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.
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.
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.
We evaluate the effectiveness of secret key extraction, for private communication between two wireless devices, from the received signal strength (RSS) variations on the wireless channel between the two devices. We use real world measurements of RSS in a variety of environments and settings. Our experimental results show that (i) in certain environments, due to lack of variations in the wireless channel, the extracted bits have very low entropy making these bits unsuitable for a secret key, (ii) an adversary can cause predictable key generation in these static environments, and (iii) in dynamic scenarios where the two devices are mobile, and/or where there is a significant movement in the environment, high entropy bits are obtained fairly quickly. Building on the strengths of existing secret key extraction approaches, we develop an environment adaptive secret key generation scheme that uses an adaptive lossy quantizer in conjunction with Cascade-based information reconciliation [7] and privacy amplification [14]. Our measurements show that our scheme, in comparison to the existing ones that we evaluate, performs the best in terms of generating high entropy bits at a high bit rate. The secret key bit streams generated by our scheme also pass the randomness tests of the NIST test suite [21] that we conduct.
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.
We evaluate the effectiveness of secret key extraction, for private communication between two wireless devices, from the received signal strength (RSS) variations on the wireless channel between the two devices. We use real world measurements of RSS in a variety of environments and settings. The results from our experiments with 802.11-based laptops show that in certain environments, due to lack of variations in the wireless channel, the extracted bits have very low entropy making these bits unsuitable for a secret key, an adversary can cause predictable key generation in these static environments, and in dynamic scenarios where the two devices are mobile, and/or where there is a significant movement in the environment, high entropy bits are obtained fairly quickly. Building on the strengths of existing secret key extraction approaches, we develop an environment adaptive secret key generation scheme that uses an adaptive lossy quantizer in conjunction with Cascade-based information reconciliation and privacy amplification. Our measurements show that our scheme, in comparison to the existing ones that we evaluate, performs the best in terms of generating high entropy bits at a high bit rate. The secret key bit streams generated by our scheme also pass the randomness tests of the NIST test suite that we conduct. We also build and evaluate the performance of secret key extraction using small, low-power, hand-held devices-Google Nexus One phones-that are equipped 802.11 wireless network cards. Last, we evaluate secret key extraction in a multiple input multiple output (MIMO)-like sensor network testbed that we create using multiple TelosB sensor nodes. We find that our MIMO-like sensor environment produces prohibitively high bit mismatch, which we address using an iterative distillation stage that we add to the key extraction process. Ultimately, we show that the secret key generation rate is increased when multiple sensors are involved in the key extraction process.
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.
Abstract Wireless communications between two devices can be protected by secret keys. However, existing key generation schemes suffer from the high bit disagreement rate and low bit generation rate. In this paper, we propose an efficient physical layer key generation scheme by exploring the Received Signal Strength (RSS) of signals. In order to reduce the high mismatch rate of the measurements and to increase the key generation rate, a pair of transmitter and receiver separately apply adaptive quantization algorithm for quantifying the measurements. Then, we implement a randomness extractor to further increase key generation rate and ensure randomness of generated of keys. Several real-world experiments are implemented to verify the effectiveness of the proposed scheme. The results show that compared with the other related schemes, our scheme performs better in bit generation rate, bit disagreement rate, and randomness.