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This article is dedicated to investigating the impulsive-based almost surely synchronization issue of neural network systems (NSSs) with quality-of-service constraints. First, the communication network considered suffers from random double deception attacks, which are modeled as a nonlinear function and a desynchronizing impulse sequence, respectively. Meanwhile, the impulsive instants and impulsive gains are randomly and only their expectations are available. Second, by taking two different types of random deception attacks into consideration, a novel mathematical model for vulnerable NSSs is constructed. Then, almost surely synchronization criteria are established by using Borel-Cantelli lemma. Furthermore, based on the derived strong and weak sufficient conditions, the almost surely synchronization of NSSs is achieved. Finally, the section of numerical example is shown to illustrate the effectiveness of the proposed method.

Cybercrime is a daily threat against organizations and partners of all sizes and with the rapid development of technology and the great dependence on it in some transactions, a type of serious threats has emerged that pose a high degree of risk to companies and organizations that rely on financial transactions in their work. This type of threat is called Business Email Compromise (BEC), which is a type of email phishing for financial purposes. This attack increased dramatically and caused very high financial losses to companies, especially in the period of remote work and in the Corona crisis, as it increased in the third quarter of the century of this year by 94%. This type of threat does not require a high percentage of knowledge, experience, or skills in deception and fraud, it requires only a reasonable level of social engineering. In this paper, we contribute to analyze this threat is, how it occurs, ways to avoid it or reduce its incidence, and impact on the organization.

This article considers the security-based passivity problem for a class of discrete-time Markov jump systems in the presence of deception attacks, where the deception attacks aim to change the transmitted signal. Considering the impact of deception attacks on network disruption, it causes the existence of time-varying delays in signal transmission inevitably, which makes the controlled system and the controller work asynchronously. The asynchronous control method is employed to overcome the nonsynchronous phenomenon between the system mode and controller mode. On the other hand, to reduce the frequency of data transmission, a resilient asynchronous event-triggered control scheme taking deception attacks into account is designed to save communication resources, and the proposed controller can cover some existing ones as special examples. Moreover, different triggering conditions corresponding to different jumping modes are developed to decide whether state signals should be transferred. A new stability criterion is derived to ensure the passivity of the resultant system although there exist deception attacks. Finally, a simulation example is given to verify the theoretical analysis.

In this article, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may suffer from deception attacks, which are governed by Bernoulli-distributed random variables. The purpose of the problem under consideration is to design a minimum-variance filter for CNs with deception attacks, state saturations, and UCSs such that upper bounds on the resulting error covariances are guaranteed. Then, the expected filter gains are acquired via minimizing the traces of such upper bounds, and sufficient conditions are established to ensure the exponential mean-square boundedness of the filtering errors. Finally, two simulation examples (including a practical application) are exploited to validate the effectiveness of our designed approach.

The proposed experiment will examine the effect of deceptive behavior on memory. Participants will be assigned to a “strong-incentive to cheat” or “weak-incentive to cheat” condition and play the adapted Sequential Dyadic Die-Rolling paradigm. Specifically, Player A (computer; participants think it is another participant) throws a die and reports it to Player B (participant). Then Player B throws his/her die, remembers the outcome, and reports it to Player A. Participants in the “strong-incentive to cheat” condition are monetarily punished if their die roll outcome differs from Player A's die roll outcome. Participants in the “weak-incentive to cheat” condition are not punished if the die roll outcomes differ. Two-days later, memory for the die-rolling event will be assessed. We predict that participants in the “strong-incentive to cheat” condition will have lower belief and recollection for the die-rolling event and will report more errors than participants in the “weak-incentive to cheat” condition.

Nowadays, automatic deception detection has received considerable attention in the machine learning community owing to this research interest to its vast applications in the fields of social media, interviews, law enforcement, and the military. In this study, a novel deep convolution neural network (DCNN) named LieNet is proposed to precisely detect the multi-scale variations of deception automatically. Our approach is a combination of contact and non-contact-based approaches. First, 20 frames from each video are fetched and concatenated to form a single image. Moreover, an audio signal is extracted from video and treated as image input by plotting the signal into two dimensional (2D) plane. Furthermore, 13 channels of EEG signals are plotted into 2D plane and concatenated to generate an image. Second, the LieNet model extracts features from each modality separately. Third, scores are estimated using a softmax classifier for all the modalities. Finally, three scores are combined using score level fusion to obtain a score, which gives support in favor of either deception or truth. The LieNet is validated on the “Bag-of-Lies (BoL)”“, Real-life (RL) trail”, and “Miami University Deception Detection (MU3D)" databases by considering four evaluation indexes viz., accuracy, precision, recall, and F1-score. Experimental outcomes depict that the LieNet defeats an initial work on Set-A and Set-B of the BoL database with average accuracies of 95.91% and 96.04% respectively. The accuracies obtained by the LieNet are 97% and 98% on RL trail and MU3D databases respectively.

