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IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)

Performance Evaluation of Secret Key Generation System for Static and Dynamic Condition

Suwadi Suwadi, Wirawan Wirawan, Mike Yuliana

Published Dec 17, 2020• 4 citations
Publisher

Abstract

Received signal strength as one of the physical layer characteristics has been proven to be extracted as a secret key to secure communications carried out by two legitimate parties. Some of the previous secret key generation systems had low key generation speed and were indicated by the key generation value parameter and high bit difference indicated by the key disagreement value parameter. This paper proposes a system that can improve the similarity of RSS between legitimate parties by adding the Kalman Filter pre-process method. The increase in the similarity of received signal strength will be followed by a decrease in the difference in bits obtained so that it will reduce the number of bits wasted in the error-correcting component and will automatically increase the key generation value. The performance evaluation of the built system will be tested in an indoor environment with several scenarios and conditions. There are 2 scenarios used, namely the scenario in the classroom and laboratory and each of them has 2 conditions, namely static and dynamic. The test results show that the best performance is obtained when the Cl scenario and static condition with the key disagreement value of 0.41 and key generation value of 6.48 bps. The proposed system also shows better performance in terms of key disagreement value and key generation value compared to the previous system.

DOI
10.1109/comnetsat50391.2020.9328938

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Received signal strength as one of the physical layer characteristics has been proven to be extracted as a secret key to secure communications carried out by two legitimate parties. Some of the previous secret key generation systems had low key generation speed and were indicated by the key generation value parameter and high bit difference indicated by the key disagreement value parameter. This paper proposes a system that can improve the similarity of RSS between legitimate parties by adding the Kalman Filter pre-process method. The increase in the similarity of received signal strength will be followed by a decrease in the difference in bits obtained so that it will reduce the number of bits wasted in the error-correcting component and will automatically increase the key generation value. The performance evaluation of the built system will be tested in an indoor environment with several scenarios and conditions. There are 2 scenarios used, namely the scenario in the classroom and laboratory and each of them has 2 conditions, namely static and dynamic. The test results show that the best performance is obtained when the Cl scenario and static condition with the key disagreement value of 0.41 and key generation value of 6.48 bps. The proposed system also shows better performance in terms of key disagreement value and key generation value compared to the previous system.
Received Signal Strength (RSS) is a parameter that is widely used in physical layer security systems because of its reciprocal and spatially decorrelated nature. However, RSS values fluctuate, so they require pre-processing before they can be used for reliable secret key generation. This study evaluates the effectiveness of combining Kalman filtering with two quantization methods, Jana multi-bit and multi-bit quantization, on the difference in signal strength (DOSS) data obtained from indoor environments. Testing is carried out by comparing the performance of the Key Generation Rate (KGR) and Key Disagreement Rate (KDR) as indicators of bitstream quality. The experimental results show that the combination of Kalman filtering and multi-bit quantization produces the best performance with a KDR as low as 1% and a KGR of 3.67 kbit/s. In contrast, the Jana multi-bit method without Kalman produces a higher KGR but with a much larger KDR. This finding confirms that quantization strategies-especially multi-bit ones-are critical in improving RSS-based bit quality even before the key generation stage is entirely performed.
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.
In symmetric cryptography systems have problems in the distribution of secret keys. The two users who will communicate require sharing keys through the public channel. The proposed solution to overcome these problems is to utilize information from the physical layer (e.g. RSS). Received Signal Strength (RSS) is an indicator for measuring the power received by wireless devices. The advantage of secret key extraction using physical layer information from a wireless channel is that it allows both devices within the transmission range to extract the secret key together. In this paper, we propose a secret key generation scheme adopted from an existing scheme with modifications to improve performance. Our proposed system is applied to static and dynamic conditions to test performance. The proposed algorithm is able to obtain a reduction in KDR (Key Disagreement Rate) up to 48.42% and an increase in the KGR (Key Generation Rate) up to 23.35% when compared to the existing scheme. Our proposed system also successfully passed the randomness using the NIST test with the approximate value of entropy generated 0.80 in static conditions and 0.81 in dynamic conditions.
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.
Secure communication in Internet of Things (IoT) devices can be improved through physical-layer secret key generation. In secret key generation, an information reconciliation process is required to match the bit sequences between the two communicating devices. However, this process often involves complex statistical computations that increase system overhead and require the transmission of bits over an insecure public channel. Therefore, this research presents a lightweight reconciliation algorithm based on minimal bit syndrome to reduce overhead and improve key security. The proposed method processes quantized Received Signal Strength (RSS) values into 8-bit block syndrome-based reconciliation mechanism and only the 8-bit syndromes from mismatched block are transmitted over the public channel. System testing was conducted under both static and dynamic scenarios in an indoor area using Raspberry Pi nodes. The results show that the proposed scheme demonstrates an improvement in the Key Generation Rate (KGR) by 2.2% and reduces the processing time by 11.6% in dynamic scenario and 8.3% in the static scenario. Also, the proposed scheme reduce the quantization and reconciliation time by 50% compared to previous research. Furthermore, the proposed method maintained a Key Disagreement Rate (KDR) of 0% across all block size and successfully passed the NIST randomness and complexity test, with all test parameters achieving p-values above 0.01. These result indicate that the proposed scheme improve the performance of existing secret key generation methods and it is suitable for implementation in IoT devices.
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.