Cognitive Jammers Assisted Covert Communication in Cognitive Radio Networks

In this work,we investigate the covert communication in cognitive radio(CR)networks with the existence of multiple cognitive jammers(CJs).Specifically,the secondary transmitter(ST)helps the primary transmitter(PT)to relay information to primary receiver(PR),as a reward,the ST can use PT's spectrum to transmit private information against the eavesdropper(Eve)under the help of one selected cognitive jammer(CJ).Meanwhile,we propose three jammer-selection schemes,namely,link-oriented jammer selection(LJS),min-max jammer selection(MMJS)and random jammer selection(RJS).For each scheme,we analyze the average covert throughput(ACT)and covert outage probability(COP).Our simulation results show that CJ is helpful to ST's covert communication,the expected minimum detection error probability and ACT can be significantly improved with the increase of false alarm of CJ.Moreover,the LJS scheme achieves best performance in ACT and COP,followed by RJS scheme,and MMJS scheme shows the worst performance.

Cooperative Covert Communication in Multi-Antenna Broadcast Channels

With the gradual popularization of 5G communications,the application of multi-antenna broadcasting technology has become widespread.Therefore,this study aims to investigate the wireless covert communication in the two-user cooperative multi-antenna broadcast channel.We focus on the issue that the deteriorated reliability and undetectability are mainly affected by the transmission power.To tackle this issue,we design a scheme based on beamforming to increase the reliability and undetectability of wireless covert communication in the multi-antenna broadcast channel.We first modeled and analyzed the cooperative multi-antenna broadcasting system,and put forward the target question.Then we use the SCA(successive convex approximation)algorithm to transform the target problem into a series of convex subproblems.Then the convex problems are solved and the covert channel capacity is calculated.In order to verify the effectiveness of the scheme,we conducted simulation verification.The simulation results show that the proposed beamforming scheme can effectively improve the reliability and undetectability of covert communication in multi-antenna broadcast channels.

Gamma Approximation Based Multi-Antenna Covert Communication Detection

Covert communication technology makes wireless communication more secure,but it also provides more opportunities for illegal users to transmit harmful information.In order to detect the illegal covert communication of the lawbreakers in real time for subsequent processing,this paper proposes a Gamma approximation-based detection method for multi-antenna covert communication systems.Specifically,the Gamma approximation property is used to calculate the miss detection rate and false alarm rate of the monitor firstly.Then the optimization problem to minimize the sum of the missed detection rate and the false alarm rate is proposed.The optimal detection threshold and the minimum error detection probability are solved according to the properties of the Lambert W function.Finally,simulation results are given to demonstrate the effectiveness of the proposed method.

Age of Information for Short-Packet Covert Communication with Time Modulated Retrodirective Array

In this paper,the covert age of information(CAoI),which characterizes the timeliness and covertness performance of communication,is first investigated in the short-packet covert communication with time modulated retrodirective array(TMRDA).Specifically,the TMRDA is designed to maximize the antenna gain in the target direction while the side lobe is sufficiently suppressed.On this basis,the covertness constraint and CAoI are derived in closed form.To facilitate the covert transmission design,the transmit power and block-length are jointly optimized to minimize the CAoI,which demonstrates the trade-off between covertness and timelessness.Our results illustrate that there exists an optimal block-length that yields the minimum CAoI,and the presented optimization results can achieve enhanced performance compared with the fixed block-length case.Additionally,we observe that smaller beam pointing error at Bob leads to improvements in CAoI.

CCM-FL:Covert communication mechanisms for federated learning in crowd sensing IoT

The past decades have witnessed a wide application of federated learning in crowd sensing,to handle the numerous data collected by the sensors and provide the users with precise and customized services.Meanwhile,how to protect the private information of users in federated learning has become an important research topic.Compared with the differential privacy(DP)technique and secure multiparty computation(SMC)strategy,the covert communication mechanism in federated learning is more efficient and energy-saving in training the ma-chine learning models.In this paper,we study the covert communication problem for federated learning in crowd sensing Internet-of-Things networks.Different from the previous works about covert communication in federated learning,most of which are considered in a centralized framework and experimental-based,we firstly proposes a centralized covert communication mechanism for federated learning among n learning agents,the time complexity of which is O(log n),approximating to the optimal solution.Secondly,for the federated learning without parameter server,which is a harder case,we show that solving such a problem is NP-hard and prove the existence of a distributed covert communication mechanism with O(log logΔlog n)times,approximating to the optimal solution.Δis the maximum distance between any pair of learning agents.Theoretical analysis and nu-merical simulations are presented to show the performance of our covert communication mechanisms.We hope that our covert communication work can shed some light on how to protect the privacy of federated learning in crowd sensing from the view of communications.

