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IEEE/ACM Transactions on Networking

InaudibleKey2.0: Deep Learning-Empowered Mobile Device Pairing Protocol Based on Inaudible Acoustic Signals

Huanqi Yang, Zhenjiang Li, Chengwen Luo, Bo Wen Wei, Weitao Xu

Published Jun 5, 2024• 5 citations
Publisher

Abstract

The increasing proliferation of Internet-of-Things (IoT) devices in daily life has rendered secure Device-to-Device (D2D) communication increasingly crucial. Achieving secure D2D communication necessitates key agreement between various IoT devices without prior knowledge. Despite existing literature proposing numerous approaches, they exhibit limitations such as low key generation rates and short pairing distances. In this paper, we present InaudibleKey2.0, an inaudible acoustic signal based key generation protocol for mobile devices. Based on acoustic channel reciprocity, InaudibleKey2.0 exploits the acoustic channel frequency response of two legitimate devices as a shared secret for key generation. To significantly enhance performance, InaudibleKey2.0 incorporates novel technologies, including a deep learning-enabled channel prediction model for improved channel reciprocity, a quantization model for increased key generation rates, and a transformer-based reconciliation method for augmented key agreement rates. We conduct comprehensive experiments to evaluate InaudibleKey2.0 in diverse real-world environments. In comparison to state-of-the-art solutions, InaudibleKey2.0 achieves 1.3–9.1 times improvement in key generation rates, 3.2–44 times extension in pairing distances, and 1.2–16 times reduction in information reconciliation counts. Security analysis substantiates that InaudibleKey2.0 is resilient to numerous malicious attacks. Furthermore, we implement InaudibleKey2.0 on modern smartphones and resource-limited IoT devices. The results indicate that it is energy-efficient and can operate on both powerful and resource-limited IoT devices without causing excessive resource consumption.

