This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easi...This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise(LDBSCAN) is proposed to discriminate the FTs from the physical targets(PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion.Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method.展开更多
A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in ...A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in range dimension,the velocity of the range gate pull-off,and the number of the decoy targets in velocity dimension and the velocity of the Doppler frequency pull-off.Also,the steps to design these parameters are brought out.The rules and design procedure discussed in this paper have important meaning for the choice of the reasonable jamming parameters in the practical applications,which can help to obtain good jamming effect.展开更多
In order to make the effective ECCM to the deceptive jamming, especially the angle deceptive jamming, this paper establishes a signal-processing model for anti-deceptive jamming firstly, in which two feature-extractin...In order to make the effective ECCM to the deceptive jamming, especially the angle deceptive jamming, this paper establishes a signal-processing model for anti-deceptive jamming firstly, in which two feature-extracting algorithms, i.e. the statistical algorithm and the neural network （NN） algorithm are presented, then uses the RBF NN as the classitier in the processing model. Finally the two algorithms are validated and compared through some simulations.展开更多
In real-time strategy(RTS)games,the ability of recognizing other players’goals is important for creating artifical intelligence(AI)players.However,most current goal recognition methods do not take the player’s decep...In real-time strategy(RTS)games,the ability of recognizing other players’goals is important for creating artifical intelligence(AI)players.However,most current goal recognition methods do not take the player’s deceptive behavior into account which often occurs in RTS game scenarios,resulting in poor recognition results.In order to solve this problem,this paper proposes goal recognition for deceptive agent,which is an extended goal recognition method applying the deductive reason method(from general to special)to model the deceptive agent’s behavioral strategy.First of all,the general deceptive behavior model is proposed to abstract features of deception,and then these features are applied to construct a behavior strategy that best matches the deceiver’s historical behavior data by the inverse reinforcement learning(IRL)method.Final,to interfere with the deceptive behavior implementation,we construct a game model to describe the confrontation scenario and the most effective interference measures.展开更多
Demand response transactions between electric consumers,load aggregators,and the distribution network manager based on the"combination of price and incentive"are feasible and efficient.However,the incentive ...Demand response transactions between electric consumers,load aggregators,and the distribution network manager based on the"combination of price and incentive"are feasible and efficient.However,the incentive payment of demand re-sponse is quantified based on private information,which gives the electric consumers and load aggregators the possibility of defrauding illegitimate interests by declaring false information.This paper proposes a method based on Vickrey-Clark-Groves(VCG)theory to prevent electric consumers and load aggregators from taking illegitimate interests through deceptive behaviors in the demand response transactions.Firstly,a demand response transaction framework with the price-and-incentive com-bined mode is established to illustrate the deceptive behaviors in the demand response transactions.Then,the idea for eradi-cating deceptive behaviors based on VCG theory is given,and a detailed VCG-based mathematical model is constructed follow-ing the demand response transaction framework.Further,the proofs of incentive compatibility,individual rationality,cost minimization,and budget balance of the proposed VCG-based method are given.Finally,a modified IEEE 33-node system and a modified IEEE 123-node system are used to illustrate and validate the proposed method.展开更多
Genetic algorithms (GA) are a new type of global optimization methodology based on na-ture selection and heredity, and its power comes from the evolution process of the population of feasi-ble solutions by using simpl...Genetic algorithms (GA) are a new type of global optimization methodology based on na-ture selection and heredity, and its power comes from the evolution process of the population of feasi-ble solutions by using simple genetic operators. The past two decades saw a lot of successful industrial cases of GA application, and also revealed the urgency of practical theoretic guidance. This paper sets focus on the evolution dynamics of GA based on schema theorem and building block hypothesis (Schema Theory), which we thought would form the basis of profound theory of GA. The deceptive-ness of GA in solving multi-modal optimization problems encoded on {0,1} was probed in detail. First, a series of new concepts are defined mathematically as the schemata containment, schemata compe-tence. Then, we defined the schema deceptiveness and GA deceptive problems based on primary schemata competence, including fully deceptive problem, consistently deceptive problem, chronically deceptive problem, and fundamentally deceptive problem. Meanwhile, some novel propositions are formed on the basis of primary schemata competence. Finally, we use the trap function, a kind of bit unitation function, and a NiH function (needle-in-a-haystack) newly designed by the authors, to dis-play the affections of schema deceptiveness on the searching behavior of GA.展开更多
We propose a method to suppress deceptive jamming by frequency diverse array （FDA） in radar electronic coun- termeasure environments. FDA offers a new range-angle-dependent beam pattern through a small frequency inc...We propose a method to suppress deceptive jamming by frequency diverse array （FDA） in radar electronic coun- termeasure environments. FDA offers a new range-angle-dependent beam pattern through a small frequency increment across elements. Due to the coupling between the angle and range, a mismatch between the test angle and physical angle occurs when the slant range on which the beam focuses is not equal to the slant range of the real target. In addition, the range of the target can be extracted by sum-difference beam except for time-delay testing, because the beam provides a range resolution in the FDA that cannot be deceived by traditional deceptive jamming. A strategy of using FDA to transmit two pulses with zero and nonzero frequency increments, respectively, is proposed to ensure that the angle of a target can be obtained by FDA. Moreover, the lo- calization performance is examined by analyzing the Cramer-Rao lower bound and detection probability. Effectiveness of the proposed method is confirmed by simulation results.展开更多
