With the rapid advancement of unmanned aerial vehicle (UAV), ensuring the security of communication links among UAVs has become crucial. In this paper, we propose a novel physical layer key generation scheme based on channel codeword reconstruction. In UAV communications, the high mobility of aerial nodes leads to short channel coherence time, which together with noise causes inevitable channel estimation errors. These errors significantly degrades the performance of wireless channel-based key generation. Therefore, we propose a codeword construction algorithm that achieves a polarization characteristic, which effectively segregates reliable keys from unreliable ones. Compared to the existing quantization-based key generation scheme, our approach maximize the utilization of raw channel information and employ soft-decision decoding to generate key. Simulation results demonstrate that the proposed scheme reduces the key disagreement rate for legitimate users and increases the number of consistently generated keys. Furthermore, our method ensures a lower key consistency rate for eavesdropper, which guarantees system security.
With the rapid advancement of unmanned aerial vehicle (UAV), ensuring the security of communication links among UAVs has become crucial. In this paper, we propose a novel physical layer key generation scheme based on channel codeword reconstruction. In UAV communications, the high mobility of aerial nodes leads to short channel coherence time, which together with noise causes inevitable channel estimation errors. These errors significantly degrades the performance of wireless channel-based key generation. Therefore, we propose a codeword construction algorithm that achieves a polarization characteristic, which effectively segregates reliable keys from unreliable ones. Compared to the existing quantization-based key generation scheme, our approach maximize the utilization of raw channel information and employ soft-decision decoding to generate key. Simulation results demonstrate that the proposed scheme reduces the key disagreement rate for legitimate users and increases the number of consistently generated keys. Furthermore, our method ensures a lower key consistency rate for eavesdropper, which guarantees system security.
Unmanned aerial vehicle (UAV) will be an essential carrier for future wireless communications due to its flexible deployment and low cost. As such, the information security of UAV communications is of paramount concern. In this paper, a novel physical layer secret key generation scheme is proposed for air-to-ground (A2G) UAV multiple-input-multiple-output (MIMO) communications, which is applicable in frequency division duplex (FDD) systems. In UAV communications, line-of-sight (LoS) propagation is a distinctive feature, which significantly weakens the performance of channel state information (CSI) based keys. Therefore, a novel channel parameter, three-dimension (3D) spatial angle, is employed to combat against a novel active eavesdropping method, which is termed as Environment Reconstruction based Attack for SEcret keys (ERASE). Compared to the existing plane-angle-based method, our scheme can efficiently utilize spatial resources and provide a higher key generation rate (KGR). The advantages of the proposed scheme are shown through both theoretical analysis and simulations.
In unmanned aerial vehicle (UAV) swarm networks, a group secret key (GSK) is required to enable secured UAV-UAV communications, multicast, and broadcast transmission. Moreover, it can be used for device authentication. Therefore, this paper proposes an efficient GSK protocol denoted as the sequential secret group key (SSGK) algorithm for distributed UAV swarmsecured communications. The proposed protocol utilizes network coding to generate cooperation information that is transmitted on the channel and is uncorrelated with the generated secret key. The proposed protocol depends on the pairwise key generation (PKG) process between pairs of UAVs. However, not all possible pairwise agreements are performed to minimize the time and signaling overhead, i.e., the pairwise key agreement is performed only between selected UAVs as a compromise between the required overhead transmission resources and the achieved redundancy level. The obtained results show that a redundancy level of 4 is sufficient to provide a reliable GSK generation process. The results also show that the performance of the key generation process highly depends on the channelbit error rate (BER), the number of UAVs, and the key length.
