63 results about "Artificial noise" patented technology

The present application provides a communication method and an apparatus. The method comprises: on the basis of a first noise signal, a first device generates a first signal, the first signal being used for sensing or ranging between the first device and a second device, and the first noise signal being used for encrypting the sensing or ranging; and the first device sends the first signal to the second device. In the method, the first device generates a sensing or ranging signal having artificial noise, so that only a specified receiving end (second device) can accurately obtain sensing or ranging information, while if receiving the sensing or ranging signal sent by the first device, other devices cannot calculate the correct sensing or ranging information. Thus, the security of wireless sensing or ranging is improved.

The invention discloses an active monitoring method based on short packet communication, and the method comprises the steps: firstly, building a communication system model which comprises monitoring equipment, a target transmitting end and a target receiving end, transmitting a power-adjustable artificial noise signal by the monitoring equipment, and actively interfering a communication link between the target transmitting end and the target receiving end; then, an optimization problem is established by taking maximization of the average effective monitoring rate of monitoring equipment as an optimization target, and meanwhile, the condition that the average decoding error rate of a target receiving end is maintained at a preset target value is taken as a constraint condition; and finally, solving an optimization problem, determining an optimal transmission rate and corresponding artificial noise transmitting power, and guiding monitoring equipment to perform optimal active monitoring. On the premise of ensuring the communication quality of the target link, a more favorable channel condition is created for the monitoring party, and the monitoring performance is remarkably improved compared with the traditional interference-free passive monitoring scheme and the active monitoring scheme with fixed interference power.

The invention discloses a vehicle task unloading method for known potential eavesdropping vehicle CSI, and belongs to the technical field of communication. In order to solve the problem that sensitive information of a task vehicle may be leaked due to potential eavesdropping behaviors of surrounding vehicles in a scene in which channel state information (CSI) in a system is known, the invention provides a vehicle task unloading method for a known potential eavesdropping vehicle (CSI). According to the method, an artificial noise-assisted adaptive eavesdropping coding technology is adopted, the artificial noise power and the transmitting direction of a base station and the transmitting power of a task vehicle are dynamically adjusted according to the real-time position of a vehicle in a system, wireless channel state information (CSI) and task time delay constraint, and the signal-to-noise ratio of a potential eavesdropping vehicle channel is deteriorated, so that the real-time position of the vehicle is determined. The capacity of an eavesdropping channel is reduced, and the system energy consumption required by task unloading is minimized on the basis of ensuring safe task unloading by increasing the legal channel capacity of a task vehicle and improving the secrecy rate.

The invention discloses a high-spectral-efficiency secure transmission method based on orthogonal time-frequency air conditioning, which is applied to an OTFS-NOMA wireless transmission system and comprises the following steps: constructing a time domain signal sending model of a base station for a primary user and a secondary user; the time domain transmission signal model comprises transmission beam forming vectors of a primary user and a secondary user, and a spatial selective artificial noise vector is introduced; wherein the artificial noise vector is constructed by using a semi-unitary matrix and a random vector obeying Gaussian distribution; constructing a system secrecy rate; constructing an optimization problem by taking system secrecy rate maximization as a principle; solving the optimization problem to obtain transmitted beam forming vectors of the primary user and the secondary user and a numerical solution of a covariance matrix, and determining a value of an artificial noise vector based on the numerical solution of the covariance matrix; and the base station generates a time domain sending signal by using the solved transmitted beam forming vector and artificial noise vector of the primary user and the secondary user and sends the signal to the primary user and the secondary user.

A wireless device (1002) may receive a set of positioning signals (1024). The wireless device may measure (1026) a set of positioning signals based on at least one of the plurality of sparse pilot masks or the plurality of artificial noise signals. The wireless device may output (1036) the measured set of positioning signals for training a positioning model. The wireless device may output the measured set of positioning signals for training a positioning model by training a positioning model at the wireless device based on the measured set of positioning signals, or may send the measured set of positioning signals to a training entity for training a positioning model. The training entity may train a positioning model based on the measured set of positioning signals. The wireless device may include a user equipment (UE) or a network node.

