Efficient key generation leveraging channel reciprocity and balanced gray code

Physical-layer key generation (PKG) establishes cryptographic keys from highly correlated measurements of wireless channels, which relies on reciprocal channel characteristics between uplink and downlink, is a promising wireless security technique for Internet of Things (IoT). However, it is challenging to extract common features in frequency-division duplexing (FDD) systems as uplink and downlink transmissions operate at different frequency bands whose channel frequency responses are not reciprocal anymore. Existing PKG methods for FDD systems have many limitations, i.e., high overhead and security problems. This article proposes a novel PKG scheme that uses the feature mapping function between different frequency bands obtained by deep learning to make two users generate highly similar channel features in FDD systems. In particular, this is the first time to apply deep learning for PKG in FDD systems. We first prove the existence of the band feature mapping function for a given environment and a feedforward network with a single hidden layer can approximate the mapping function. Then, a key generation neural network (KGNet) is proposed for reciprocal channel feature construction, and a key generation scheme based on the KGNet is also proposed. Numerical results verify the excellent performance of the KGNet-based key generation scheme in terms of randomness, key generation ratio, and key error rate. Besides, the overhead analysis shows that the method proposed in this article can be used for resource-constrained IoT devices in FDD systems.

Vehicular communication is delay sensitive and demands high security. However, the time for key establishment between node pairs is limited due to the unique features of fast-moving and high dynamics in Vehicular ad hoc networks (VANETs). Moreover, under high-mobility scenarios, the communication performance of Orthogonal Frequency Division Multiplexing (OFDM) signals degrades significantly, while Orthogonal Time Frequency Space (OTFS) signals maintains better performance. Towards this end, considering the time for key establishment, we propose an efficient physical layer secret key generation (PLSKG) scheme utilizing OTFS channel state information (CSI). First, we preprocess the estimated CSI with a moving average coding (MAC) algorithm to improve channel reciprocity. Next, we adopt a bidirectional difference quantization (BDQ) for increased key bit generation and propose a one-way reconciliation protocol to remove bit mismatch. Results from extensive simulations have verified that our scheme achieves random 0-b disagreement keys with a high key generation rate and reduced time for key establishment compared to other schemes.

Channel reciprocity is a very crucial component in establishing a secret key generation scheme. Non-simultaneous measurement conditions and noise cause low channel reciprocity, which is indicated by measurements of channel parameters that are not perfectly identical in both users. The stages of the secret key generation scheme that directly quantifies the channel parameters will have an impact on the high difference in the bits produced. In this paper, we propose the use of Modified Polynomial Regression methods to enhance channel reciprocity that would lower the rate of key disagreement between two users. We also propose a combination of the Modified Polynomial Regression method with multilevel quantization to overcome the trade-off between performance parameters, i.e. the key disagreement rate and key generation rate. The test results conducted in an indoor wireless environment show that our proposed scheme has better performance compared to the existing scheme in terms of increasing reciprocity, key generation rate and decreasing key disagreement rate. The resulting secret key has also fulfilled the randomness requirements set by the National Institutes of Standards and Technology statistical suite.

A local pilot auxiliary key generation scheme for secure underwater acoustic communication

In physical layer security systems there is a clear need to exploit the radio link characteristics to automatically generate an encryption key between two end points. The success of the key generation depends on the channel reciprocity, which is impacted by the non-simultaneous measurements and the white nature of the noise. In this paper, an OFDM subcarriers' channel responses based key generation system with enhanced channel reciprocity is proposed. By theoretically modelling the OFDM subcarriers' channel responses, the channel reciprocity is modelled and analyzed. A low pass filter is accordingly designed to improve the channel reciprocity by suppressing the noise. This feature is essential in low SNR environments in order to reduce the risk of the failure of the information reconciliation phase during key generation. The simulation results show that the low pass filter improves the channel reciprocity, decreases the key disagreement, and effectively increases the success of the key generation.

SecureMD5: A new stream cipher for secure file systems and encryption key generation with artificial intelligence

In this paper, a secret key extraction protocol using interference is proposed in wireless fading channel. It establishes symmetrical keys for two parties in wireless networks via measuring channel gains and utilizes artificial jamming sent by the third party to make the measured channel gains changed quickly. Simulation results demonstrate that the proposed scheme has a higher key generation rate and key randomness than existing key generation schemes.

We present a symmetric physical layer based secret key generation scheme for Point-to-Point Optical Link (PPOL) communication by exploiting Polarization Mode Dispersion (PMD) as a random and inimitable channel characteristic. The randomness and security strength of generated cryptographic keys based on PMD is significantly high. In this paper, we present that random modulation of a probe signal caused by PMD in a high-speed data communication network (40Gb/s and 60Gb/s) is reciprocal with average Pearson correlation coefficient of 0.862, despite the presence of optical nonlinearities, dispersion, and noise in the system. 128-bit symmetric cryptographic key has been successfully generated using the proposed scheme. Moreover, PMD based encryption keys passed the National Institute of Standards and Technology (NIST) tests. We have shown through simulations with a 50km link that, with optimal key generation settings, symmetric keys can be generated with high randomness (high P-values for NIST randomness tests) and with sufficient generation rates (>50%). Furthermore, we considered an attack model of a non-invasive adversary intercepting at 10km into the link and found that the generated keys have high average key bit mismatch rates (>40%).