Due to the anonymous and free-for-all characteristics of online forums,it is very hard for human beings to differentiate deceptive reviews from truthful reviews.This paper proposes a deep learning approach for text re...Due to the anonymous and free-for-all characteristics of online forums,it is very hard for human beings to differentiate deceptive reviews from truthful reviews.This paper proposes a deep learning approach for text representation called DCWord (Deep Context representation by Word vectors) to deceptive review identification.The basic idea is that since deceptive reviews and truthful reviews are composed by writers without and with real experience on using the online purchased goods or services,there should be different contextual information of words between them.Unlike state-of-the-art techniques in seeking best linguistic features for representation,we use word vectors to characterize contextual information of words in deceptive and truthful reviews automatically.The average-pooling strategy (called DCWord-A) and maxpooling strategy (called DCWord-M) are used to produce review vectors from word vectors.Experimental results on the Spam dataset and the Deception dataset demonstrate that the DCWord-M representation with LR (Logistic Regression) produces the best performances and outperforms state-of-the-art techniques on deceptive review identification.Moreover,the DCWord-M strategy outperforms the DCWord-A strategy in review representation for deceptive review identification.The outcome of this study provides potential implications for online review management and business intelligence of deceptive review identification.展开更多
Over past decades,deceptive counterfeits which cannot be recognized by ordinary consumers when purchasing,such as counterfeit cosmetics,have posed serious threats on consumers’health and safety,and resulted in huge e...Over past decades,deceptive counterfeits which cannot be recognized by ordinary consumers when purchasing,such as counterfeit cosmetics,have posed serious threats on consumers’health and safety,and resulted in huge economic loss and inestimable brand damages to the genuine goods at the same time.Thus,how to effectively control and eliminate deceptive counterfeits in the market has become a critical problem to the local government.One of the principal challenges in combating the cheating action for the government is how to enhance the enforcement of relative quality inspection agencies like industrial administration office(IAO).In this paper,we formulate a two-stage counterfeit product model with a fixed checking rate from IAO and a penalty for holding counterfeits.Tominimize the total expected cost over two stages,the retailer adopts optimal ordering policies which are correlated with the checking rate and penalty.Under certain circumstances,we find that the optimal expected cost function for the retailer is first-order continuous and convex.The optimal ordering policy in stage two depends closely on the inventory level after the first sales period.When the checking rate in stage one falls into a certain range,the optimal ordering policy for the retailer at each stage is to order both kinds of products.Knowing the retailer’s optimal ordering policy at each stage,IAO can modify the checking rate accordingly to keep the ratio of deceptive counterfeits on the market under a certain level.展开更多
Background:Ischemic preconditioning(IPC)is purported to have beneficial effects on athletic performance,although findings are inconsistent,with some studies reporting placebo effects.The majority of studies have inves...Background:Ischemic preconditioning(IPC)is purported to have beneficial effects on athletic performance,although findings are inconsistent,with some studies reporting placebo effects.The majority of studies have investigated IPC alongside a placebo condition,but without a control condition that was devoid of experimental manipulation,thereby limiting accurate determination of the IPC effects.Therefore,the aims of this study were to assess the impact of the IPC intervention,compared to both placebo and no intervention,on exercise capacity and athletic performance.Methods:A systematic search of PubMed,Embase,SPORTDiscus,Cochrane Library,and Latin American and Caribbean Health Sciences Literature(LILACS)covering records from their inception until July 2023 was conducted.To qualify for inclusion,studies had to apply IPC as an acute intervention,comparing it with placebo and/or control conditions.Outcomes of interest were performance(force,number of repetitions,power,time to exhaustion,and time trial performance),physiological measurements(maximum oxygen consumption,and heart rate),or perceptual measurements(RPE).For each outcome measure,we conducted 3 independent meta-analyses(IPC vs.placebo,IPC vs.control,placebo vs.control)using an inverse-variance random-effects model.The between-treatment effects were quantified by the standardized mean difference(SMD),accompanied by their respective 95%confidence intervals.Additionally,we employed the Grading of Recommendations,Assessment,Development and Evaluation(GRADE)approach to assess the level of certainty in the evidence.Results:Seventy-nine studies were included in the quantitative analysis.Overall,IPC demonstrates a comparable effect to the placebo condition(using a low-pressure tourniquet),irrespective of the subjects'training level(all outcomes presenting p>0.05),except for the outcome of time to exhaustion,which exhibits a small magnitude effect(SMD=0.37;p=0.002).Additionally,the placebo exhibited effects notably greater than the control condition(outcome:number of repetitions;SMD=0.45;p=0.03),suggesting a potential influence of participants'cognitive perception on the outcomes.However,the evidence is of moderate to low certainty,regardless of the comparison or outcome.Conclusion:IPC has significant effects compared to the control intervention,but it did not surpass the placebo condition.Its administration might be influenced by the cognitive perception of the receiving subject,and the efficacy of IPC as an ergogenic strategy for enhancing exercise capacity and athletic performance remains questionable.展开更多