Sellers may display unreasonably high prices (in high-cost oriented contexts) that are never accepted or would surely be discounted through bilateral bargaining. Conversely, general or vague prices with incredible appeals may be advertised (in low-cost oriented settings) as a range or for a category but not tied to specific items. Nevertheless, these seemingly irrelevant or unbinding prices can affect buyer behavior and bargaining outcome. This paper presents a new explanation for these puzzling phenomena. We propose that advertised reference prices can be a strategic tool to communicate privately known seller costs to influence optimal buyer strategy to search value information. We show that cheap-talk communication via uncommitted prices can be endogenously credible, because optimal buyer search strategy can be imperfectly aligned with seller preference. In particular, a high-cost seller may prefer the buyer to acquire information in a more cautious manner (i.e., less willing to stop at good news but more eager to quit at bad news) than a low-cost seller, which may coincide with the buyer's optimal search strategy. We demonstrate that endogenous buyer search can serve as a two-way discipline to regulate both high- and low-cost sellers' incentive for deception, which thus can sustain credible communication for high-cost and/or low-cost oriented settings.

In this paper, the robust asynchronous filtering problem is investigated for a class of discrete-time T-S fuzzy complex dynamical networks subjected to random coupling delays and deception attacks. Specifically, the deception attacks are considered in the filter, where the adversary attempts to inject some false information data in the measurement output to modify the transmitted signal in the communication networks. We introduce respectively two sets of stochastic variables satisfying the Bernoulli distribution to depict the probability of the data transmitted by the network being subjected to time-varying coupling delays and deception attacks. By using Lyapunov-Krasovskii stability theory and Abel lemma-based finite-sum inequality, a new set of sufficient conditions is established which ensures the stochastic stability of the resulting error system with a prescribed mixed Hand passivity performance index. The proposed filter parameters are obtained by solving linear matrix inequalities. Ultimately, both the effectiveness and advantages of the proposed asynchronous filter with deception attacks are verified by two numerical examples including a tunnel diode circuit model.

This article provides a discourse analysis of a large corpus of televised psychic readings. The goal of this study is to uncover the relationship between the linguistic structure of psychic readings and the psychics’ linguistic agenda. The findings of this study suggest that the psychics’ engage in linguistic tactics that allow them to negotiate and extract specific information from their subjects. The discourse structure of psychic readings facilitates deception, since the subjects, rather than the psychics, are the actual source of subject-specific information in a reading.

Pathological lying has been discussed in the research literature for more than a century, mostly in case studies. Recent research has supported pathological lying as a diagnostic entity, although it remains absent from nosological systems. The current study aimed to survey practitioners about their experiences working with clients who engage in pathological lying and to examine practitioners' abilities to diagnose pathological lying.Psychotherapists (N=295) were recruited and asked to report about their experiences with patients who engaged in pathological lying. Participants were also presented with four clinical vignettes and a definition of pathological lying and were asked to determine whether the individuals portrayed in the vignettes met that definition.Most practitioners reported clinical experience with patients exhibiting pathological lying, although such patients made up a small proportion of their caseloads. Clinicians described these patients as lying with great frequency and indicated that lying caused marked distress and impaired functioning in social, occupational, financial, and legal domains. The behavior typically had begun during adolescence and had continued for ≥5 years. Respondents reported usually offering a diagnosis other than pathological lying, such as a personality disorder. By using a published definition of pathological lying, respondents (N=156) were able to reliably identify cases of pathological lying portrayed in clinical vignettes and were able to consistently discriminate between pathological lying and both related and unrelated disorders.The participants largely endorsed the proposition of including pathological lying in nosological systems such as the

Research on commercial computer games has demonstrated that in-game behavior is related to the players’ personality profiles. However, this potential has not yet been fully utilized for personality assessments. Hence, we developed an applied (i.e., serious) assessment game to assess the Honesty–Humility personality trait. In two studies, we demonstrate that this game adequately assesses Honesty–Humility. In Study 1 ( N = 116), we demonstrate convergent validity of the assessment game with self-reported Honesty–Humility and divergent validity with the other HEXACO traits and cognitive ability. In Study 2 ( N = 287), we replicate the findings from Study 1, and also demonstrate that the assessment game shows incremental validity—beyond self-reported personality—in the prediction of cheating for financial gain, but not of counterproductive work and unethical behaviors. The findings demonstrate that assessment games are promising tools for personality measurement in applied contexts.

Concealed information detection has a strong connection with human cognition. Existing deception detection approaches such as polygraph testing usually exploit psychophysiological changes. However, they often suffer from low accuracy and attacking-by-training. Compared with conventional physiological responses, electroencephalogram (EEG) directly reflects activity responses in the brain, thus can be potentially more accurate in deception detection. In this paper, we propose an EEG-based concealed information detection framework. In this framework, different test trials are designed to evoke effective brain responses corresponding to concealed information while keeping the subject focused. Meanwhile, we employ rapid serial visual presentation (RSVP) for deception detection. Our framework presents the stimuli on the fringe of awareness, making it not easy to take the countermeasures. Furthermore, we develop a method based on neural network to detect brain responses. Experimental results with 10 subjects show that, our approach can effectively detect concealed information with an accuracy of 87.13%.