The physical characteristics of the wireless channel can be exploited to secure communication within Internet-of-Things (IoT) networks. Several techniques have been proposed in the literature; however, the feasibility of such techniques in IoT environments remains unclear. In some cases IoT devices may be deployed in static environments wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. On the other hand, in some cases IoT devices are deployed in dynamic environments wherein the channel properties changes very fast over the time. Key generation schemes proposed for one environment are not directly applicable to the other. While low key generation rate (KGR) is an issue for static environments, higher values of bit error rate (BER) becomes a bottleneck in dynamic environments. This paper proposes a mapping-table based key distribution scheme for IoT networks deployed in both static and dynamic environments. In the proposed scheme, the channel magnitude is exploited in the key generation process. The proposed scheme is immune to channel estimation errors, while providing sufficient randomness in the static environment.

WITHDRAWN: A novel RSS based light weight digital certificate and key generation scheme for coherent communication of IoT devices

Limitations of the computational and energy capabilities of IoT devices provide new challenges in securing communication between devices. Physical layer security (PHYSEC) is one of the solutions that can be used to solve the communication security challenges. In this paper, we conducted an investigation on PHYSEC which utilizes channel reciprocity in generating a secret key, commonly known as secret key generation (SKG) schemes. Our research focused on the efforts to get a simple SKG scheme by eliminating the information reconciliation stage so as to reduce the high computational and communication cost. We exploited the pre-processing method by proposing a modified Kalman (MK) and performing a combination of the method with a multilevel quantization, i.e., combined multilevel quantization (CMQ). Our approach produces a simple SKG scheme for its significant increase in reciprocity so that an identical secret key between two legitimate users can be obtained without going through the information reconciliation stage.

Information theoretic limits for random key generation in multiple-input multiple-output (MIMO) wireless systems exhibiting a reciprocal channel response are investigated experimentally with a new three-node MIMO measurement campaign. As background, simple expressions are presented for the number of available key bits, as well as the number of bits that are secure from a close eavesdropper. Two methods for generating secret keys are analyzed in the context of MIMO channels and their mismatch rate and efficiency are derived. A new wideband indoor MIMO measurement campaign in the 2.51- to 2.59-GHz band is presented, whose purpose is to study the number of available key bits in both line-of-sight and nonline-of-sight environments. Application of the key generation methods to measured propagation channels indicates key generation rates that can be obtained in practice for four-element arrays.

Physical-layer key generation holds significant potential in establishing cryptographic key pairs for emerging LoRa networks. Nevertheless, current key generation solutions may underperform due to critically impaired channel reciprocity, attributed to the low data rate and long range inherent in LoRa networks. In this study, we present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ChirpKey</i>, a novel key generation scheme for LoRa networks. We pinpoint the key hurdles as the coarse-grained channel measurement, inefficient quantization methods, and out-of-range device constraints. To capture fine-grained channel information, we introduce a unique, LoRa-specific channel measurement method that focuses on analyzing chirp-level variations in LoRa packets. We also propose a LoRa channel state estimation algorithm to neutralize asynchronous channel sampling. Instead of the traditional quantization approach, we propose an innovative key delivery method based on perturbed compressed sensing, offering enhanced robustness and security. For LoRa devices beyond each other's communication reach, we integrate relay nodes to ensure reliable key generation. To foster secure group communication, we formulate two protocols that facilitate collaborative key generation across both star and chain configurations. Evaluation across diverse real-world scenarios reveals that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ChirpKey</i> enhances the key matching rate by 11.03–26.58% and increases the key generation rate by 27–49× in comparison to existing leading systems. Our security analysis shows that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ChirpKey</i> can effectively withstand a variety of prevalent attacks. Furthermore, we implement a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ChirpKey</i> prototype, demonstrating its capability to operate within 0.2 s.

The Internet of Things requires developing ultralow power platforms embedding actuators, sensors, and signal processors. In order to limit the power consumption of such systems, nonuniform sampling schemes are very promising solutions, especially if coupled to event-driven circuitries. This strategy allows reducing the amount of sampled data, the system activity, and then the power consumption. Moreover, High-Level Synthesis (HLS) helps designers in rapidly developing ultra-low power platforms. In this article, we present a comparison of the uniform and non-uniform schemes in term of activity and power consumption. This evaluation is performed on Finite Impulse Response (FIR) filters in three different flavors: a synchronous filter using a classical sampling scheme and two asynchronous filters implementing a nonuniform sampling scheme, where one has been manually designed and the other generated by HLS. The filters have been designed in CMOS 350 nm and 40 nm. The filter manually designed provides an area reduction of 8 % and depending on the signal and the application, it is able to consume from 6.6 to 43 times less energy than the synchronous version. The filter produced by HLS exhibits an area reduction of 12%, and consume from 3.3 to 28 times less energy.

With the rapid development of quantum computing technology, traditional public key cryptographic systems face serious threats. Post-quantum cryptographic algorithms have become an important research direction in the field of information security. The Unbalanced Oil and Vinegar (UOV) signature is one of the important candidate schemes in post-quantum cryptography. It can effectively resist quantum computing attacks. However, the extensive matrix multiplication and addition operations during key generation and the intensive computations in the random number generation stage consume substantial CPU resources. This causes the UOV key generation phase to account for more than 90% of the total UOV computational workload. To address these problems, this paper proposes a GPU parallel computing-based optimization scheme for UOV key generation. The approach focuses on accelerating two key components. First, GPU threads are used to parallelize matrix multiplication and addition operations. Thread-level parallel reconstruction and triangular matrix storage optimization are adopted. This achieves a 2.34× acceleration effect. Second, the natural parallel characteristics of AES-CTR mode are fully utilized. GPU multi-level buffering and batch processing techniques are used to optimize the Pseudo-Random Number Generator (PRNG) generation process for partial public key matrices. This obtains a significant 9.88× acceleration. Experimental results show that compared to the current optimal CPU implementation, the proposed GPU parallelization scheme achieves an overall 1.64× acceleration for the UOV algorithm key generation phase.