This paper explores security risks in state estimation based on multi-sensor systems that implement a Kalman filter and aχ^(2) detector.When measurements are transmitted via wireless networks to a remote estimator,th...This paper explores security risks in state estimation based on multi-sensor systems that implement a Kalman filter and aχ^(2) detector.When measurements are transmitted via wireless networks to a remote estimator,the innovation sequence becomes susceptible to interception and manipulation by adversaries.We consider a class of linear deception attacks,wherein the attacker alters the innovation to degrade estimation accuracy while maintaining stealth against the detector.Given the inherent volatility of the detection function based on theχ^(2) detector,we propose broadening the traditional feasibility constraint to accommodate a certain degree of deviation from the distribution of the innovation.This broadening enables the design of stealthy attacks that exploit the tolerance inherent in the detection mechanism.The state estimation error is quantified and analyzed by deriving the iteration of the error covariance matrix of the remote estimator under these conditions.The selected degree of deviation is combined with the error covariance to establish the objective function and the attack scheme is acquired by solving an optimization problem.Furthermore,we propose a novel detection algorithm that employs a majority-voting mechanism to determine whether the system is under attack,with decision parameters dynamically adjusted in response to system behavior.This approach enhances sensitivity to stealthy and persistent attacks without increasing the false alarm rate.Simulation results show that the designed leads to about a 41%rise in the trace of error covariance for stable systems and 29%for unstable systems,significantly impairing estimation performance.Concurrently,the proposed detection algorithm enhances the attack detection rate by 33%compared to conventional methods.展开更多
Mimetic seeds attract birds to disperse seeds mainly by mimicking fleshy fruits or arillate seeds,however,they provide little nutritive reward for bird dispersers.The key characteristics of mimetic seeds are conspicuo...Mimetic seeds attract birds to disperse seeds mainly by mimicking fleshy fruits or arillate seeds,however,they provide little nutritive reward for bird dispersers.The key characteristics of mimetic seeds are conspicuous seed color,hard seed coat,certain toxic secondary metabolites,and perhaps smooth waxy layer.In this review,we discuss the global distribution of mimetic seeds,the interaction of mimetic seeds with bird dispersers,and secondary metabolites that underlie key characteristics of mimetic seeds.Mimetic-seed species mainly occur in the tropics,with large numbers distributed along coastal areas.The interaction between mimetic-seed species and bird dispersers can be antagonistic,mutualistic,or both.These interactions are generally established by conspicuous visual cues and hard tactile cues from mimetic seeds.The formation and variation of key characteristics of mimetic seeds may contribute to the metabolism of several kind of secondary compounds.Here,we also discuss mimetic-seed dispersal in the context of an evolutionary game,and propose several aspects of mimetic-seed dispersal that remain unstudied.While this review is based on preliminary findings and does not account for other potential influencing factors such as climate,it is expected to contribute to an improved understanding of mimetic-seed dispersal.展开更多
This paper focuses on the design of event-triggered controllers for the synchronization of delayed Takagi-Sugeno(T-S)fuzzy neural networks(NNs)under deception attacks.The traditional event-triggered mechanism(ETM)dete...This paper focuses on the design of event-triggered controllers for the synchronization of delayed Takagi-Sugeno(T-S)fuzzy neural networks(NNs)under deception attacks.The traditional event-triggered mechanism(ETM)determines the next trigger based on the current sample,resulting in network congestion.Furthermore,such methods suffer from the issues of deception attacks and unmeasurable system states.To enhance the system stability,we adaptively detect the occurrence of events over a period of time.In addition,deception attacks are recharacterized to describe general scenarios.Specifically,the following enhancements are implemented:First,we use a Bernoulli process to model the occurrence of deception attacks,which can describe a variety of attack scenarios as a type of general Markov process.Second,we introduce a sum-based dynamic discrete event-triggered mechanism(SDDETM),which uses a combination of past sampled measurements and internal dynamic variables to determine subsequent triggering events.Finally,we incorporate a dynamic output feedback controller(DOFC)to ensure the system stability.The concurrent design of the DOFC and SDDETM parameters is achieved through the application of the cone complement linearization(CCL)algorithm.We further perform two simulation examples to validate the effectiveness of the algorithm.展开更多
This paper proposes a model-based control framework for vehicle platooning systems with secondorder nonlinear dynamics operating over switching signed networks,time-varying delays,and deception attacks.The study inclu...This paper proposes a model-based control framework for vehicle platooning systems with secondorder nonlinear dynamics operating over switching signed networks,time-varying delays,and deception attacks.The study includes two configurations:a leaderless structure using Finite-Time Non-Singular Terminal Bipartite Consensus(FNTBC)and Fixed-Time Bipartite Consensus(FXTBC),and a leader—follower structure ensuring structural balance and robustness against deceptive signals.In the leaderless model,a bipartite controller based on impulsive control theory,gauge transformation,and Markovian switching Lyapunov functions ensures mean-square stability and coordination under deception attacks and communication delays.The FNTBC achieves finite-time convergence depending on initial conditions,while the FXTBC guarantees fixed-time convergence independent of them,providing adaptability to different operating states.In the leader—follower case,a discontinuous impulsive control law synchronizes all followers with the leader despite deceptive attacks and switching topologies,maintaining robust coordination through nonlinear corrective mechanisms.To validate the approach,simulations are conducted on systems of five and seventeen vehicles in both leaderless and leader—follower configurations.The results demonstrate that the proposed framework achieves rapid consensus,strong robustness,and high resistance to deception attacks,offering a secure and scalable model-based control solution for modern vehicular communication networks.展开更多
The State Administration for Industry and Commerce recently said it has suggested the addition of an article in the Advertising Law to make celebrities who represent fake products in deceptive advertising criminally r...The State Administration for Industry and Commerce recently said it has suggested the addition of an article in the Advertising Law to make celebrities who represent fake products in deceptive advertising criminally responsible for their actions if it is展开更多
Deceptive interrogation,undercover investigation,special information,and covert spying may be used as deceptive evidentiary acts.By Article 52 of the Criminal Procedure Law,these methods must undergo the examination o...Deceptive interrogation,undercover investigation,special information,and covert spying may be used as deceptive evidentiary acts.By Article 52 of the Criminal Procedure Law,these methods must undergo the examination of the admissibility of evidence in the trial stage.How interpretate obtaining evidence by deception such judicial postmortem review should include the necessity of investigation and the legality of investigation.The sources of information examined should not only be limited to the defendanfs confession and prosecution files but also include the evidence of personal testimony,intelligence sources,and material evidence sources,especially the appropriate presentation of investigation files.In a case,the necessity,possibility,and possibility of distortion of the means of obtaining evidence determine whether the specific evidence has the legality of evidence.Documents must be able to truthfully reflect the implementation process of specific evidence in the case.展开更多