This article focuses on the distributed maximum correntropy filtering issue for general stochastic nonlinear systems subject to deception attacks. The considered nonlinear functions consist of a determined one and a stochastic one, and the stochastic signals sent by deception attacks with identified statistic characteristics could be non-Gaussian. The corresponding calculation formulas of both the filter gains and the upper bound of the filter error covariance are proposed by means of the Taylor series expansion and the fixed-point iterative update rule, where the weighted maximum correntropy criterion is utilized to take the place of traditional minimum covariance indexes. Such an upper bound is only dependent on the local information, neighbor information, and the identified statistics of deception attacks and, therefore, the developed filtering scheme realizes the requirement of distributed calculation. Furthermore, a simplified version is obtained by removing weights in the correntropy criterion. Finally, an illustrative example is given to verify the effectiveness of developed distributed maximum correntropy filtering subject to deception attacks.

Defensive deception techniques have emerged as a promising proactive defense mechanism to mislead an attacker and thereby achieve attack failure. However, most game-theoretic defensive deception approaches have assumed that players maintain consistent views under uncertainty. They do not consider players’ possible, subjective beliefs formed due to asymmetric information given to them. In this work, we formulate a hypergame between an attacker and a defender where they can interpret the same game differently and accordingly choose their best strategy based on their respective beliefs. This gives a chance for defensive deception strategies to manipulate an attacker’s belief, which is the key to the attacker’s decision-making. We consider advanced persistent threat (APT) attacks, which perform multiple attacks in the stages of the cyber kill chain (CKC) where both the attacker and the defender aim to select optimal strategies based on their beliefs. Through extensive simulation experiments, we demonstrated how effectively the defender can leverage defensive deception techniques while dealing with multi-staged APT attacks in a hypergame in which the imperfect information is reflected based on perceived uncertainty, cost, and expected utilities of both the attacker and defender, the system lifetime (i.e., mean time to security failure), and improved false-positive rates of intrusion detection.

Women remain underrepresented in technology and computing fields. Aware of this problem, many tech organizations seek diversification strategies. Several academic sources recommend including gender diverse images in recruitment materials as a low-cost way to potentially attract female workers. However, for gender nondiverse organizations, this strategy means misrepresenting the current on-the-ground diversity of their organization. Four experiments investigate how women and men perceive organizations that counterfeit diversity (i.e., exaggerate gender diversity in recruitment advertisements) relative to organizations that (a) authentically portray a high degree of gender diversity (authentic diversity; Experiments 1-3); (b) authentically portray a low degree of gender diversity (authentic nondiversity; Experiments 2 and 3); and (c) acknowledge a lack of diversity in the present, but aspire to increase diversity in the future (aspirational diversity; Experiment 3). Results reveal that women and men perceive counterfeit diversity as insincere. This perceived insincerity, in turn, decreases women's and men's interest in the organization and engenders identity threat concerns among women (Experiments 1-4). Taken together, these findings complicate scholarly discussions of diversity and inclusion strategies by highlighting the role of perceived sincerity. When recruitment strategies are deemed insincere, these strategies can backfire-decreasing interest in the organization, fomenting threat, and perpetuating underrepresentation. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Ground moving target indication (GMTI) has been extensively applied in modern warfare. In this letter, a novel deceptive jamming technique for countering multichannel synthetic aperture radar (SAR)-GMTI is presented, which is implemented with the frequency diverse array (FDA). Different from the phased array (PA), FDA modulates the transmitting signal with multiple frequencies across its array elements, which, consequently, enables range-dimension false target deception for SAR imaging. Furthermore, to achieve effective deception for the GMTI, micromotion modulation is adopted to simulate dynamic features of the moving targets. Mathematical derivation and simulation results show that the proposed technique can efficiently produce massive false targets in both the range and azimuth dimensions.

This paper addresses the event-triggered control problem of discrete-time uncertain networked control systems under random deception attacks. In order to deal with a network resource constraint, a novel two-event-generator scheme over both sensor-to-controller and controller-to-actuator channels is proposed to reduce the transmission frequency of system states and control commands, while maintaining desired system performance. More specifically, one of the event-generators is a time-varying memory-based event-triggered scheme (METS), and the other is the traditional event-triggered scheme (ETS). On the other hand, in order to incorporate network security , a new model of memory-based NCSs is established under random deception attacks. Then, sufficient conditions for preserving the asymptotic stability of uncertain NCSs are proposed by using the Lyapunov functional method. Furthermore, co-design criteria are derived for determining both the memory-based state feedback controller gains and event-triggering parameter matrices. Finally, the effectiveness of the proposed methods is verified by a quarter-car suspension system.