Provided is a combined de-aliasing method of one-way wave equation modeling in a frequency-wavenumber domain. 1, nonphysical signal distortion or artificial noise resulting from a folding effect of Fourier transform and undersampling of Fourier transform and improper mathematical operations of numerical truncation or singular value generation from numerical calculation is eliminated in both of a frequency-wavenumber domain and a spatio-temporal domain; and a specific technical solution includes the following steps: step 1, eliminating singular-value aliasing; step 2, eliminating an artificial boundary noise; step 3, eliminating a Fourier folding effect; and step 4, outputting a correct one-way wave equation after eliminating the aliasing. The combined de-aliasing method of one-way wave equation modeling in a frequency-wavenumber domain involves a reasonable denoising technique, is especially aimed at a one-way wave equation modeling equation in an acoustic medium, and can be extended to elastic mediums and viscoelastic mediums.

This invention discloses a secure communication method for eavesdropping on NOMA networks based on artificial noise. In the first time slot, the source user transmits a NOMA signal. The relay user selected according to the maximum-minimum relay selection scheme transmits artificial noise signals to interfere with the eavesdropping user while receiving the signal. In the second time slot, the selected relay user XORs the decoded signal with the artificial noise from the first time slot, reconstructs the signal, and transmits it. The source user also transmits artificial noise to interfere with the eavesdropping user. Each user calculates the required signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR) and the corresponding interruption probability and eavesdropping probability. This invention combines artificial noise, relay cooperation, and one-time pad technology to construct a secure communication scheme. This scheme ensures that the eavesdropping user has only one chance to directly intercept the legitimate user's signal, while in traditional secure communication schemes, the eavesdropping user can directly obtain the source user's signal twice. Therefore, this invention effectively enhances the physical layer security of cooperative NOMA networks.

The invention discloses a rapid high-precision diffusion inversion method and system based on self-supervised learning. The method comprises an initial image potential variable acquisition step, an initial noise estimation acquisition step, a noise prediction step based on a double-branch network structure reverse model and a pseudo noise label prediction step. According to the method, a double-branch architecture design is adopted, global prior of a pre-training diffusion model and fine-grained optimization of image correction branches are combined, and the reconstruction precision is improved through a residual fusion mechanism; through a self-supervised inversion loss function and a pseudo-annotation generation strategy, effective mapping of an image and noise is realized under the condition of no artificial noise annotation; a multi-scale course learning strategy is introduced, so that the model can gradually master the dynamic characteristics of the diffusion process, and the training stability and generalization ability are enhanced; and meanwhile, the number of layers is only increased for an image correction branch in an expansion mechanism, so that the model capacity is improved without damaging diffusion prior, and convergence stability is ensured.

The application discloses a multi-source heterogeneous data adaptive weighting optimization method based on uncertainty, and is a multi-source adaptive weighting optimization method combining Bayesian uncertainty modeling and joint discrimination strategy. In the multi-source heterogeneous data scene which is not sensitive to training loss change, the application introduces uncertainty as the core basis for source-level reliability discrimination, and realizes adaptive adjustment of the multi-source data training weight through a joint discrimination mechanism of loss and uncertainty and a time dynamic parameter control strategy. Without relying on artificial noise labeling or prior reliability information, the method can automatically identify high-noise or distribution mismatch data sources, effectively suppress the gradient contribution of the data sources on the premise of ensuring the stability of model training, and thus improves the overall robustness and generalization performance in the multi-source training environment.

The invention discloses a shore ship adaptive communication method, system and device based on reconfigurable intelligent surface assistance, and relates to the technical field of communication and deep reinforcement learning. The method comprises the following steps: determining a target equivalent channel, an eavesdropping equivalent channel and a diagonal phase shift matrix to be optimized according to a first RIS phased array and a second RIS phased array; determining a base station channel and a superposition channel according to the diagonal phase shift matrix to be optimized, the target equivalent channel and the eavesdropping equivalent channel; determining a total safety rate according to the to-be-optimized beam forming vector and transmission data of the second base station, the to-be-optimized artificial noise vector of the first base station, a base station channel and a superposition channel; constructing constraint conditions according to the maximum transmitting power of the first base station, the to-be-optimized beam forming vector, the to-be-optimized artificial noise vector and the to-be-optimized diagonal phase shift matrix; and based on a multi-strategy value network fusion algorithm, solving a target optimization result by taking the maximum total safety rate as a target and taking a constraint condition as a constraint.