In this paper, we address physical-layer key generation between two unmanned aerial vehicles (UAVs) in flight, which are hindered by a dominant line-of-sight component (LOS) in their wireless channel. Although strong LOS component yields better error-performance in data transmission, it is well known that limited randomness in the channel variation will render the underlying physical-layer key generation algorithms ineffective. Pointing at this disadvantage, we explore a relay-based secret-key generation technique between the two UAVs, wherein a ground- stationed relay assists the two UAVs to witness a common source of randomness with higher entropy than their direct channel. We propose the Relay- Assisted Selective Inversion (RASI) protocol, which selectively offers common randomness from either of the channels from the relay to the two UAVs. To showcase the benefits of the RASI protocol, we first obtain theoretical lower bounds on the differential entropy of the common source of randomness, and subsequently employ a practical key-generation algorithm to synthesize the digital keys. We show that RASI can help the two UAVs to generate keys with higher key-rate than using the direct channel only. Finally, we also show that RASI outperforms an existing state-of-the-art relay-based method in terms of key-rate and computational complexity at the UAVs, while marginally losing to the latter in communication- overhead.
In order to enhance the secrecy transmission of unmanned aerial vehicle (UAV) swarm, a novel physical-layer key generation (PLKG) efficient UAV swarm trajectory planning method is proposed in this work. Different from the existing UAV trajectory planning methods that only focus on collision avoidance, energy saving and improving transmission quality, the proposed method incorporates the PLKG capability into the UAV trajectory design. Based on the findings of the fact that the wireless scattering experienced by UAV signals from different UAV trajectories are typically distinct, the channel randomness oriented PLKG behaves differently for various UAV trajectories. As a result, we propose to incorporate the PLKG metric into the UAV trajectory planning objectives, in order to improve the secrecy of UAV swarm transmissions. The theoretical derivation between UAV swarm PLKG metric and the wireless scattering entropy is obtained, and we propose a channel entropy knowledge sharing mechanism for UAV swarm to achieve PLKG efficient swarm trajectory planning. Simulation results show that the key generation performance can be largely improved in comparison to the traditional secrecy rate maximization oriented UAV swarm trajectory planning.
The rapid evolution of unmanned aerial vehicles (UAVs) has positioned air-ground networks as vital infrastructures for diverse applications. However, the open channels of air-ground networks remain inherently vulnerable to persistent eavesdropping threats. While physical-layer key generation (PLKG) offers a lightweight security mechanism by leveraging channel reciprocity to extract shared secrets, the inherent mobility of UAVs introduces a paradoxical tradeoff. Increased channel randomness from dynamic flight patterns enhances security through entropy amplification but simultaneously disrupts channel reciprocity, leading to key mismatch between legitimate parties. Existing PLKG schemes struggle to maintain reliability in key generation due to static channel characteristics and synchronization overhead, limiting their practical deployment in air-ground networks. To resolve this conflict, we propose a Doppler shift key generation (DSKG) scheme that systematically regulates Doppler shifts through UAV trajectory design to derive secure keys. By formulating the problem as a Markov decision process, we develop a proximal policy optimization (PPO)-clip-based reinforcement learning algorithm to dynamically control UAV speed and steering angle, ensuring robust Doppler shift reciprocity while maximizing both key entropy and generation rate. Experimental results quantify the improvements of our scheme over benchmarks in maintaining high key unpredictability and generation efficiency. Furthermore, the analysis provides valuable insights into parameter impacts, confirming the practical viability of the DSKG scheme for securing air-ground communications.
Although unmanned aerial vehicles (UAVs) are enabling various applications in military, public, and commercial fields, the issue of information security in UAV communications is a critical issue which hinder the extensive applications of the UAVs. To cope with this issue, physical layer security is an alternative security technology, which can enhance the information security by flexibly adjusting transmission strategies and parameters to accommodate the channel changes. In this paper, the information security of the UAV communications is investigated from the perspective of physical layer security. The ground-to-air communications are considered under the presence of eavesdroppers, while the UAV can operate in a full-duplex mode so that it can perform cooperative jamming to confuse the eavesdroppers. The achievable secrecy rate of the UAV networks is maximized by the joint designs of the transmit precoding and cooperative jamming. To this end, an intractable optimization problem is formulated, and a solution scheme is proposed by using the approaches of equivalent transformation and alternating optimization. Simulation results demonstrate that the proposed scheme achieves a notable improvement in secrecy rate.