Hearings of witnesses and defendants play a crucial role when reaching court trial decisions. Given the high-stakes nature of trial outcomes, developing computational models that assist the decision-making process is an important research venue. In this paper, we address the identification of deception in real-life trial data. We use a dataset consisting of videos collected from public court trials. We explore the use of verbal and non-verbal modalities to build a multimodal deception detection system that aims to discriminate between truthful and deceptive statements provided by defendants and witnesses. In particular, three complementary modalities (visual, acoustic and linguistic) are evaluated for the classification of deception at the subject level. The final classifier is obtained by combining the three modalities via score-level classification, achieving 83.05% accuracy in subject-level deceit detection. To place our results in perspective, we present a human deception detection study where we evaluate the human capability of detecting deception using different modalities and compare the results to the developed system. The results show that our system outperforms the average non-expert human capability of identifying deceit.

In this article, the adaptive control for a class of strict-feedback nonlinear systems with uncertainties under injection and deception attacks is considered. An adaptive control scheme is proposed to deal with the injection and deception attacks meanwhile guarantee that regulation errors could be made arbitrarily small by adjusting control parameters. Compared with existing works whose models are linear or relatively simple, the model we consider in this article is nonlinear with parametric uncertainties. A new type of feedback control scheme is introduced to solve this problem. A simulation example is given to verify the effectiveness of our proposed control scheme.

In this paper, the issue of synchronization is investigated for coupled neural networks subject to stochastic deception attacks. Firstly, a general differential inequality with delayed impulses is given. Then, the established differential inequality is further extended to the case of delayed stochastic impulses, in which both the impulsive instants and impulsive intensity are stochastic. Secondly, by modeling the stochastic discrete-time deception attacks as stochastic impulses, synchronization criteria of the coupled neural networks under the corresponding attacks are given. Finally, two numerical examples are provided to demonstrate the correctness of the theoretical results.

This paper investigates the sliding mode control (SMC) for semi-Markov jump cyber-physical systems (S-MJCPSs) under randomly occurring deception attacks (RODA). It is assumed that the adversaries inject false data into the control signal in probability. First, a mode-dependent sliding surface is designed under the framework of integral form. Second, the criteria to ensure stochastic stability (SS) of the corresponding system are proposed, which establishes the theoretical framework of semi-Markov Lyapunov function. Third, an appropriate SMC law under attacks and uncertainties is constructed to drive the states of S-MJCPSs onto the switching manifold in finite time. Finally, the simulation study on a single-link robot arm model (SLRAM) is provided to demonstrate the obtained results.

Abstract. Deception of research participants has long been and remains a hot-button issue in the behavioral sciences. At the same time, the field of psychology is fortunate to have an ethics code to rely on in determining whether and how to use and report on deception of participants. Despite ongoing normative controversies, the smallest common denominator among psychologists is that deception ought to be a last resort – to be used only when there is no other defensible way to study a question or phenomenon. Going beyond previous normative discussions or inquiries into the mere prevalence of deception, we ask the fundamental question whether common practice is compatible with this interpretation of our field’s ethical standards. Findings from an empirical literature review – focusing on the feasibility of nondeceptive alternative procedures and the presence of explicit justifications for the use of deception – demonstrate that there is a notable gap between the last resort interpretation of our ethical standards and common practice in psychological research. The findings are discussed with the aim of identifying viable ways in which researchers, journal editors, and the scientific associations crafting our ethics codes may narrow this gap.

Entropy-based network traffic anomaly detection techniques are attractive due to their simplicity and applicability in a real-time network environment. Even though flow data provide only a basic set of information about network communications, they are suitable for efficient entropy-based anomaly detection techniques. However, a recent work reported a serious weakness of the general entropy-based anomaly detection related to its susceptibility to deception by adding spoofed data that camouflage the anomaly. Moreover, techniques for further classification of the anomalies mostly rely on machine learning, which involves additional complexity. We address these issues by providing two novel approaches. Firstly, we propose an efficient protection mechanism against entropy deception, which is based on the analysis of changes in different entropy types, namely Shannon, R?nyi, and Tsallis entropies, and monitoring the number of distinct elements in a feature distribution as a new detection metric. The proposed approach makes the entropy techniques more reliable. Secondly, we have extended the existing entropy-based anomaly detection approach with the anomaly classification method. Based on a multivariate analysis of the entropy changes of multiple features as well as aggregation by complex feature combinations, entropy-based anomaly classification rules were proposed and successfully verified through experiments. Experimental results are provided to validate the feasibility of the proposed approach for practical implementation of efficient anomaly detection and classification method in the general real-life network environment.

