scholarly journals Automated Deception Detection Systems, a Review

2021 ◽  
pp. 70-80
Author(s):  
Shaimaa H. Abd ◽  
Ivan A. Hashim ◽  
Ali Sadeq A. Jalal

Humans use deception daily since it can significantly affect their life and provide a getaway solution for any undesired situation. Deception is either related to low-stakes (e.g. innocuous) or high-stakes (e.g. with harmful situations). Deception investigation importance has increased, and it became a critical issue over the years with the increase of security levels around the globe. Technology has made remarkable achievements in many human life fields, including deception detection. Automated deception detection systems (DDSs) are widely used in different fields, especially for security purposes. The DDS is comprised of multiple stages, each of which should be built/trained to perform intelligently so that the whole system can give the right decision of whether the involved person is telling the truth or not. Thus, different artificial intelligent (AI) algorithms have been utilized by the researchers over the past years. In addition, there are different cues for DDS that have been considered for the previous works, which are either related to verbal or non-verbal cues. This paper presents a review on the basic methods and the used deception detection techniques for the recent 10 years, that were studied and performed in the field of DDS, with a comparison of the deception detection accuracy reached and the number of participants used for system training.

2021 ◽  
Author(s):  
Christopher Albert Gunderson ◽  
Leanne ten Brinke ◽  
Peter Sokol-Hessner

Recent research suggests that people experience distinct physiological reactions to lies versus truths. It is unclear, however, if this experience is incorporated into greater truth-lie judgment accuracy. We hypothesized individuals with high interoceptive accuracy—those with greater access to bodily experiences and stronger physiological responses to emotional stimuli—might be particularly likely to accurately discriminate high-stakes, emotional lies and truths. Participants (n = 71) completed two study sessions: the first assessed their interoceptive accuracy with heartbeat detection measures and the second assessed their deception detection ability while measuring their physiological reactivity. Interoceptive accuracy was associated with a greater difference in vasoconstriction to liars (vs. truth-tellers), suggesting that interoception was positively associated with physiological sensitivity to deception. Interoceptive accuracy, however, was unrelated to deception detection accuracy. While better interoception provides enhanced physiological signals that could better discriminate lies from truths, it does not improve deception detection accuracy.


2021 ◽  
pp. 073346482110497
Author(s):  
Christopher A. Gunderson ◽  
Leanne ten Brinke

Although poor deception detection accuracy is thought to be an important risk factor for fraud among older adults, this link has not been explicitly studied. Using a cross-sectional design, older and young adults viewed and made judgments of real, high-stakes truths and lies with financial consequences. Older (vs. young) adults exhibited a greater truth bias when evaluating individuals pleading for help in finding a missing relative, which was associated with greater donations to deceptive pleaders. However, all participants were highly vulnerable to fraud. Future research should consider both risk and protective factors affecting financial fraud across the lifespan.


2017 ◽  
Vol 9 (2) ◽  
pp. 101-118 ◽  
Author(s):  
Gheorghe Sebestyen ◽  
Anca Hangan

AbstractNowadays, when multiple aspects of our life depend on complex cyber-physical systems, automated anomaly detection, prevention and handling is a critical issue that inuence our security and quality of life. Recent catastrophic events showed that manual (human-based) handling of anomalies in complex systems is not recommended, automatic and intelligent handling being the proper approach. This paper presents, through a number of case studies, the challenges and possible solutions for implementing computer-based anomaly detection systems.


2018 ◽  
Vol 45 (5) ◽  
pp. 794-807
Author(s):  
Suzanne L. K. Stewart ◽  
Clea Wright ◽  
Catherine Atherton

Despite evidence that variation exists between individuals in high-stakes truth and deception detection accuracy rates, little work has investigated what differences in individuals’ cognitive and emotional abilities contribute to this variation. Our study addressed this question by examining the role played by cognitive and affective theory of mind (ToM), emotional intelligence (EI), and various aspects of attention (alerting, orienting, executive control) in explaining variation in accuracy rates among 115 individuals (87 women; mean age = 27.04 years [ SD = 11.32]) who responded to video clips of truth-tellers and liars in real-world, high-stakes contexts. Faster attentional alerting supported truth detection, and better cognitive ToM and perception of emotion (an aspect of EI) supported deception detection. This evidence indicates that truth and deception detection are distinct constructs supported by different abilities. Future research may address whether interventions targeting these cognitive and emotional traits can also contribute to improving detection skill.