Industrial robots are becoming increasingly vulnerable to cyber incidents and attacks,particularly with the dawn of the Industrial Internet-of-Things(IIoT).To gain a comprehensive understanding of these cyber risks,vu...Industrial robots are becoming increasingly vulnerable to cyber incidents and attacks,particularly with the dawn of the Industrial Internet-of-Things(IIoT).To gain a comprehensive understanding of these cyber risks,vulnerabilities of industrial robots were analyzed empirically,using more than three million communication packets collected with testbeds of two ABB IRB120 robots and five other robots from various original equipment manufacturers(OEMs).This analysis,guided by the confidentiality-integrity-availability(CIA)triad,uncovers robot vulnerabilities in three dimensions:confidentiality,integrity,and availability.These vulnerabilities were used to design Covering Robot Manipulation via Data Deception(CORMAND2),an automated cyber-physical attack against industrial robots.CORMAND2 manipulates robot operation while deceiving the Supervisory Control and Data Acquisition(SCADA)system that the robot is operating normally by modifying the robot’s movement data and data deception.CORMAND2 and its capability of degrading the manufacturing was validated experimentally using the aforementioned seven robots from six different OEMs.CORMAND2 unveils the limitations of existing anomaly detection systems,more specifically the assumption of the authenticity of SCADA-received movement data,to which we propose mitigations for.展开更多
The static and predictable characteristics of cyber systems give attackers an asymmetric advantage in gathering useful information and launching attacks.To reverse this asymmetric advantage,a new defense idea,called M...The static and predictable characteristics of cyber systems give attackers an asymmetric advantage in gathering useful information and launching attacks.To reverse this asymmetric advantage,a new defense idea,called Moving Target Defense(MTD),has been proposed to provide additional selectable measures to complement traditional defense.However,MTD is unable to defeat the sophisticated attacker with fingerprint tracking ability.To overcome this limitation,we go one step beyond and show that the combination of MTD and Deception-based Cyber Defense(DCD)can achieve higher performance than either of them.In particular,we first introduce and formalize a novel attacker model named Scan and Foothold Attack(SFA)based on cyber kill chain.Afterwards,we develop probabilistic models for SFA defenses to provide a deeper analysis of the theoretical effect under different defense strategies.These models quantify attack success probability and the probability that the attacker will be deceived under various conditions,such as the size of address space,and the number of hosts,attack analysis time.Finally,the experimental results show that the actual defense effect of each strategy almost perfectly follows its probabilistic model.Also,the defense strategy of combining address mutation and fingerprint camouflage can achieve a better defense effect than the single address mutation.展开更多
This paper is aimed at the distributed fault estimation issue associated with the potential loss of actuator efficiency for a type of discrete-time nonlinear systems with sensor saturation.For the distributed estimati...This paper is aimed at the distributed fault estimation issue associated with the potential loss of actuator efficiency for a type of discrete-time nonlinear systems with sensor saturation.For the distributed estimation structure under consideration,an estimation center is not necessary,and the estimator derives its information from itself and neighboring nodes,which fuses the state vector and the measurement vector.In an effort to cut down data conflicts in communication networks,the stochastic communication protocol(SCP)is employed so that the output signals from sensors can be selected.Additionally,a recursive security estimator scheme is created since attackers randomly inject malicious signals into the selected data.On this basis,sufficient conditions for a fault estimator with less conservatism are presented which ensure an upper bound of the estimation error covariance and the mean-square exponential boundedness of the estimating error.Finally,a numerical example is used to show the reliability and effectiveness of the considered distributed estimation algorithm.展开更多
Deception detection is regarded as a concern for everyone in their daily lives and affects social interactions.The human face is a rich source of data that offers trustworthy markers of deception.The deception or lie ...Deception detection is regarded as a concern for everyone in their daily lives and affects social interactions.The human face is a rich source of data that offers trustworthy markers of deception.The deception or lie detection systems are non-intrusive,cost-effective,and mobile by identifying facial expressions.Over the last decade,numerous studies have been conducted on deception detection using several advanced techniques.Researchers have focused their attention on inventing more effective and efficient solutions for the detection of deception.So,it could be challenging to spot trends,practical approaches,gaps,and chances for contribution.However,there are still a lot of opportunities for innovative deception detection methods.Therefore,we used a variety of machine learning(ML)and deep learning(DL)approaches to experiment with this work.This research aims to do the following:(i)review and analyze the current lie detection(LD)systems;(ii)create a dataset;(iii)use several ML and DL techniques to identify lying;and(iv)create a hybrid model known as LDNet.By combining layers from Vgg16 and DeneseNet121,LDNet was developed and offered the best accuracy(99.50%)of all the models.Our developed hybrid model is a great addition that significantly advances the study of LD.The findings from this research endeavor are expected to advance our understanding of the effectiveness of ML and DL techniques in LD.Furthermore,it has significant practical applications in diverse domains such as security,law enforcement,border control,organizations,and investigation cases where accurate lie detection is paramount.展开更多
文摘This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise(LDBSCAN) is proposed to discriminate the FTs from the physical targets(PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion.Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method.
