciliation stage for security reasons. There are two methods of quantization, namely lossless quantization and lossy quantization.…”

An Efficient Key Generation for the Internet of Things Based Synchronized Quantization

“…The lower the computing time and the communication overhead required, the more efficient the built key generation system. There are 4 existing key generation systems that will be used for comparison, i.e., system [9,31,33,46,48]. The system [9] uses four phases where the RSS channel characteristics will be quantized using the cumulative distribution function (CDF) method.…”

“…The system [9] uses four phases where the RSS channel characteristics will be quantized using the cumulative distribution function (CDF) method. The system [31] uses five phases where the RSS channel characteristics will be divided into several blocks, each containing 50 data. Each block will be pre-processed using the Kalman method and the results will be converted into multi-bits with the quantization method proposed by [24].…”

“…Some studies [30,31] seek to overcome this problem by modifying the existing signal pre-processing phase. The phase is modified by dividing the measurement data into several blocks of data.…”