In this paper, the problem of fuzzy model-based leader-following consensus control for multi-agent systems (MASs) under deception attacks is investigated. For the sake of alleviating the communication burden, a novel memory-based event-triggered scheme (METS) is first proposed for the considered MASs to reduce redundant data transmission, and the leader-following consensus can be achieved faster with a smaller adjustment error by applying the historical released packets. Considering the designed METS and upper-bounded attacks synthetically, the closed-loop fuzzy system model is well established. Furthermore, with the help of Lyapunov-Krasovskii technique, some sufficient conditions are derived to ensure the consensus of MASs subject to deception attacks. Finally, a simulation example is introduced to manifest the effectiveness of the proposed method.

Only few studies have addressed how soccer goalkeepers adapt to both the spatial and temporal constraints while trying to stop a penalty kick. Moreover, research on penalty kicks has only involved male goalkeepers, even though the resultant constraint (i.e., the relation between the maximum action capabilities defining the time required and ball flight time and direction defining the time available) may or may not differ for female goalkeepers. We therefore compared penalty goalkeeping between male and female goalkeepers of similar skill level. The results showed that the resultant constraint was more stringent for female than male goalkeepers. In accordance with the affordance-based control theory, female and male goalkeepers both adapted to the resultant constraint, but did scale their diving action differently. Female goalkeepers initiated the lateral dive within the action boundaries set by the resultant constraint, while male goalkeepers tended to dive late, beyond the action boundaries. Owing to the early dive, female goalkeepers saved more penalties than male in non-deceptive penalties. Nevertheless, female goalkeepers were also more susceptible to deception by the penalty taker than male goalkeepers. These findings extend our knowledge of the affordance-based control theory in sports and contribute to the understanding of gender differences in soccer penalty goalkeeping.

Self-report psychopathy scales are increasingly used in research and practice despite criticisms that they may be susceptible to response distortion and bias. We assessed the utility of including the Virtuous Responding (VR) and Deviant Responding (DR) validity scales from the Psychopathic Personality Inventory-Revised (PPI-R) for identifying underreporting and overreporting, respectively, on both the full and short-form versions of the Self-Report Psychopathy scale (SRP 4 and SRP-SF) in a pre/post experimental design. Using a sample of 384 male community members and a clinical comparison group of 99 males from a forensic outpatient program, we demonstrated that SRP scores were more susceptible to overreporting than underreporting, and that overreporting significantly and negatively affected convergent validity. Finally, baseline psychopathy scores were unrelated to successful response distortion (i.e., changing scores in correct direction while remaining undetected by the validity scales). It is recommended that assessments using self-report psychopathy scales consider including validity indices to detect response distortion. In doing so, it will be important to consider that general impression management may be conceptually distinct from specific forms of response distortion, such as the intentional amplification or minimization of psychopathic traits. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

In this paper, a secure distributed filtering problem is investigated for a state-saturated system subject to random occurring nonlinearities and deception attack. To resist the hostile attack from a malicious attacker who can modify the data of the transmission module according to a certain probability, an attack detector with a dynamic threshold is designed for each sensor to decide whether to broadcast the current measurement innovation to neighbors. A distributed filtering algorithm is designed to estimate the state and a sufficient condition is established to guarantee the mean-square boundedness of the estimation error. Moreover, a critical attack probability above which the steady-state estimation error covariance will exceed a pre-set value is found. In addition, a minimum attack magnitude is given to ensure that the attack signal is able to be completely detected. A numerical example is carried out to testify the validity of the proposed results.

The increasing demand to dispose of the cases swiftly, police often resort to third-degree methods to extract information from the individual; and in the process violate the fundamental rights to life and personal liberty stated under article 21 of the constitution of India. With the development of science and technology quickly eliciting the information is possible by adopting methods of polygraph, brain mapping, and narco analysis. In the past various experts, committees and judgements in courts have recommended these technologies to be used. Though there is a demand, it also raises serious legal, ethical and medical issues. Through this article we attempted to analyze the issues from various angles, and should take steps in the future to implement them. Keywords: Deception Detection Test (DDT), polygraph, brain mapping, narco analysis.

The purpose is to inform the seminary libraries to design library services based on an outside-in strategy to meet the information intents of the theological students from clandestine, unregistered Christian churches in China. Specifically, the goals of this research are to: 1. Examine how the previous tactic information practices—walking, poaching, reading, and deception—exercised routinely in the unregistered Christian communities in China were shaped by the information-impoverished situations. 2. Stratify how information intents could change their tactic practices in finding religious information, when members from these information-impoverished communities come to study at theological seminaries in the United States, where information is rich and freely accessible. The study applies Todd’s extended six categories of information intents to analyze de Certeau’s four types of tactic information practices in walking, poaching, reading, and deception/disguise, as demonstrated in the interviews and information world maps of the seventeen theological students from China.