基金Sponsored by National Basic Research Program of China (6139001012)
文摘A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in range dimension,the velocity of the range gate pull-off,and the number of the decoy targets in velocity dimension and the velocity of the Doppler frequency pull-off.Also,the steps to design these parameters are brought out.The rules and design procedure discussed in this paper have important meaning for the choice of the reasonable jamming parameters in the practical applications,which can help to obtain good jamming effect.
文摘In order to make the effective ECCM to the deceptive jamming, especially the angle deceptive jamming, this paper establishes a signal-processing model for anti-deceptive jamming firstly, in which two feature-extracting algorithms, i.e. the statistical algorithm and the neural network （NN） algorithm are presented, then uses the RBF NN as the classitier in the processing model. Finally the two algorithms are validated and compared through some simulations.
文摘In real-time strategy(RTS)games,the ability of recognizing other players’goals is important for creating artifical intelligence(AI)players.However,most current goal recognition methods do not take the player’s deceptive behavior into account which often occurs in RTS game scenarios,resulting in poor recognition results.In order to solve this problem,this paper proposes goal recognition for deceptive agent,which is an extended goal recognition method applying the deductive reason method(from general to special)to model the deceptive agent’s behavioral strategy.First of all,the general deceptive behavior model is proposed to abstract features of deception,and then these features are applied to construct a behavior strategy that best matches the deceiver’s historical behavior data by the inverse reinforcement learning(IRL)method.Final,to interfere with the deceptive behavior implementation,we construct a game model to describe the confrontation scenario and the most effective interference measures.
基金supported by the Fundamental Research Funds for the Central Universities(No.B230201048).
文摘Demand response transactions between electric consumers,load aggregators,and the distribution network manager based on the"combination of price and incentive"are feasible and efficient.However,the incentive payment of demand re-sponse is quantified based on private information,which gives the electric consumers and load aggregators the possibility of defrauding illegitimate interests by declaring false information.This paper proposes a method based on Vickrey-Clark-Groves(VCG)theory to prevent electric consumers and load aggregators from taking illegitimate interests through deceptive behaviors in the demand response transactions.Firstly,a demand response transaction framework with the price-and-incentive com-bined mode is established to illustrate the deceptive behaviors in the demand response transactions.Then,the idea for eradi-cating deceptive behaviors based on VCG theory is given,and a detailed VCG-based mathematical model is constructed follow-ing the demand response transaction framework.Further,the proofs of incentive compatibility,individual rationality,cost minimization,and budget balance of the proposed VCG-based method are given.Finally,a modified IEEE 33-node system and a modified IEEE 123-node system are used to illustrate and validate the proposed method.
基金This work was supported by the National Natural Science Foundation of China (Grant No. 69974026).
文摘Genetic algorithms (GA) are a new type of global optimization methodology based on na-ture selection and heredity, and its power comes from the evolution process of the population of feasi-ble solutions by using simple genetic operators. The past two decades saw a lot of successful industrial cases of GA application, and also revealed the urgency of practical theoretic guidance. This paper sets focus on the evolution dynamics of GA based on schema theorem and building block hypothesis (Schema Theory), which we thought would form the basis of profound theory of GA. The deceptive-ness of GA in solving multi-modal optimization problems encoded on {0,1} was probed in detail. First, a series of new concepts are defined mathematically as the schemata containment, schemata compe-tence. Then, we defined the schema deceptiveness and GA deceptive problems based on primary schemata competence, including fully deceptive problem, consistently deceptive problem, chronically deceptive problem, and fundamentally deceptive problem. Meanwhile, some novel propositions are formed on the basis of primary schemata competence. Finally, we use the trap function, a kind of bit unitation function, and a NiH function (needle-in-a-haystack) newly designed by the authors, to dis-play the affections of schema deceptiveness on the searching behavior of GA.
文摘We propose a method to suppress deceptive jamming by frequency diverse array （FDA） in radar electronic coun- termeasure environments. FDA offers a new range-angle-dependent beam pattern through a small frequency increment across elements. Due to the coupling between the angle and range, a mismatch between the test angle and physical angle occurs when the slant range on which the beam focuses is not equal to the slant range of the real target. In addition, the range of the target can be extracted by sum-difference beam except for time-delay testing, because the beam provides a range resolution in the FDA that cannot be deceived by traditional deceptive jamming. A strategy of using FDA to transmit two pulses with zero and nonzero frequency increments, respectively, is proposed to ensure that the angle of a target can be obtained by FDA. Moreover, the lo- calization performance is examined by analyzing the Cramer-Rao lower bound and detection probability. Effectiveness of the proposed method is confirmed by simulation results.
基金supported in part by National Natural Science Foundation of China under Grant Nos.71932002,61379046,91318302 and 61432001the Innovation Fund Project of Xi'an Science and Technology Program(Special Series for Xi'an University under Grant No.2016CXWL21).