Author(s):  
Gregor Volberg

Previous studies often revealed a right-hemisphere specialization for processing the global level of compound visual stimuli. Here we explore whether a similar specialization exists for the detection of intersected contours defined by a chain of local elements. Subjects were presented with arrays of randomly oriented Gabor patches that could contain a global path of collinearly arranged elements in the left or in the right visual hemifield. As expected, the detection accuracy was higher for contours presented to the left visual field/right hemisphere. This difference was absent in two control conditions where the smoothness of the contour was decreased. The results demonstrate that the contour detection, often considered to be driven by lateral coactivation in primary visual cortex, relies on higher-level visual representations that differ between the hemispheres. Furthermore, because contour and non-contour stimuli had the same spatial frequency spectra, the results challenge the view that the right-hemisphere advantage in global processing depends on a specialization for processing low spatial frequencies.


2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Nurul Fatima Hasan

Indeed, in terms of the whole implementation of life has been arranged in the view of Islamic teachings to regulate all human life including in relation to the implementation of the economy and business. Islam does not allow any person to work haphazardly to achieve his/her goals and desires by justifying any means such as committing fraud, cheating, false vows, usury, and any other vanity deeds. But, Islam has given a boundary or line between the allowable and the unlawful, the right and wrong and the lawful and the unlawful. These limits or dividing lines are known as ethics. Behavior in business or trade is also not escaped from the moral value or business ethics values. Islamic business ethics is of which adheres to the principle of unity, equilibrium principle, freewill principle, responsibility principle, It is important for business people to integrate that ethical dimension into the framework or scope of the business. Keyword: Ethics, Business Ethics, Islamic Business Ethic.


2019 ◽  
Author(s):  
Valentina Escotet Espinoza

UNSTRUCTURED Over half of Americans report looking up health-related questions on the internet, including questions regarding their own ailments. The internet, in its vastness of information, provides a platform for patients to understand how to seek help and understand their condition. In most cases, this search for knowledge serves as a starting point to gather evidence that leads to a doctor’s appointment. However, in some cases, the person looking for information ends up tangled in an information web that perpetuates anxiety and further searches, without leading to a doctor’s appointment. The Internet can provide helpful and useful information; however, it can also be a tool for self-misdiagnosis. Said person craves the instant gratification the Internet provides when ‘googling’ – something one does not receive when having to wait for a doctor’s appointment or test results. Nevertheless, the Internet gives that instant response we demand in those moments of desperation. Cyberchondria, a term that has entered the medical lexicon in the 21st century after the advent of the internet, refers to the unfounded escalation of people’s concerns about their symptomatology based on search results and literature online. ‘Cyberchondriacs’ experience mistrust of medical experts, compulsion, reassurance seeking, and excessiveness. Their excessive online research about health can also be associated with unnecessary medical expenses, which primarily arise from anxiety, increased psychological distress, and worry. This vicious cycle of searching information and trying to explain current ailments derives into a quest for associating symptoms to diseases and further experiencing the other symptoms of said disease. This psychiatric disorder, known as somatization, was first introduced to the DSM-III in the 1980s. Somatization is a psycho-biological disorder where physical symptoms occur without any palpable organic cause. It is a disorder that has been renamed, discounted, and misdiagnosed from the beginning of the DSMs. Somatization triggers span many mental, emotional, and cultural aspects of human life. Our environment and social experiences can lay the blueprint for disorders to develop over time; an idea that is widely accepted for underlying psychiatric disorders such as depression and anxiety. The research is going in the right direction by exploring brain regions but needs to be expanded on from a sociocultural perspective. In this work, we explore the relationship between somatization disorder and the condition known as cyberchondria. First, we provide a background on each of the disorders, including their history and psychological perspective. Second, we proceed to explain the relationship between the two disorders, followed by a discussion on how this relationship has been studied in the scientific literature. Thirdly, we explain the problem that the relationship between these two disorders creates in society. Lastly, we propose a set of intervention aids and helpful resource prototypes that aim at resolving the problem. The proposed solutions ranged from a site-specific clinic teaching about cyberchondria to a digital design-coded chrome extension available to the public.