On March 12, 2018, John Laubscher, owner of AJ's Archery in Nelson, NY, had a gut feeling and refused to sell a rifle to a Syracuse University student-disrupting a mass shooting (https://www.syracuse.com/crime/2018/04/how_gun_shop_owner_thwarted_on_the_edge_su_student_from_buying_high-capacity_rif.html. Accessed 10 Nov 2021). Prompted by this, we surveyed the opinions, beliefs, attitudes, and current practices of gun sellers in Onondaga County, NY, in regard to safe gun sales. The primary outcome was to determine which types of "concerning behaviors" are more likely to cause a seller to intervene in some manner. Secondary outcomes included the following: ascertaining the frequency of denials of customer purchases, frequency of reporting to law enforcement, and identifying any gaps that make it difficult for gun sellers to report behaviors to the authorities. Follow-up interviews were conducted with those who were willing to speak with the authors in more depth. A response rate of 12.9% was achieved. Sixty-two percent (62.5%) of respondents had some experience in uniformed services, with specialized training in mental or emotional crises, as well as deception detection. The majority found the training helpful in their gun selling career. Reasons for personal denials were reported as: "interest in illegal fittings," "information revealed during conversation," and "lack of basic knowledge of using the firearm looking to purchase." Two respondents stated that due to a lack of a "reporting protocol," they would not report any concerns to law enforcement. The study helps inform future research in regard to surveying more sellers across NY state and nationwide.

Os debates públicos sobre o fenômeno do negacionismo parecem se pautar sobre a ambiguidade da noção de engano: os “negacionistas profissionais” seriam aqueles que enganam, os cientistas seriam os que não (se) enganam e as “pessoas comuns” seriam as mais suscetíveis a se enganarem ou serem enganadas. Porém, estudos mostram que os negacionistas consideram sua própria atitude como uma precaução contra o engano; por isso, explicações que os tratam como anticientificistas, antidemocráticos e ignorantes não dão conta do fenômeno em toda sua complexidade. Neste artigo, recorro à noção nietzschiana de “vontade de verdade” para pensar o negacionismo como um efeito deletério da imagem da ciência como um escudo desinteressado contra o engano. Mais que isso, examino a hipótese de que a oposição verdade/engano nos torna a todos potenciais negacionistas, e proponho, como proteção contra esse risco, admitir os interesses que levam as pessoas a disputar os fatos científicos. Discuto também o contexto sociopolítico no qual o negacionismo pôde emergir e apresento alguns caminhos para uma noção de verdade mais condizente com as “questões de preocupação” (matters of concern) atuais.

The aim of this study is to instrumentally explore the cognitive and emotional load behind deception. According to literature, the cognitive and emotional load comprises of cognitive-, and emotional-related variables that are in association with the probability of lies. This study is a milestone of the Lie Research group at Karoli Gaspar University of the Reformed Church in Hungary. Acquaintances, friends, and other university students who were invited to our thoroughly organised interactive games. This research makes use of an interactive role-playing game called Mafia (also known as Werewolf). However, this version of the game also featured an interrogation session that was conducted by professionals who are familiar with the voice analysing software LVA-650. In order to establish the two-factor model, it was essential to carry out a confirmatory factor analysis. The voice segments (n = 969) collected from the interrogations served as the basis for the statistical investigation (research license: 278/2016/P). The confirmatory factor analysis showed significant correlations among the variables (Fig. 1). The model fit indices confirmed the hypothesised model (RMSEA: .043; SRMR: .035; TLI: .975; CFI: .987). During deception both emotional and cognitive load have various components, and they may appear in similar channels (e.g. micro-expressions, movements, changes in the voice). However, our aim was the explore the possibilities of the LVA-650, which can divide these two types of loads among algorithms. Our results suggest that both emotion and cognition play a major role in deception. These findings help researchers and professionals better understand deception and may alleviate the process of detecting lies. Thus far, this may be the first study in Hungary that documents instrumental methods about the cognitive and emotional background of deception.

Evidence published nearly 20 years ago suggested people tell more lies per social interaction via synchronous, distributed, and recordless media (the phone) versus relatively richer (face-to-face communication) and leaner media (email, instant messaging). With nontrivial changes to the size and variety of our media landscape, it is worth re-examining the relationship between deception and technology. Over 7 days, 250 participants reported their social interactions and lies across face-to-face communication, social media, texting, the phone, video chat, and email. Replicating Hancock, Thom-Santelli, and Ritchie (2004), people told the most lies per social interaction over synchronous, distributed, and recordless media (the phone, video chat), though the effects were small and between-person effects explained more variance than between-media effects. Lying rates were also associated with aversive personality traits, plus antisocial, and relational deception motives. Together, while media options have evolved, technological design features often remain stable and indicate deception rates. Theoretical contributions are discussed.