文摘Due to the anonymous and free-for-all characteristics of online forums,it is very hard for human beings to differentiate deceptive reviews from truthful reviews.This paper proposes a deep learning approach for text representation called DCWord (Deep Context representation by Word vectors) to deceptive review identification.The basic idea is that since deceptive reviews and truthful reviews are composed by writers without and with real experience on using the online purchased goods or services,there should be different contextual information of words between them.Unlike state-of-the-art techniques in seeking best linguistic features for representation,we use word vectors to characterize contextual information of words in deceptive and truthful reviews automatically.The average-pooling strategy (called DCWord-A) and maxpooling strategy (called DCWord-M) are used to produce review vectors from word vectors.Experimental results on the Spam dataset and the Deception dataset demonstrate that the DCWord-M representation with LR (Logistic Regression) produces the best performances and outperforms state-of-the-art techniques on deceptive review identification.Moreover,the DCWord-M strategy outperforms the DCWord-A strategy in review representation for deceptive review identification.The outcome of this study provides potential implications for online review management and business intelligence of deceptive review identification.
基金the National Natural Science Foundation of China(Nos.71390334 and 11271356).
文摘Over past decades,deceptive counterfeits which cannot be recognized by ordinary consumers when purchasing,such as counterfeit cosmetics,have posed serious threats on consumers’health and safety,and resulted in huge economic loss and inestimable brand damages to the genuine goods at the same time.Thus,how to effectively control and eliminate deceptive counterfeits in the market has become a critical problem to the local government.One of the principal challenges in combating the cheating action for the government is how to enhance the enforcement of relative quality inspection agencies like industrial administration office(IAO).In this paper,we formulate a two-stage counterfeit product model with a fixed checking rate from IAO and a penalty for holding counterfeits.Tominimize the total expected cost over two stages,the retailer adopts optimal ordering policies which are correlated with the checking rate and penalty.Under certain circumstances,we find that the optimal expected cost function for the retailer is first-order continuous and convex.The optimal ordering policy in stage two depends closely on the inventory level after the first sales period.When the checking rate in stage one falls into a certain range,the optimal ordering policy for the retailer at each stage is to order both kinds of products.Knowing the retailer’s optimal ordering policy at each stage,IAO can modify the checking rate accordingly to keep the ratio of deceptive counterfeits on the market under a certain level.
基金partially supported by the State Funding Agency of Minas Gerais,Brazil(FAPEMIG),Process No.APQ-01811-21supported by Alexander von Humboldt-Stiftung(AvH)/Coordena??o de Aperfei?oamento de Pessoal de Nível Superior(CAPES)+1 种基金National Council for Scientific and Technological Development-CNPq(Process No.308138/2022-8)supported by National Council for Scientific and Technological Development-CNPq(Process No.BPD-00905-22).
文摘Background:Ischemic preconditioning(IPC)is purported to have beneficial effects on athletic performance,although findings are inconsistent,with some studies reporting placebo effects.The majority of studies have investigated IPC alongside a placebo condition,but without a control condition that was devoid of experimental manipulation,thereby limiting accurate determination of the IPC effects.Therefore,the aims of this study were to assess the impact of the IPC intervention,compared to both placebo and no intervention,on exercise capacity and athletic performance.Methods:A systematic search of PubMed,Embase,SPORTDiscus,Cochrane Library,and Latin American and Caribbean Health Sciences Literature(LILACS)covering records from their inception until July 2023 was conducted.To qualify for inclusion,studies had to apply IPC as an acute intervention,comparing it with placebo and/or control conditions.Outcomes of interest were performance(force,number of repetitions,power,time to exhaustion,and time trial performance),physiological measurements(maximum oxygen consumption,and heart rate),or perceptual measurements(RPE).For each outcome measure,we conducted 3 independent meta-analyses(IPC vs.placebo,IPC vs.control,placebo vs.control)using an inverse-variance random-effects model.The between-treatment effects were quantified by the standardized mean difference(SMD),accompanied by their respective 95%confidence intervals.Additionally,we employed the Grading of Recommendations,Assessment,Development and Evaluation(GRADE)approach to assess the level of certainty in the evidence.Results:Seventy-nine studies were included in the quantitative analysis.Overall,IPC demonstrates a comparable effect to the placebo condition(using a low-pressure tourniquet),irrespective of the subjects'training level(all outcomes presenting p>0.05),except for the outcome of time to exhaustion,which exhibits a small magnitude effect(SMD=0.37;p=0.002).Additionally,the placebo exhibited effects notably greater than the control condition(outcome:number of repetitions;SMD=0.45;p=0.03),suggesting a potential influence of participants'cognitive perception on the outcomes.However,the evidence is of moderate to low certainty,regardless of the comparison or outcome.Conclusion:IPC has significant effects compared to the control intervention,but it did not surpass the placebo condition.Its administration might be influenced by the cognitive perception of the receiving subject,and the efficacy of IPC as an ergogenic strategy for enhancing exercise capacity and athletic performance remains questionable.