2021 ◽  
Vol 11 (13) ◽  
pp. 6016
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho

For autonomous vehicles, it is critical to be aware of the driving environment to avoid collisions and drive safely. The recent evolution of convolutional neural networks has contributed significantly to accelerating the development of object detection techniques that enable autonomous vehicles to handle rapid changes in various driving environments. However, collisions in an autonomous driving environment can still occur due to undetected obstacles and various perception problems, particularly occlusion. Thus, we propose a robust object detection algorithm for environments in which objects are truncated or occluded by employing RGB image and light detection and ranging (LiDAR) bird’s eye view (BEV) representations. This structure combines independent detection results obtained in parallel through “you only look once” networks using an RGB image and a height map converted from the BEV representations of LiDAR’s point cloud data (PCD). The region proposal of an object is determined via non-maximum suppression, which suppresses the bounding boxes of adjacent regions. A performance evaluation of the proposed scheme was performed using the KITTI vision benchmark suite dataset. The results demonstrate the detection accuracy in the case of integration of PCD BEV representations is superior to when only an RGB camera is used. In addition, robustness is improved by significantly enhancing detection accuracy even when the target objects are partially occluded when viewed from the front, which demonstrates that the proposed algorithm outperforms the conventional RGB-based model.


Author(s):  
Keren Dopelt ◽  
Dganit Cohen ◽  
Einat Amar-Krispel ◽  
Nadav Davidovitch ◽  
Paul Barach

The demand for medical assistance in dying remains high and controversial with a large knowledge gap to support optimal patient care. The study aimed to explore physicians’ attitudes regarding euthanasia and examine the factors that related to these attitudes. We surveyed 135 physicians working at a tertiary-care hospital in Israel. The questionnaire was comprised of demographic and background information, DNR procedure information, encounters with terminally ill patients, familiarity with the law regarding end-of-life questions, and Attitudes toward Euthanasia. About 61% agreed that a person has the right to decide whether to expedite their own death, 54% agreed that euthanasia should be allowed, while 29% thought that physicians should preserve a patients’ life even when they expressed the wish to die. A negative statistically significant relationship was found between the level of religiosity and attitudes toward euthanasia. The physicians’ attitudes towards euthanasia are quite positive when compared to other countries. The data shows a conflict of values: the sacredness of human life versus the desire to alleviate patients’ suffering. The Coronavirus-19 outbreak reinforces the importance of supporting physicians’ efforts to provide ethical and empathic communication for terminally ill patients. Future studies should aim to improve our understanding and treatment of the specific types of suffering that lead to end-of-life requests.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1581
Author(s):  
Xiaolong Chen ◽  
Jian Li ◽  
Shuowen Huang ◽  
Hao Cui ◽  
Peirong Liu ◽  
...  

Cracks are one of the main distresses that occur on concrete surfaces. Traditional methods for detecting cracks based on two-dimensional (2D) images can be hampered by stains, shadows, and other artifacts, while various three-dimensional (3D) crack-detection techniques, using point clouds, are less affected in this regard but are limited by the measurement accuracy of the 3D laser scanner. In this study, we propose an automatic crack-detection method that fuses 3D point clouds and 2D images based on an improved Otsu algorithm, which consists of the following four major procedures. First, a high-precision registration of a depth image projected from 3D point clouds and 2D images is performed. Second, pixel-level image fusion is performed, which fuses the depth and gray information. Third, a rough crack image is obtained from the fusion image using the improved Otsu method. Finally, the connected domain labeling and morphological methods are used to finely extract the cracks. Experimentally, the proposed method was tested at multiple scales and with various types of concrete crack. The results demonstrate that the proposed method can achieve an average precision of 89.0%, recall of 84.8%, and F1 score of 86.7%, performing significantly better than the single image (average F1 score of 67.6%) and single point cloud (average F1 score of 76.0%) methods. Accordingly, the proposed method has high detection accuracy and universality, indicating its wide potential application as an automatic method for concrete-crack detection.


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