Deception jamming poses a fatal threat to the radar performance, and its jamming performance has been greatly improved through networking. However, available deception electronic counter‐countermeasure (ECCM) methods are mostly developed in the scenario of a single jamming source. Therefore, it is of great importance to develop deception ECCM methods that can counter multiple jammers. This work proposes a deception jamming discrimination method applicable to multiple jammer sources in distributed multiple‐radar system, based on the correlation coefficient between different target‐received signal vectors. The false targets generated by one jammer are highly correlated, while a radar target is uncorrelated with either other radar targets or false targets. For the estimated correlation coefficient, the Fisher z‐transformation is applied to determine the correlation between targets with the Z‐test. Since the jammer usually generates multiple false targets at once to enhance its deceptions, a target can be judged as a false target when multiple targets are highly correlated with it; otherwise a radar target is declared. More importantly, compared with existing methods, no prior information is required here. Simulation results corroborate the feasibility of the proposed discrimination method and its performance due to the influence of jamming‐to‐noise ratio. The spatial correlation of radar targets and geometry conditions are covered.

Groups often make better judgements than individuals, and recent research suggests that this phenomenon extends to the deception detection domain. The present research investigated whether the influence of groups enhances the accuracy of judgements, and whether group size influences deception detection accuracy. Two-hundred fifty participants evaluated written statements with a pre-established detection accuracy rate of 60% in terms of veracity before viewing either the judgements and rationales of several other group members or a short summary of the written statement and revising or restating their own judgements accordingly. Participants' second responses were significantly more accurate than their first, suggesting a small positive effect of structured groups on deception detection accuracy. Group size did not have a significant effect on detection accuracy. The present work extends our understanding of the utility of group deception detection, suggesting that asynchronous, structured groups outperform individuals at detecting deception.

With the development of digital radiofrequency memory devices, the deception jamming has become a major jamming type in radar electronic counter countermeasures, especially the dense deception jamming. Recent years, some methods using signal features are proposed for specific deception jamming excision scene. It verifies the feasibility that uses signal features to discriminate deception jamming. However, discriminator training and simulation are indeed hard to achievable since no jamming samples can be obtained in advance. In this letter, we focus on the online dense deception jamming discrimination problem without the offline data training. Since deception jamming signals generated by jammers are definitely different from physical backscattering target echoes on signal features and dense jamming signals generated by one jammer has similar signal fingerprint features, an unsupervised clustering method with heuristic feature extraction is proposed. All discrimination processes are data driven and can be executed online without a priori information. To evaluate its effectiveness, the proposed method is applied to a group of experimental data collected from a trial C -band radar. Results corroborate the proposed method and indicate the direction of future research.

This article focuses on the consensus control problem for a class of time-varying stochastic nonlinear time-delay multiagent systems (MASs) attacked by deception attacks. The stochastic deception attack is considered in the procedure of propagating measurement information among agents. To solve the consensus control problem for addressed MASs under stochastic deception attacks, a definition of quasi-consensus is put forward. The objective of our investigation is to devise a consensus protocol to drive all agents to stay within an allowable range despite the existence of stochasticity and external malicious attacks. With the help of recursive linear matrix inequality and stochastic analysis methods, sufficient conditions are acquired to guarantee that all agents are constrained in the desirable range. Subsequently, an optimization algorithm is presented, which is to seek the locally optimal allowable distance among agents. Finally, a simulation example is presented to demonstrate the availability of our proposed algorithm.

This paper is concerned with the event-triggered control (ETC) problem for switched systems in networked environments, which are suffered from denial-of-service (DoS) attack and deception attack. Considering that the packet in networked switched systems contains the sampled state and switching signal, DoS attack prevents the packet transmission to cause the zero input, while deception attack falsifies the packet to cause the asynchronous control input with nonlinear disturbance. First, the probabilistic characterization of invalid packet transmissions caused by two different attack models is constructed, namely the ratio of the number of packet transmissions suffering from network attacks to the total number of packet transmissions. Second, a suitable ETC scheme is designed to determine the next triggering instant, which guarantees that the value of Lyapunov function cannot exceed a given restriction and updates the control input at switching instant. After that, the average dwell time and control gains are designed to guarantee the almost sure asymptotic stability of such systems. Finally, a numerical simulation is given to verify the effectiveness of the theoretical results.

We propose deception as a bridging concept that will enhance the study of misinformation, disinformation, and misperceptions. As we set it out here, the concept integrates insights from multiple social science disciplines and uniquely connects actors’ intentions, information, and attitudinal or behavioral outcomes. A focus on deception will enrich research that describes the existence of false and misleading information but stops short of identifying their influence. Equally, through its focus on how actors’ deceptive strategies are important in attempts to exercise power, it can augment the study of the cognitive and attitudinal biases that render people susceptible to misperceptions. We identify the main themes in the study of deception: media-systemic distortions in information supply; the relational interactions that both produce and activate cognitive biases; and the attributes, strategies, and techniques of deceptive entities. We conclude with a summary typology of ten principal variables and their 57 focal indicators. Keywords: deception, misperceptions, misinformation, disinformation, media, power