文摘This paper explores security risks in state estimation based on multi-sensor systems that implement a Kalman filter and aχ^(2) detector.When measurements are transmitted via wireless networks to a remote estimator,the innovation sequence becomes susceptible to interception and manipulation by adversaries.We consider a class of linear deception attacks,wherein the attacker alters the innovation to degrade estimation accuracy while maintaining stealth against the detector.Given the inherent volatility of the detection function based on theχ^(2) detector,we propose broadening the traditional feasibility constraint to accommodate a certain degree of deviation from the distribution of the innovation.This broadening enables the design of stealthy attacks that exploit the tolerance inherent in the detection mechanism.The state estimation error is quantified and analyzed by deriving the iteration of the error covariance matrix of the remote estimator under these conditions.The selected degree of deviation is combined with the error covariance to establish the objective function and the attack scheme is acquired by solving an optimization problem.Furthermore,we propose a novel detection algorithm that employs a majority-voting mechanism to determine whether the system is under attack,with decision parameters dynamically adjusted in response to system behavior.This approach enhances sensitivity to stealthy and persistent attacks without increasing the false alarm rate.Simulation results show that the designed leads to about a 41%rise in the trace of error covariance for stable systems and 29%for unstable systems,significantly impairing estimation performance.Concurrently,the proposed detection algorithm enhances the attack detection rate by 33%compared to conventional methods.
基金supported by the Yunnan Ten Thousand Talents Plan Young&Elite Talents Project(YNWR-QNBJ-2018-017)the National Natural Science Foundation of China(32371564)+2 种基金the Key Project of Basic Research of Yunnan Province,China(202101AS070035202301AS070001)to G.ChenYunnan Provincial Science and Technology Talent and Platform Plan(202305AM070005).
文摘Mimetic seeds attract birds to disperse seeds mainly by mimicking fleshy fruits or arillate seeds,however,they provide little nutritive reward for bird dispersers.The key characteristics of mimetic seeds are conspicuous seed color,hard seed coat,certain toxic secondary metabolites,and perhaps smooth waxy layer.In this review,we discuss the global distribution of mimetic seeds,the interaction of mimetic seeds with bird dispersers,and secondary metabolites that underlie key characteristics of mimetic seeds.Mimetic-seed species mainly occur in the tropics,with large numbers distributed along coastal areas.The interaction between mimetic-seed species and bird dispersers can be antagonistic,mutualistic,or both.These interactions are generally established by conspicuous visual cues and hard tactile cues from mimetic seeds.The formation and variation of key characteristics of mimetic seeds may contribute to the metabolism of several kind of secondary compounds.Here,we also discuss mimetic-seed dispersal in the context of an evolutionary game,and propose several aspects of mimetic-seed dispersal that remain unstudied.While this review is based on preliminary findings and does not account for other potential influencing factors such as climate,it is expected to contribute to an improved understanding of mimetic-seed dispersal.
基金Project supported by the National Natural Science Foundation of China(Nos.T2121002,62473321,62403014,and 62233001)。
文摘This paper focuses on the design of event-triggered controllers for the synchronization of delayed Takagi-Sugeno(T-S)fuzzy neural networks(NNs)under deception attacks.The traditional event-triggered mechanism(ETM)determines the next trigger based on the current sample,resulting in network congestion.Furthermore,such methods suffer from the issues of deception attacks and unmeasurable system states.To enhance the system stability,we adaptively detect the occurrence of events over a period of time.In addition,deception attacks are recharacterized to describe general scenarios.Specifically,the following enhancements are implemented:First,we use a Bernoulli process to model the occurrence of deception attacks,which can describe a variety of attack scenarios as a type of general Markov process.Second,we introduce a sum-based dynamic discrete event-triggered mechanism(SDDETM),which uses a combination of past sampled measurements and internal dynamic variables to determine subsequent triggering events.Finally,we incorporate a dynamic output feedback controller(DOFC)to ensure the system stability.The concurrent design of the DOFC and SDDETM parameters is achieved through the application of the cone complement linearization(CCL)algorithm.We further perform two simulation examples to validate the effectiveness of the algorithm.
基金Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP.2/103/46”Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia for funding this research work through project number“NBU-FFR-2025-871-15”funding from Prince Sattam bin Abdulaziz University project number(PSAU/2025/R/1447).
文摘This paper proposes a model-based control framework for vehicle platooning systems with secondorder nonlinear dynamics operating over switching signed networks,time-varying delays,and deception attacks.The study includes two configurations:a leaderless structure using Finite-Time Non-Singular Terminal Bipartite Consensus(FNTBC)and Fixed-Time Bipartite Consensus(FXTBC),and a leader—follower structure ensuring structural balance and robustness against deceptive signals.In the leaderless model,a bipartite controller based on impulsive control theory,gauge transformation,and Markovian switching Lyapunov functions ensures mean-square stability and coordination under deception attacks and communication delays.The FNTBC achieves finite-time convergence depending on initial conditions,while the FXTBC guarantees fixed-time convergence independent of them,providing adaptability to different operating states.In the leader—follower case,a discontinuous impulsive control law synchronizes all followers with the leader despite deceptive attacks and switching topologies,maintaining robust coordination through nonlinear corrective mechanisms.To validate the approach,simulations are conducted on systems of five and seventeen vehicles in both leaderless and leader—follower configurations.The results demonstrate that the proposed framework achieves rapid consensus,strong robustness,and high resistance to deception attacks,offering a secure and scalable model-based control solution for modern vehicular communication networks.