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative jammer.To maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and trajectory.For practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the ground.To solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.

Jamming Assisted Covert Wireless Communication in Multi-Channel Systems

This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection transmission schemes,named random sub-channel selection(RSS)scheme and maximum sub-channel selection(MSS)scheme,to enhance communication covertness.For each proposed scheme,we first derive closed-form expressions of the transmission outage probability(TOP),the average effective rate,and the minimum average detection error probability(DEP).Then,the average effective covert rate(ECR)is maximized by jointly optimizing the transmit power at the transmitter and the number of sub-channels.Numerical results show that there is an optimal value of the number of sub-channels that maximizes the average ECR.We also find that to achieve the maximum average ECR,a larger number of subchannels are needed facing a stricter covertness constraint.

Intelligent Reflecting Surface-Aided Secure and Covert Communications

This work employs intelligent reflecting surface(IRS)to enhance secure and covert communication performance.We formulate an optimization problem to jointly design both the reflection beamformer at IRS and transmit power at transmitter Alice in order to optimize the achievable secrecy rate at Bob subject to a covertness constraint.We first develop a Dinkelbach-based algorithm to achieve an upper bound performance and a high-quality solution.For reducing the overhead and computational complexity of the Dinkelbach-based scheme,we further conceive a low-complexity algorithm in which analytical expression for the IRS reflection beamforming is derived at each iteration.Examination result shows that the devised low-complexity algorithm is able to achieve similar secrecy rate performance as the Dinkelbach-based algorithm.Our examination also shows that introducing an IRS into the considered system can significantly improve the secure and covert communication performance relative to the scheme without IRS.

Delta Compression Correction Method for Covert Communication in IoT

Covert communication can conceal the existence of wireless transmission and thus has the ability to address information security transfer issue in many applications of the booming Internet of Things(IoT).However,the proliferation of sensing devices has generated massive amounts of data,which has increased the burden of covert communication.Considering the spatiotemporal correlation of data collection causing redundancy between data,eliminating duplicate data before transmission is beneficial for shortening transmission time,reducing the average received signal power of warden,and ultimately realizing covert communication.In this paper,we propose to apply delta compression technology in the gateway to reduce the amount of data generated by IoT devices,and then sent it to the cloud server.To this end,a cost model and evaluation method that is closer to the actual storage mode of computer systems is been constructed.Based on which,the delta version sequence obtained by existing delta compression algorithms is no longer compact,manifested by the still high cost.In this situation,we designed the correction scheme based on instructions merging(CSIM)correction to save costs by merging instructions.Firstly,the delta version sequence is divided into five categories and corresponding merge rules were derived.Then,for any COPY/ADD class delta compression algorithm,merge according to strict to relaxed to selection rules while generating instructions.Finally,a more cost-effective delta version sequence can be gained.The experimental results on random data show that the delta version sequences output by the CSIM corrected 1.5-pass and greedy algorithms have better performance in cost reducing.