Cognitive control is crucially involved in making (dis)honest decisions. However, the precise nature of this role has been hotly debated. Is honesty an intuitive response, or is will power needed to override an intuitive inclination to cheat? A reconciliation of these conflicting views proposes that cognitive control enables dishonest participants to be honest, whereas it allows those who are generally honest to cheat. Thus, cognitive control does not promote (dis)honesty per se; it depends on one's moral default. In the present study, we tested this proposal using electroencephalograms in humans (males and females) in combination with an independent localizer (Stroop task) to mitigate the problem of reverse inference. Our analysis revealed that the neural signature evoked by cognitive control demands in the Stroop task can be used to estimate (dis)honest choices in an independent cheating task, providing converging evidence that cognitive control can indeed help honest participants to cheat, whereas it facilitates honesty for cheaters.SIGNIFICANCE STATEMENTDishonesty causes enormous economic losses. To target dishonesty with interventions, a rigorous understanding of the underlying cognitive mechanisms is required. A recent study found that cognitive control enables honest participants to cheat, whereas it helps cheaters to be honest. However, it is evident that a single study does not suffice as support for a novel hypothesis. Therefore, we tested the replicability of this finding using a different modality (EEG instead of fMRI) together with an independent localizer task to avoid reverse inference. We find that the same neural signature evoked by cognitive control demands in the localizer task can be used to estimate (dis)honesty in an independent cheating task, establishing converging evidence that the effect of cognitive control indeed depends on a person's moral default.

Sex differences in mate preferences are well established. It is also well understood that humans often seek to manipulate their standing on important mate-value traits. Yet, there is a paucity of work examining potential sex differences in response to deception along these important dimensions. In Study 1, a sample of 280 undergraduates (123 females) responded to a hypothetical online dating scenario asking participants to rank how upset they would be if deceived about a date's attractiveness, occupation, or volunteerism. Women ranked occupation deception as more upsetting than men did, and men ranked attractiveness deception as more upsetting than women did. Given potential measurement differences between forced-choice and continuous response options, Study 2 randomly assigned 364 undergraduates (188 females) to one of the deceptions conditions and asked them to report their level of upset and willingness to go on the date using a continuous response scale. Women were more likely than men to cancel the date if the deception involved volunteerism or occupation. There was no significant sex difference in the attractiveness condition. Neither mate value nor sociosexuality moderated the sex difference in the levels of upset due to the deception. Together, these findings demonstrate that women and men exhibit differences in the degree to which they become upset by opposite sex deceptions in online dating, regardless of self-perceived mate value and sociosexuality, in alignment with evolved sex differences in mate preferences.

Purpose This paper aims to examine the dynamics of emotional cues and cognitive cues in review fakeness. Additionally, the boundary condition (i.e. review valence) for the dynamics between emotional cues and cognitive cues is investigated. Design/methodology/approach This research conducted two studies, which analyzed restaurant and hotel reviews collected from Yelp.com. The authors adopted linguistic inquiry and word count 2015 to code review contents and tested the hypotheses using logistic regression. Findings Fake reviews contain more emotional cues compared with authentic reviews. Moreover, the dynamics of emotional cues and cognitive cues are salient among negative reviews. Practical implications This research provides implications to identify fake online reviews based on linguistic cues. Originality/value This research contributes to the literature by revealing the competition of mental resources between emotional and cognitive systems when deception is for harming others. Grounded in interpersonal deception theory, this paper investigates the interactive effect and complements the literature, which mainly used emotional cues and cognitive cues individually to detect fake reviews.

Thermoregulation is often thought to be a key motivating factor behind the origins of clothing. Less attention has been given, however, to the production and use of clothing across traditional societies in contexts outside of thermoregulatory needs. Here I investigate the use of disguises, modesty coverings, and body armor among the 10 hunter-gatherer societies in the Probability Sample Files (PSF) within the Human Relations Area Files (HRAF) World Cultures database, with a particular focus on disguise cases and how they compare with strategies of deception across other taxa. The employment of disguises-defined as altering one's appearance for purposes of deceiving conspecifics or other animals-is noted for eight of the 10 societies, with their use occurring in contexts of hunting, religious or cult practices, and war or interpersonal violence. Most hunter-gatherer disguises demonstrated clear similarities to cases of visual deception found in other species, with the majority of examples fitting categories of animal mimicry, masquerading as plants, disruptive coloration (camouflage), or background matching (camouflage), while disguises unique to humans involved the impersonation of culture-specific "spirit-beings." Clothing for modesty purposes (nine societies) and body armor (six societies) are also noted. I propose that strategic initiatives by individuals or groups to disguise or conceal themselves represents one possible initial pathway to the cultural evolution of clothing. There are likely multiple potential (nonexclusive) social and functional pathways to the emergence of clothing outside of thermoregulatory needs.