The Detection of Crime

Author(s):  
Brian H. Bornstein ◽  
Jeffrey S. Neuschatz

The deception detection method Münsterberg advocates is grounded on principles of association. Although this approach derives partially from a Freudian view of the unconscious, it is not terribly dissimilar to more modern, physiologically based lie detection methods. In recent years, deception detection has become a major focus within psychology and law. Research shows that humans’ ability to detect deception is limited but, summarizing across the body of studies, slightly better than chance. However, most police investigators believe they can detect when suspects are lying. This chapter covers the reliability of modern deception detection techniques with the exception of the polygraph, which is covered in the next chapter.

2020 ◽  
Vol 8 ◽  
pp. 199-214
Author(s):  
Xi (Leslie) Chen ◽  
Sarah Ita Levitan ◽  
Michelle Levine ◽  
Marko Mandic ◽  
Julia Hirschberg

Humans rarely perform better than chance at lie detection. To better understand human perception of deception, we created a game framework, LieCatcher, to collect ratings of perceived deception using a large corpus of deceptive and truthful interviews. We analyzed the acoustic-prosodic and linguistic characteristics of language trusted and mistrusted by raters and compared these to characteristics of actual truthful and deceptive language to understand how perception aligns with reality. With this data we built classifiers to automatically distinguish trusted from mistrusted speech, achieving an F1 of 66.1%. We next evaluated whether the strategies raters said they used to discriminate between truthful and deceptive responses were in fact useful. Our results show that, although several prosodic and lexical features were consistently perceived as trustworthy, they were not reliable cues. Also, the strategies that judges reported using in deception detection were not helpful for the task. Our work sheds light on the nature of trusted language and provides insight into the challenging problem of human deception detection.


2014 ◽  
Vol 1 (1) ◽  
pp. 122-128 ◽  
Author(s):  
Timothy R. Levine

Actively detecting deception requires (a) gathering information for fact-checking the communication content, (b) strategically prompting deception cues, and (c) encouraging honest admissions and discouraging continued deceit. Most deception-detection research, active or otherwise, finds that people are only slightly better than chance at correctly distinguishing truth from lies. Poor accuracy stems from a lack of reliable deception cues that hold across people and situations. Consequently, basing lie detection on deception cues is prone to error. However, some approaches to active deception detection yield higher accuracy than passive observation. Not all active approaches are advantageous. Mere interaction and mere question-asking produce outcomes similar to passive observation. Evidence-based and confession-solicitation approaches can be highly effective: for example, strategic use of evidence (SUE) and the content in context approach.


2014 ◽  
Vol 19 (3) ◽  
pp. 172-183 ◽  
Author(s):  
Matthias Gamer

Traditional lie detection tools, such as the polygraph, voice stress analysis, or special interrogation techniques, rely on behavioral or psychophysiological manifestations of deception. With the advent of neuroimaging techniques, the question emerged whether it would be possible to directly identify deceit in the part of the body where it is generated: the brain. After a few promising studies, these techniques became soon commercially available and there have been attempts to use such results in the court in recent years. The current article reviews the development of neuroimaging techniques in the field of deception detection and critically discusses the potential but also the shortcomings of such methods. Unfortunately, the majority of research in this field was rather unsystematic and neglected the accumulated knowledge regarding methodological pitfalls that were extensively discussed in the scientific community in conjunction with the polygraph. Therefore, neuroimaging studies on deception largely differ with respect to the experimental paradigm (the interrogation technique), the methods for analyzing the data, and the procedures to obtain individual diagnoses. Moreover, most studies used artificial laboratory settings that differ considerably from real-life applications. As a consequence, neuroimaging techniques are not applicable for detecting deception in individual field cases at the moment. However, recent advantages such as multivariate pattern analysis might yield novel neuroimaging applications in the near future that are capable of improving established techniques for detecting deception or concealed knowledge.


2021 ◽  
Vol 12 (2) ◽  
pp. 1-18
Author(s):  
Jessamyn Dahmen ◽  
Diane J. Cook

Anomaly detection techniques can extract a wealth of information about unusual events. Unfortunately, these methods yield an abundance of findings that are not of interest, obscuring relevant anomalies. In this work, we improve upon traditional anomaly detection methods by introducing Isudra, an Indirectly Supervised Detector of Relevant Anomalies from time series data. Isudra employs Bayesian optimization to select time scales, features, base detector algorithms, and algorithm hyperparameters that increase true positive and decrease false positive detection. This optimization is driven by a small amount of example anomalies, driving an indirectly supervised approach to anomaly detection. Additionally, we enhance the approach by introducing a warm-start method that reduces optimization time between similar problems. We validate the feasibility of Isudra to detect clinically relevant behavior anomalies from over 2M sensor readings collected in five smart homes, reflecting 26 health events. Results indicate that indirectly supervised anomaly detection outperforms both supervised and unsupervised algorithms at detecting instances of health-related anomalies such as falls, nocturia, depression, and weakness.