The invention discloses a safety optimization method for an STAR-RIS auxiliary integrated common inductance and energy transfer system. The method mainly comprises the steps that S1, the STAR-RIS auxiliary multi-input single-output integrated common inductance and energy transfer system is constructed; s2, according to the communication scene, one IOT device is located in the STAR-RIS reflection area, and the base station transmits information to the IOT device through the straight-through link and the STAR-RIS reflection link. The sensing scene is that a target is located in a building, the signal intensity of a straight-through link is ignored, and the target is sensed only through an STAR-RIS transmission link; and S3, under the condition that the total emission energy of the base station is limited, constructing an optimization equation for maximizing the safety rate of the system. Performing decoupling optimization solution on active beam forming, artificial noise and STAR-RIS phase shift parameters of the base station based on an alternating optimization algorithm; s4, optimizing active beam forming and artificial noise of the base station; and S5, the STAR-RIS phase shift parameter is solved. According to the invention, the security of a communication system can be obviously improved.

The invention relates to a manual noise reduction intelligent door and window system, and belongs to the technical field of intelligent doors and windows. The manual noise reduction intelligent door and window system comprises an outer frame, a window sash is hinged to the inner side of the outer frame, a positioning groove is formed in the surface of the window sash, and an intelligent noise reduction mechanism connected with the positioning groove in a clamped mode is installed in the outer frame in an embedded mode; the intelligent noise reduction mechanism comprises an annular frame embedded in the inner side of the outer frame, and an annular groove communicating with the positioning groove is formed in the inner side of the annular frame; external noise is collected in real time through the microphone, a built-in AI chip of the Internet of Things microcontroller analyzes noise spectrum and phase and generates reverse interference sound, and the loudspeaker emits sound waves to the noise direction for interference offset, so that structural sound transmission caused by vibration is effectively inhibited, and the problem that the resonance efficiency of an existing door and window sound barrier is remarkably reduced is solved. And the active noise reduction capability is improved.

The invention discloses an unmanned aerial vehicle safety communication integration method based on dual-function artificial noise, which is used for solving the defects that the existing unmanned aerial vehicle safety communication depends on third-party node channel information, and the traditional optimization method is complex in calculation, easy to sink into local optimum and lack of long-term planning capability. A communication unmanned aerial vehicle equipped with a uniform planar array is adopted, and difunctional artificial noise is emitted when serving ground legal users, so that on one hand, third-party nodes are interfered, and on the other hand, noise echoes are used for sensing and tracking the positions of the third-party nodes. In order to solve a high-dimensional non-convex joint optimization problem, deep reinforcement learning is introduced, unmanned aerial vehicle trajectory planning, beam forming and user scheduling are modeled as a Markov decision process, and an intelligent agent is enabled to maximize an optimal strategy of long-term accumulation rewards through environment interaction learning. According to the method, the safety rate and the sensing performance of the system can be remarkably improved in an unknown environment, good robustness and real-time decision-making capability are achieved, and an effective scheme is provided for unmanned aerial vehicle safety communication in a complex scene.

The invention provides a low-altitude electromagnetic spectrum suppression region cooperation method with a pass key, and the method comprises the steps: compiling the pass key, carrying out the full-band suppression of a key protection low-airspace through the combination of the pass key, constructing a special channel, carrying out the noise camouflage of the special channel, and enabling a security part unmanned plane to pass through the pass key and an artificial noise sequence. And communication with a security control system and other security party unmanned aerial vehicles is realized in a special channel. According to the method, the security party unmanned aerial vehicle can realize hidden and reliable cooperative communication under full-band suppression, meanwhile, the communication capability of the intruder unmanned aerial vehicle is effectively rejected, a dynamic secret key mechanism guarantees communication security, noise injection guarantees channel concealment, and the communication efficiency is improved. According to the scheme, the communication guarantee and cooperative combat capability of a low-airspace security task in a complex electromagnetic environment is remarkably improved, and the method has important actual combat value.

The invention belongs to the field of satellite two-way security communication, and particularly discloses a satellite two-way security communication method based on signal constellation splitting and superposition, comprising the following steps: generating a first sending signal and a second sending signal, the real part of the signal bearing privacy information of a user, and the imaginary part bearing artificial noise; the signals are preprocessed to compensate channel responses when the signals are transmitted to the relay node through the first channel and the second channel respectively, so that real parts of the two sent signals have the same coefficient at the relay node; extracting real parts of the two signals, discarding imaginary parts of the two signals, and superposing the two extracted real part signals to form a mixed signal; forwarding the mixed signal to a corresponding user; and demodulating the real part signal of the signal sent by the opposite-end user from the received mixed signal according to the known real part and channel information of the signal sent by the opposite-end user so as to realize information transmission. According to the invention, the embedding of the artificial noise and the constellation superposition can be realized in the single time slot, and the communication security is ensured.