Joint Active and Passive Beamforming Design in Intelligent Reflecting Surface(IRS)-Assisted Covert Communications:A Multi-Agent DRL Approach

Intelligent Reflecting Surface(IRS),with the potential capability to reconstruct the electromagnetic propagation environment,evolves a new IRSassisted covert communications paradigm to eliminate the negligible detection of malicious eavesdroppers by coherently beaming the scattered signals and suppressing the signals leakage.However,when multiple IRSs are involved,accurate channel estimation is still a challenge due to the extra hardware complexity and communication overhead.Besides the crossinterference caused by massive reflecting paths,it is hard to obtain the close-formed solution for the optimization of covert communications.On this basis,the paper improves a heterogeneous multi-agent deep deterministic policy gradient(MADDPG)approach for the joint active and passive beamforming(Joint A&P BF)optimization without the channel estimation,where the base station(BS)and multiple IRSs are taken as different types of agents and learn to enhance the covert spectrum efficiency(CSE)cooperatively.Thanks to the‘centralized training and distributed execution’feature of MADDPG,each agent can execute the active or passive beamforming independently based on its partial observation without referring to others.Numeral results demonstrate that the proposed deep reinforcement learning(DRL)approach could not only obtain a preferable CSE of legitimate users and a low detection of probability(LPD)of warden,but also alleviate the communication overhead and simplify the IRSs deployment.

Deep Learning for Covert Communication

In recent years,deep learning has been gradually used in communication physical layer receivers and has achieved excellent performance.In this paper,we employ deep learning to establish covert communication systems,enabling the transmission of signals through high-power signals present in the prevailing environment while maintaining covertness,and propose a convolutional neural network(CNN)based model for covert communication receivers,namely Deep CCR.This model leverages CNN to execute the signal separation and recovery tasks commonly performed by traditional receivers.It enables the direct recovery of covert information from the received signal.The simulation results show that the proposed Deep CCR exhibits significant advantages in bit error rate(BER)compared to traditional receivers in the face of noise and multipath fading.We verify the covert performance of the covert method proposed in this paper using the maximum-minimum eigenvalue ratio-based method and the frequency domain entropy-based method.The results indicate that this method has excellent covert performance.We also evaluate the mutual influence between covert signals and opportunity signals,indicating that using opportunity signals as cover can cause certain performance losses to covert signals.When the interference-tosignal power ratio(ISR)is large,the impact of covert signals on opportunity signals is minimal.

Space/Air Covert Communications:Potentials,Scenarios,and Key Technologies

Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface(RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.

Covert Communication with a Spectrum Sharing Relay in the Finite Blocklength Regime

In this paper,we investigate the feasibility and performance of the covert communication with a spectrum sharing relay in the finite blocklength regime.Specifically,the relay opportunistically forwards the source's messages to the primary receiver or conveys the covert messages to its own receiver via the sharing spectrum,while the warden attempts to detect the transmission.First,we derive a lower bound on the covertness constraint,and the analytical expressions of both the primary average effective covert throughput(AECT)and sum AECT are presented by considering the overall decoding error performance.Then,we formulate two optimization problems to maximize the primary and sum AECT respectively by optimizing the blocklength and the transmit power at the source and the relay.Our examinations show that there exists an optimal blocklength to maximize the primary and sum AECT.Besides,it is revealed that,to maximize the primary AECT,the optimal transmit power of each hop increases as its channel quality deteriorates.Furthermore,in the optimization for maximizing the sum AECT,the optimal transmit power at the source equals to zero when the channel quality from relay to the secondary receiver is not weaker than that from relay to the primary receiver.

Covert Communication in Integrated High Altitude Platform Station Terrestrial Networks

In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.

Multi-Antenna Jammer Assisted Covert Communications in Data Collected IoT with NOMA

In this paper,we investigate covert communications in data collected IoT with NOMA,where the paired sensor nodes S_(m) and S_(n) transmit covert messages to a legitimate receiver(Bob)in the presence of a Warden(Willie).To confuse the detection at Willie,an extra multi-antenna friendly jammer(Jammer)has been employed to transmit artificial noise(AN)with random power.Based on the CSI of Willie is available or not at Jammer,three AN transmission schemes,including null-space artificial noise(NAN),transmit antenna selection(TAS),and zeroforcing beamforming(ZFB),are proposed.Furthermore,the closed-form expressions of expected minimum detection error probability(EMDEP)and joint connection outage probability(JCOP)are derived to measure covertness and reliability,respectively.Finally,the maximum effective covert rate(ECR)is obtained with a given covertness constraint.The numerical results show that ZFB scheme has the best maximum ECR in the case of the number of antennas satisfies N>2,and the same maximum ECR can be achieved in ZFB and NAN schemes with N=2.Moreover,TAS scheme also can improve the maximum ECR compared with the benchmark scheme(i.e.,signal-antenna jammer).In addition,a proper NOMA node pairing can further improve the maximum ECR.