文摘The State Administration for Industry and Commerce recently said it has suggested the addition of an article in the Advertising Law to make celebrities who represent fake products in deceptive advertising criminally responsible for their actions if it is
文摘Deceptive interrogation,undercover investigation,special information,and covert spying may be used as deceptive evidentiary acts.By Article 52 of the Criminal Procedure Law,these methods must undergo the examination of the admissibility of evidence in the trial stage.How interpretate obtaining evidence by deception such judicial postmortem review should include the necessity of investigation and the legality of investigation.The sources of information examined should not only be limited to the defendanfs confession and prosecution files but also include the evidence of personal testimony,intelligence sources,and material evidence sources,especially the appropriate presentation of investigation files.In a case,the necessity,possibility,and possibility of distortion of the means of obtaining evidence determine whether the specific evidence has the legality of evidence.Documents must be able to truthfully reflect the implementation process of specific evidence in the case.
基金Science and Technology Innovation 2030 Program(2018AAA0101605).
文摘Industrial robots are becoming increasingly vulnerable to cyber incidents and attacks,particularly with the dawn of the Industrial Internet-of-Things(IIoT).To gain a comprehensive understanding of these cyber risks,vulnerabilities of industrial robots were analyzed empirically,using more than three million communication packets collected with testbeds of two ABB IRB120 robots and five other robots from various original equipment manufacturers(OEMs).This analysis,guided by the confidentiality-integrity-availability(CIA)triad,uncovers robot vulnerabilities in three dimensions:confidentiality,integrity,and availability.These vulnerabilities were used to design Covering Robot Manipulation via Data Deception(CORMAND2),an automated cyber-physical attack against industrial robots.CORMAND2 manipulates robot operation while deceiving the Supervisory Control and Data Acquisition(SCADA)system that the robot is operating normally by modifying the robot’s movement data and data deception.CORMAND2 and its capability of degrading the manufacturing was validated experimentally using the aforementioned seven robots from six different OEMs.CORMAND2 unveils the limitations of existing anomaly detection systems,more specifically the assumption of the authenticity of SCADA-received movement data,to which we propose mitigations for.
基金supported by the National Key Research and Development Program of China(No.2016YFB0800601)the Key Program of NSFC-Tongyong Union Foundation(No.U1636209)+1 种基金the National Natural Science Foundation of China(61602358)the Key Research and Development Programs of Shaanxi(No.2019ZDLGY13-04,No.2019ZDLGY13-07)。
文摘The static and predictable characteristics of cyber systems give attackers an asymmetric advantage in gathering useful information and launching attacks.To reverse this asymmetric advantage,a new defense idea,called Moving Target Defense(MTD),has been proposed to provide additional selectable measures to complement traditional defense.However,MTD is unable to defeat the sophisticated attacker with fingerprint tracking ability.To overcome this limitation,we go one step beyond and show that the combination of MTD and Deception-based Cyber Defense(DCD)can achieve higher performance than either of them.In particular,we first introduce and formalize a novel attacker model named Scan and Foothold Attack(SFA)based on cyber kill chain.Afterwards,we develop probabilistic models for SFA defenses to provide a deeper analysis of the theoretical effect under different defense strategies.These models quantify attack success probability and the probability that the attacker will be deceived under various conditions,such as the size of address space,and the number of hosts,attack analysis time.Finally,the experimental results show that the actual defense effect of each strategy almost perfectly follows its probabilistic model.Also,the defense strategy of combining address mutation and fingerprint camouflage can achieve a better defense effect than the single address mutation.
基金supported in part by the National Natural Science Foundation of China(62073189,62173207)the Taishan Scholar Project of Shandong Province(tsqn202211129)。
文摘This paper is aimed at the distributed fault estimation issue associated with the potential loss of actuator efficiency for a type of discrete-time nonlinear systems with sensor saturation.For the distributed estimation structure under consideration,an estimation center is not necessary,and the estimator derives its information from itself and neighboring nodes,which fuses the state vector and the measurement vector.In an effort to cut down data conflicts in communication networks,the stochastic communication protocol(SCP)is employed so that the output signals from sensors can be selected.Additionally,a recursive security estimator scheme is created since attackers randomly inject malicious signals into the selected data.On this basis,sufficient conditions for a fault estimator with less conservatism are presented which ensure an upper bound of the estimation error covariance and the mean-square exponential boundedness of the estimating error.Finally,a numerical example is used to show the reliability and effectiveness of the considered distributed estimation algorithm.
基金funded by the Ministry of Higher Education(MOHE),Malaysia under the Fundamental Research Grant Project(FRGS/1/2021/SS0/TAYLOR/02/6)。
文摘Deception detection is regarded as a concern for everyone in their daily lives and affects social interactions.The human face is a rich source of data that offers trustworthy markers of deception.The deception or lie detection systems are non-intrusive,cost-effective,and mobile by identifying facial expressions.Over the last decade,numerous studies have been conducted on deception detection using several advanced techniques.Researchers have focused their attention on inventing more effective and efficient solutions for the detection of deception.So,it could be challenging to spot trends,practical approaches,gaps,and chances for contribution.However,there are still a lot of opportunities for innovative deception detection methods.Therefore,we used a variety of machine learning(ML)and deep learning(DL)approaches to experiment with this work.This research aims to do the following:(i)review and analyze the current lie detection(LD)systems;(ii)create a dataset;(iii)use several ML and DL techniques to identify lying;and(iv)create a hybrid model known as LDNet.By combining layers from Vgg16 and DeneseNet121,LDNet was developed and offered the best accuracy(99.50%)of all the models.Our developed hybrid model is a great addition that significantly advances the study of LD.The findings from this research endeavor are expected to advance our understanding of the effectiveness of ML and DL techniques in LD.Furthermore,it has significant practical applications in diverse domains such as security,law enforcement,border control,organizations,and investigation cases where accurate lie detection is paramount.