The RIS assisted ISAC system joint optimization method facing eavesdropping confrontation belongs to the field of communication, comprising: taking potential eavesdroppers as sensing targets and modeling the system; taking the RIS reflection phase matrix, the secret signal beam vector and the artificial noise beam vector as joint configuration variables, taking the communication secrecy rate and the target direction sensing accuracy as joint optimization targets, and constructing a multi-objective optimization problem; adopting a random grouping and density sensing non-dominated sorting genetic algorithm, combining a non-dominated sorting method, a random grouping mutation mechanism and a density sensing end front selection strategy to solve the multi-objective optimization problem; and optimizing the joint configuration variables. The method breaks through the limitation of the prior art that only serves legal users, realizes active confrontation to eavesdroppers, avoids the artificial fragmentation caused by variable splitting, can directly find the optimal solution in a multi-dimensional continuous space, and improves the solving efficiency and solution set distribution uniformity under high-dimensional strong coupling variables.

The application discloses an omni-directional physical layer security transmission method, system, device, computer readable storage medium and computer program product based on a uniform circular array, and the method comprises the following steps: constructing a UCA-RFDA system model at a transmitting end, and allocating random frequency offsets to each antenna array element; deriving a steering vector of the UCA-RFDA system model based on a far-field plane wave approximation principle, and establishing a channel model which simultaneously depends on an azimuth angle and a distance; defining a two-dimensional security region with a legal user as a center based on the channel model, deriving a security transmission constraint condition, establishing an elliptical constraint model, and solving a minimum antenna element number and a minimum array diameter; completing array parameter configuration according to the minimum antenna element number and the minimum array diameter, generating artificial noise in a zero space of a legal user channel, constructing a security transmission signal containing an information signal and the artificial noise, and transmitting the security transmission signal. The application realizes omni-directional security coverage by using a uniform circular array, and realizes security enhancement in combination with random frequency diversity.

The application discloses a non-line-of-sight physical layer security transmission method and device and a storage medium, relates to the technical field of wireless communication, and solves the problems of poor communication effect of a direct transmission link between a transmitter and an expected user and even non-existent security communication when the direct transmission link exists. The method comprises the following steps: establishing an intelligent metasurface assisted frequency control array system, and respectively calculating the steering vectors of the transmitter to the expected user, the intelligent metasurface to the expected user and the transmitter to the intelligent metasurface; acquiring and analyzing the signals received by the expected user and an eavesdropper, determining the analysis result, and designing a transmitting beamforming vector and an intelligent metasurface reflection coefficient matrix; calculating an artificial noise projection matrix; and transmitting symbol information according to the calculation result. The method can achieve the effects of secure communication of the transmitter and the expected user through the direct transmission link, more concentrated point-type beam energy and lower sidelobe energy without increasing the system bandwidth.

The present application relates to a kind of HIs under IRS auxiliary terahertz communication system secret rate maximization method, belong to network security field.Communication system often exists transceiver hardware damage and eavesdropper, which can greatly reduce the security performance of communication system.For this problem, to improve system resource utilization efficiency as target, a kind of HIs under IRS auxiliary terahertz communication system secret rate maximization method is proposed.This method uses alternating optimization, continuous convex approximation, semi-definite programming and other convex optimization methods, considers the HIs of base station and IRS, jointly base station beamforming vector, artificial noise and IRS phase shift, maximizes user secret rate, to obtain optimal security transmission performance, and improve system anti-HIs ability.

The invention discloses an RIS-assisted UAV-ISAC system safety energy efficiency optimization method. The method comprises the following steps: collecting channel information data of each link by using an unmanned aerial vehicle (UAV) subsystem; obtaining a channel posteriori covariance according to the channel posteriori distribution and a channel transfer model; a multi-agent PPO decision-making network is constructed, a deep reinforcement learning model DRL is constructed in the multi-agent PPO decision-making network, and the multi-agent PPO decision-making network generates a beam forming matrix of artificial noise AN and generates a total emission signal; and optimizing control parameters of the multi-agent PPO decision network, and outputting the convergent multi-agent PPO decision network to optimize the communication rate, the energy efficiency and the safety performance of the system. According to the method, a Bayesian channel estimation mechanism is introduced, the robustness of the system in a scene that CSI (Channel State Information) is imperfect is improved, and the stability performance of channel uncertainty RMSE and SEE is ensured.

