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International Electronics Symposium (IES)

RSS-based Secret Key Establishment using Middle-Point Quantization and Clover Filter Algorithm

Choirun Nisa, Amang Sudarsono, Mike Yuliana

Published Sep 1, 2020• 1 citation
Publisher

Abstract

In recent years, the Internet of Things (IoT) becomes popular technology. The one aspect that makes important concern in IoT is the confidentiality of communications. For securing communication in IoT, cryptography algorithm such as symmetrical cryptography requires the secret key exchange process in a public wireless network to ensure the sameness of the secret key. However, the exchange of secret keys in the public wireless network can be exploited by adversaries. So, we present the secret key generation scheme that generates a shared random key through observation of the communication channel parameter i.e. Receive Signal Strength (RSS) between two devices that no need to exchange the secret key. We use Middle-Point quantization to convert the RSS into bit sequences and use Clover Filter to eliminate the error bits after the quantization process. Measurement results showed that the proposed scheme improves the performance of existing schemes if the interval used is 25. The proposed scheme improves the KGR 24 times and improves efficiency to 63%. While for KDR, the proposed scheme can decrease the KDR value of 67.9%. Also, in all scenarios, the proposed scheme can pass the NIST randomness test.

DOI
10.1109/ies50839.2020.9231866

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Sensors•Jun 13, 2019•24 citations
In recent years, the Internet of Things (IoT) becomes popular technology. The one aspect that makes important concern in IoT is the confidentiality of communications. For securing communication in IoT, cryptography algorithm such as symmetrical cryptography requires the secret key exchange process in a public wireless network to ensure the sameness of the secret key. However, the exchange of secret keys in the public wireless network can be exploited by adversaries. So, we present the secret key generation scheme that generates a shared random key through observation of the communication channel parameter i.e. Receive Signal Strength (RSS) between two devices that no need to exchange the secret key. We use Middle-Point quantization to convert the RSS into bit sequences and use Clover Filter to eliminate the error bits after the quantization process. Measurement results showed that the proposed scheme improves the performance of existing schemes if the interval used is 25. The proposed scheme improves the KGR 24 times and improves efficiency to 63%. While for KDR, the proposed scheme can decrease the KDR value of 67.9%. Also, in all scenarios, the proposed scheme can pass the NIST randomness test.
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.
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.
Summary Achieving security in the Internet of things (IoT) networks by generating symmetric keys from the wireless channel parameters like received signal strength (RSS) is a promising approach. Despite the easy acquisition of the RSS signal, RSS‐based security is less explored for IoT. In this work, we analyze the performance of RSS‐based wireless physical layer key generation with correlated colored noise components and proposed a low complexity filtering approach to improve the performance for the IoT network. We started with providing a survey of various recent researches related to RSS‐based key generation and also discussed correlated colored noise components with a few of the recent works considering them. Further, we analyze various colored noise components in the time domain by the Allan variance and Ljung‐Box test. Furthermore, we develop a key generation model and proposed a moving window averaging‐based filtering followed by Lloyd max quantization to improve the BDR performance, degraded due to the presence of correlated colored noise components. The simulation results show that the proposed preprocessing technique has a considerable improvement in the BDR performance, and the keys generated have sufficient randomness, which is verified by NIST test.
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.
For the future Internet of Things (IoT) with ubiquitous wireless connectivity, the physical layer secret key (PLSK) scheme has been recognized as an effective and lightweight way to achieve secure communications by exploiting the reciprocity of the wireless channel. Compared with channel state information (CSI)-based PLSK generation schemes, received signal strength (RSS)-based schemes are more advantageous in terms of the communication costs and mobility for the IoT applications. However, due to the vulnerability of predictable channel attacks, RSS-based schemes cannot always guarantee perfect security. In this paper, we combine angle of arrival (AoA) and received signal strength (RSS) to generate physical layer secret key (PLSK). In particular, we propose a novel measurement named effective key generation rate (EKGR) to comprehensively and directly evaluate a PLSK scheme. Meanwhile, we further simplify the conventional PLSK generation steps to meet the low-complexity demand of IoT devices. At last, numerical results demonstrate that comparing with RSS-based and AoA-based schemes, our proposed EKGR of the RSS-AoA-based scheme achieves 78% or even 120% performance improvement.
One solution to ensure secrecy in the Internet of Things (IoT) is cryptography. However, classical cryptographic systems require high computational complexity that is not appropriate for IoT devices with restricted computing resources, energy, and memory. Physical layer security that utilizes channel characteristics is an often used solution because it is simpler and more efficient than classical cryptographic systems. In this paper, we propose a signal strength exchange (SSE) system as an efficient key generation system and a synchronized quantization (SQ) method as a part of the SSE system that synchronizes data blocks in the quantization phase. The SQ method eliminates the signal pre-processing phase by performing a multi-bit conversion directly from the channel characteristics of the measurement results. Synchronization is carried out between the two authorized nodes to ensure sameness of the produced keys so it can eliminate the error-correcting phase. The test results at the IoT devices equipped with IEEE 802.11 radio show that SSE system is more efficient in terms of computing time and communication overhead than existing systems.