DOI
10.1109/tnet.2024.3407783

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The increasing proliferation of Internet-of-Things (IoT) devices in daily life has rendered secure Device-to-Device (D2D) communication increasingly crucial. Achieving secure D2D communication necessitates key agreement between various IoT devices without prior knowledge. Despite existing literature proposing numerous approaches, they exhibit limitations such as low key generation rates and short pairing distances. In this paper, we present InaudibleKey2.0, an inaudible acoustic signal based key generation protocol for mobile devices. Based on acoustic channel reciprocity, InaudibleKey2.0 exploits the acoustic channel frequency response of two legitimate devices as a shared secret for key generation. To significantly enhance performance, InaudibleKey2.0 incorporates novel technologies, including a deep learning-enabled channel prediction model for improved channel reciprocity, a quantization model for increased key generation rates, and a transformer-based reconciliation method for augmented key agreement rates. We conduct comprehensive experiments to evaluate InaudibleKey2.0 in diverse real-world environments. In comparison to state-of-the-art solutions, InaudibleKey2.0 achieves 1.3–9.1 times improvement in key generation rates, 3.2–44 times extension in pairing distances, and 1.2–16 times reduction in information reconciliation counts. Security analysis substantiates that InaudibleKey2.0 is resilient to numerous malicious attacks. Furthermore, we implement InaudibleKey2.0 on modern smartphones and resource-limited IoT devices. The results indicate that it is energy-efficient and can operate on both powerful and resource-limited IoT devices without causing excessive resource consumption.
Secure Device-to-Device (D2D) communication is becoming increasingly important with the ever-growing number of Internet-of-Things (IoT) devices in our daily life. To achieve secure D2D communication, the key agreement between different IoT devices without any prior knowledge is becoming desirable. Although various approaches have been proposed in the literature, they suffer from a number of limitations, such as low key generation rate and short pairing distance. In this paper, we present InaudibleKey, an inaudible acoustic signal based key generation protocol for mobile devices. Based on acoustic channel reciprocity, InaudibleKey exploits the acoustic channel frequency response of two legitimate devices as a common secret to generating keys. InaudibleKey employs several novel technologies to significantly improve its performance. We conduct extensive experiments to evaluate the proposed system in different real environments. Compared to state-of-the-art works, InaudibleKey improves key generation rate by 3 times, extends pairing distance by 3.2 times, and reduces information reconciliation counts by 2.5 times. Security analysis demonstrates that InaudibleKey is resilient to a number of malicious attacks. We also implement InaudibleKey on modern smartphones and resource-limited IoT devices. Results show that it is energy-efficient and can run on both powerful and resource-limited IoT devices without incurring excessive resource consumption.
Secure Device-to-Device (D2D) communication is becoming increasingly important with the ever-growing number of Internet-of-Things (IoT) devices in our daily life. To achieve secure D2D communication, the key agreement between different IoT devices without any prior knowledge is becoming desirable. Although various approaches have been proposed in the literature, they suffer from a number of limitations, such as low key generation rate and short pairing distance. In this paper, we present an inaudible acoustic signal based key generation protocol for mobile devices. Based on acoustic channel reciprocity, our system exploits channel frequency response of two legitimate devices as a common secret to generate keys. Extensive experiments are conducted to evaluate the proposed system in different real environments. Evaluation results show that the proposed system can generate the same secret key for two mobile devices with high probability.
To build a secure wireless networking system, it is essential that the cryptographic key is known only to the two (or more) communicating parties. Existing key extraction schemes put the devices into physical proximity and utilize the common inherent randomness between the devices to agree on a secret key, but they often rely on specialized hardware (e.g., the specific wireless NIC model) and have low bit rates. In this article, we seek a key extraction approach that only leverages off-the-shelf mobile devices, while achieving significantly higher key generation efficiency. The core idea of our approach is to exploit the fast varying inaudible acoustic channel as the common random source for key generation and wireless parallel communication for exchanging reconciliation information to improve the key generation rate. We have carefully studied and validated the feasibility of our approach through both theoretical analysis and a variety of measurements. We implement our approach on different mobile devices and conduct extensive experiments in different real scenarios. The experiment results show that our approach achieves high efficiency and satisfactory robustness. Compared with state-of-the-art methods, our approach improves the key generation rate by 38.46% and reduces the bit mismatch ratio by 42.34%.
To build a secure wireless networking system, it is essential that the cryptographic key is known only to the two (or more) communicating parties. Existing key extraction schemes put the devices into the physical proximity, and utilize the common inherent randomness between the devices to agree on a secret key, but they often rely on custom devices and have low bit rate. In this paper, we seek a key extraction approach that only leverages off-the-shelf mobile devices, while achieving significantly higher key generation efficiency. The core idea of our approach is to exploit fast varying inaudible acoustic channel for generating enough randomness and wireless parallel communication for exchanging reconciliation information to improve the key generation rate. We have carefully studied and validated the feasibility of our approach through both theoretical analysis and a variety of measurements. We implement our approach on different mobile devices and conduct extensive experiments in different real scenarios. The experiment results show that our approach achieves high efficiency and satisfactory robustness. Compared with the state of art methods, our approach improves the key generation rate by 38.46% and reduces the bit mismatch ratio by 42.34%.
This article presents a novel low-complexity deep learning model for physical-layer secret key generation (PSKG), specifically designed to enhance wireless security in the Internet of Things (IoT). PSKG typically generates cryptographic keys by exploiting the reciprocal nature of wireless channels; however, this reciprocity is frequently compromised in time-division duplex (TDD) systems due to hardware imperfections and noise, which significantly complicate the key generation process. To effectively address these challenges, the proposed deep neural network (DNN) is developed to efficiently learn and enhance reciprocity features, even in the presence of imperfect channel state information (CSI). Furthermore, the study introduces a DNN-based PSKG method that strategically leverages the phase of channel frequency responses for key extraction. The results conclusively demonstrate that the proposed model substantially reduces the key disagreement ratio (KDR) and enhances randomness, thus providing a robust and practical solution for securing wireless communications in IoT environments.
Devices in the Internet of Things (IoT) are usually limited in computing resources and energy capacity, which means that encryption schemes with higher complexity are not suitable for them to ensure secure communication. As a promising solution to this problem, physical layer key generation suggests that shared secret keys can be generated from noisy wireless channel measurements to enhance the security of wireless communications. In this article, we propose a key generation scheme with extremely low implementation complexity, which allows physical layer key generation to be implemented on IoT nodes. First, we preprocess the channel measurements with simple moving average filtering before quantization to improve channel reciprocity. Next, a bidirectional difference quantization scheme is proposed to realize reliable quantization of channel measurements, which is ingenious in that the quantization process does not depend on quantization thresholds, and thus, the mismatched key bits caused by measurements close to quantization thresholds can be effectively avoided. Then, we propose an improved Cascade protocol to achieve lightweight and efficient information reconciliation. The simulation results show that our scheme can well balance the reliability and efficiency of key generation, and has excellent performance in terms of implementation complexity and key randomness.