This invention provides a communication method, apparatus, electronic device, and storage medium. The method applied to a transmitting device includes: injecting artificial noise signals into one or more signals to be transmitted to obtain one or more encrypted sequences, and storing the injection positions of the artificial noise signals; randomly clustering a codebook composed of the one or more encrypted sequences to obtain multiple non-empty clusters, and randomly dividing each non-empty cluster into multiple sub-clusters; randomly encoding the sequence number of the non-empty cluster to which each encrypted sequence belongs to obtain a first sequence number corresponding to each encrypted sequence; sending the first sequence number and the encrypted sequence to a receiving device for authentication based on the first sequence number; and generating a private key corresponding to the encrypted sequence based on the injection positions of the artificial noise signals, so that the receiving device can decode the encrypted sequence using the private key after successful authentication. The key generation method employed in this invention improves key randomness and transmission security.

The invention discloses a near-field secure communication hybrid beam focusing method for rate splitting multiple access enabling, and belongs to the technical field of wireless communication and novel multiple access. The method comprises the following steps: S1, constructing a channel model of a near-field legal user and an eavesdropper based on spherical wave propagation characteristics; s2, the base station adopts a rate splitting multiple access technology to split and encode the information of the legal user into a public information stream and a private information stream, and the public information stream is also used as artificial noise to weaken the decoding capability of an eavesdropper; and S3, establishing an optimization problem by taking maximization of the secrecy rate of the worst legal user as a target, and carrying out joint solution on the hybrid beam focusing matrix and the public secrecy rate allocation variable through a penalty-based alternate optimization algorithm. According to the invention, under the condition that the number of radio frequency links is obviously reduced, the performance close to full-digital beam focusing is realized, and compared with a far-field secure transmission scheme, the method has better secrecy performance.

The invention discloses an EPDT safety communication system based on the semantic importance of a power distribution wireless private network. The EPDT safety communication system is suitable for power distribution network fault alarm, load control, electric energy quality monitoring and other time delay sensitive scenes in a 5G / 6G electric power communication network. The system performs efficient compression and processing on power distribution network service data through a semantic communication coding technology, and optimizes queue management in combination with information age AoI and semantic importance SI. Meanwhile, the data transmission security is enhanced through an orthogonal artificial noise AN injection technology, and a cross-layer dynamic optimization model based on a depth deterministic policy gradient (DDPG) is adopted to adjust transmission parameters and security policies in real time according to network states and service requirements.

The application discloses a kind of artificial noise auxiliary de-cellular perception integrated beamforming methods, comprising: multiple distributed access points AP, user, eavesdropper and a perception target are laid out, and access point AP is centrally controlled by central processing unit.First, AP sends signal and receives target reflection signal, and detection probability is calculated based on generalized likelihood ratio test;With this probability as optimization goal, combined with communication demand and eavesdropping restriction, optimization problem is constructed.By analyzing the structure of the problem, it is decomposed into two sub-problems of beamforming and artificial noise joint optimization, and power allocation.The former is transformed into a convex optimization problem using semidefinite relaxation method;The latter uses bisection method to iteratively optimize power allocation, and updates the power allocation parameter optimization interval at each iteration, thereby maximizing system performance under a given total power.The application can effectively improve the detection probability and improve the perception safety under different power constraints with lower complexity.

The invention discloses a communication perception security joint beam forming method for an intelligent granary. The method comprises the following steps: constructing a completely known communication perception integrated system model considering channel state information of an eavesdropper; establishing a communication performance index and a sensing performance index of the ISAC system model; constructing an optimization problem by taking the sum of the minimum communication beam power and the artificial noise power as a target; splitting the optimization problem into three sub-problems by adopting a block coordinate descent method; and solving the sub-problem 1 by using an algorithm combining fractional programming and positive semidefinite relaxation, modeling the sub-problem 2 into positive semidefinite programming and solving, and solving the sub-problem 3 according to generalized Rayleigh entropy to obtain respective optimal solutions of a sensor beam forming vector, an artificial noise covariance matrix and a base station receiving filter vector. According to the method, the safety communication of the system is ensured under the condition that the requirements of communication quality and sensing precision are met, and a high-robustness optimization approach is provided for the intelligent granary which is a multi-node, multi-target and multi-interference-source complex system.