A Derivative Matrix-Based Covert Communication Method in Blockchain

The data in the blockchain cannot be tampered with and the users are anonymous,which enables the blockchain to be a natural carrier for covert communication.However,the existing methods of covert communication in blockchain suffer from the predefined channel structure,the capacity of a single transaction is not high,and the fixed transaction behaviors will lower the concealment of the communication channel.Therefore,this paper proposes a derivation matrix-based covert communication method in blockchain.It uses dual-key to derive two types of blockchain addresses and then constructs an address matrix by dividing addresses into multiple layers to make full use of the redundancy of addresses.Subsequently,to solve the problem of the lack of concealment caused by the fixed transaction behaviors,divide the rectangular matrix into square blocks with overlapping regions and then encrypt different blocks sequentially to make the transaction behaviors of the channel addresses match better with those of the real addresses.Further,the linear congruence algorithm is used to generate random sequence,which provides a random order for blocks encryption,and thus enhances the security of the encryption algorithm.Experimental results show that this method can effectively reduce the abnormal transaction behaviors of addresses while ensuring the channel transmission efficiency.

Deep Reinforcement Learning for IRS-Assisted UAV Covert Communications

Covert communications can hide the existence of a transmission from the transmitter to receiver.This paper considers an intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)covert communication system.It was inspired by the high-dimensional data processing and decisionmaking capabilities of the deep reinforcement learning(DRL)algorithm.In order to improve the covert communication performance,an UAV 3D trajectory and IRS phase optimization algorithm based on double deep Q network(TAP-DDQN)is proposed.The simulations show that TAP-DDQN can significantly improve the covert performance of the IRS-assisted UAV covert communication system,compared with benchmark solutions.

Intelligent Covert Communication Design for Cooperative Cognitive Radio Network

Extensive research attentions have been devoted to studying cooperative cognitive radio networks(CCRNs),where secondary users(SU)providing cooperative transmissions can be permitted by primary users(PU)to use spectrum.In order to maximize SU’s utility,SU may transmit its own information during the period of cooperative transmission,which stimulates the use of covert transmission against PU’s monitoring.For this sake,this article reviews the motivations of studying covert communications in CCRN.In particular,three intelligent covert transmission approaches are developed for maximizing SU’s utility in CCRNs,namely,intelligent parasitic covert transmission(IPCT),intelligent jammer aided covert transmission(IJCT)and intelligent reflecting surface assisted covert transmission(IRSC).Further,some raw performance evaluations are discussed,and a range of potential research directions are also provided.

An Empirical Study on the Differences between Overt Translation and Covert Translation in Legal

Currently,it is key to convey precise meanings to readers for translators.Observing expressing habits between different languages is the precondition to make target texts more readable.It is crucial to ensure the exactness and seriousness of legal texts,but it does not mean that translators have to take machined way to leave out and even give up transmitting in-deep cultural implications for the intention of achieving the all-inclusive integrity of target content.It is a correct choice for translators to take overt translation and covert translation in line with traits of source language and target language and differences between civil law system and common law system.The intention of the article is to make an empirical study between overt translation and covert translation.

隐匿性肝性脑病病人延续护理需求现状及影响因素

目的:调查隐匿性肝性脑病病人延续护理需求,分析其影响因素,为其延续护理实践方案提供参考。方法:采用便利抽样的方法,选取2022年2月—9月在山西省某三级甲等综合医院消化内科住院被诊断为肝硬化的病人69例,采用自行编制的病人延续护理需求调查表进行调查。结果:隐匿性肝性脑病病人延续护理需求得分为85~182分(173.34±25.71)分,需求内容中对信息的需求度最高。家庭平均月收入、工作状况、文化程度是隐匿性肝性脑病病人延续护理需求的影响因素。结论:隐匿性肝性脑病病人延续护理需求迫切,应研究以病人需求为导向的延续护理干预策略,实施精准化护理,提高病人的健康相关生活质量。