This invention discloses a physical layer security strategy generation method and system for uncertain air-to-ground environments, belonging to the field of communication signal processing technology. The method includes: constructing a downlink multi-user MISO system model incorporating a UAV base station, legitimate users, and eavesdroppers, and using a bounded channel uncertainty model to describe channel errors; constructing an optimization model with the objective of maximizing security and confidentiality; constructing a generator network based on a conditional denoising diffusion probability model, including a channel encoder and a denoising U-Net network; performing two-stage training on the generator network: the first stage learns the conditional distribution of the strategy by minimizing noise prediction error; the second stage introduces a security and confidentiality loss function and a power constraint penalty term for targeted fine-tuning; in actual communication, the fine-tuned model is used to quickly generate beamforming and artificial noise strategies that satisfy power constraints from random noise. This invention significantly improves the physical layer security performance and response speed of air-to-ground communication systems.

The invention relates to an anti-eavesdropping communication system and method based on chaotic MIMO, and belongs to the field of anti-eavesdropping communication in a wireless communication system. The system comprises a transmitter and a receiver, the transmitter comprises a chaotic sequence generator, a Gramer-Schmidt orthogonal device, a chaotic sequence combiner, a bit separator, a chaotic sequence code index selector, a serial-to-parallel converter, an M-PSK modulator, an artificial noise module and a transmitting antenna selector. The receiver comprises a chaotic sequence code index detector, a joint transmitting antenna index and M-PSK modulation symbol detector, a symbol / bit converter and a bit combiner. According to the system, extra information bits are transmitted by using a spatial domain transmitting antenna index and a chaos sequence code index, and coefficients of multiple groups of artificial noise signals are designed, so that interference introduced by artificial noise is completely eliminated at a legal receiver and cannot be completely eliminated at an illegal eavesdropping receiver, and the interference is effectively eliminated. The probability of successful eavesdropping of communication information by an illegal receiver is reduced, and the anti-eavesdropping performance of the system is improved.

The invention discloses an unmanned aerial vehicle auxiliary covert communication system and method based on an energy collection jammer, and belongs to the field of information safety and wireless communication systems. According to the method, the covert communication performance under an Internet of Things system consisting of an information transmitter (Alice), a legal receiver (Bob), an unmanned aerial vehicle (UAV) relay, a potential detector (Willie) and a plurality of energy harvesting jammers (EHJ) is realized; all EHJs collect energy from information transmitted by Alice, then artificial noise interference Willie is emitted to detect hidden information, an EHJ selection and UAV position optimization strategy is provided to maximize hidden capacity, and the detection error probability is maximized by optimizing a detection threshold; while the concealment requirement is met, the influence of key parameters of the system on the detection error probability and the concealment capacity is analyzed through a large amount of numerical calculation; according to the unmanned aerial vehicle assisted Internet of Things system, the energy collection jammer is utilized, and good concealment and safety are achieved in covert communication.

This invention discloses a robust terahertz secure communication method for unmanned aerial vehicles (UAVs). The method first establishes a UAV terahertz secure communication system; then, with the goal of minimizing the total transmit power of the UAV flight base station, it establishes an optimization problem involving the joint UAV trajectory Q, artificial noise vector f, and transmit beamforming vector w; finally, using the block coordinate descent method and the S-process semidefinite relaxation successive convex approximation algorithm, it transforms the optimization problem into a solution, obtaining the optimal UAV trajectory set Q corresponding to minimizing the total transmit power P of the UAV flight base station. b Optimal artificial noise vector f b and the optimal transmit beamforming vector w b This communication method provides accurate channel estimation, resulting in low energy consumption for UAV base stations.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first user equipment (UE) may transmit, to a network node or a second UE, a secret key (SK) / artificial noise (AN) (SK / AN) buffer status report (BSR) that includes information associated with one or more of an SK or an AN. The first UE may transmit, to the network node or the second UE and based at least in part on the SK / AN BSR, a data BSR that indicates data that is available for transmission. The first UE may transmit, to the network node or the second UE, the data that is available based at least in part on the data BSR, wherein the data is secured based at least in part on one or more of the SK or the AN indicated by the SK / AN BSR. Numerous other aspects are described. WO