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiang Li ◽  
Jianzheng Liu ◽  
Jessica Baron ◽  
Khoa Luu ◽  
Eric Patterson

AbstractRecent attention to facial alignment and landmark detection methods, particularly with application of deep convolutional neural networks, have yielded notable improvements. Neither these neural-network nor more traditional methods, though, have been tested directly regarding performance differences due to camera-lens focal length nor camera viewing angle of subjects systematically across the viewing hemisphere. This work uses photo-realistic, synthesized facial images with varying parameters and corresponding ground-truth landmarks to enable comparison of alignment and landmark detection techniques relative to general performance, performance across focal length, and performance across viewing angle. Recently published high-performing methods along with traditional techniques are compared in regards to these aspects.


2021 ◽  
Vol 11 (12) ◽  
pp. 5685
Author(s):  
Hosam Aljihani ◽  
Fathy Eassa ◽  
Khalid Almarhabi ◽  
Abdullah Algarni ◽  
Abdulaziz Attaallah

With the rapid increase of cyberattacks that presently affect distributed software systems, cyberattacks and their consequences have become critical issues and have attracted the interest of research communities and companies to address them. Therefore, developing and improving attack detection techniques are prominent methods to defend against cyberattacks. One of the promising attack detection methods is behaviour-based attack detection methods. Practically, attack detection techniques are widely applied in distributed software systems that utilise network environments. However, there are some other challenges facing attack detection techniques, such as the immutability and reliability of the detection systems. These challenges can be overcome with promising technologies such as blockchain. Blockchain offers a concrete solution for ensuring data integrity against unauthorised modification. Hence, it improves the immutability for detection systems’ data and thus the reliability for the target systems. In this paper, we propose a design for standalone behaviour-based attack detection techniques that utilise blockchain’s functionalities to overcome the above-mentioned challenges. Additionally, we provide a validation experiment to prove our proposal in term of achieving its objectives. We argue that our proposal introduces a novel approach to develop and improve behaviour-based attack detection techniques to become more reliable for distributed software systems.


Author(s):  
V. Purushothaman ◽  
K. Vinoth Kumar ◽  
Sabari Girish Ambat ◽  
R. Venkataswami

Abstract Background Total brachial plexus palsy (TBPP) accounts for nearly 50% of all brachial plexus injuries. Since achieving a good functional hand was almost impossible, the aim was settled to get a good shoulder and elbow function. It was Gu, who popularized the concept of utilizing contralateral C7 (CC7) with vascularized ulnar nerve graft (VUNG) to get some hand function. We have modified it to suit our patients by conducting it as a single-stage procedure, thereby trying to get a functional upper limb. Methods From 2009 to 2014, we had 20 TBPP patients. We feel nerve reconstruction is always better than any other salvage procedure, including free muscle transfer. We modified Gu's concept and present our concept of total nerve reconstruction as “ALL IN ONE OR (W)HOLE IN ONE REPAIR.” Results All patients able to move their reconstructed limbs independently or with the help of contralateral limbs. Three patients developed hook grip and one patient was able to incorporate limbs to do bimanual jobs. One important observation is that all the reconstructed limbs regain the bulk, and to a certain extent, the attitude and appearance looks normal, as patients no longer hide it or hang it in a sling. Conclusion Adult brachial plexus injury itself is a devastating injury affecting young males. By doing this procedure, the affected limb is not dissociated from the rest of the body and rehabilitation can be aimed to get a supportive limb.


Author(s):  
Wei Liang ◽  
Lai-bin Zhang ◽  
Zhao-hui Wang

In China, the rarefaction-pressure wave techniques are widely used to diagnose the leakage fault for liquid pipelines. Many leaking propagating assumptions, such as stable single-phased flow hypothesis and none rarefaction wave front hypothesis, are often uncertain in the process of leak detection, which can easily result in some errors. Thus the rarefaction-pressure wave techniques should be integrated with other analytical techniques to compute a more accurate leak location. Additionally, the development trends of rarefaction-pressure wave techniques lie in three aspects. First, rarefaction-pressure wave detection techniques will be integrated with other compatible detection techniques and modern signal processing methods to solve the complex problems encountered in leak detection. Second, studies of rarefaction-pressure wave techniques have advanced to a new stage. The deductions on propagation mechanism of rarefaction-pressure wave have been successfully applied to determine leaks qualitatively. Third, analysis on rarefaction-pressure wave detection techniques will be made from a quantitative point of view. The quantitative data have been used to deduce leak amounts and location. The purpose of this paper is to present the recent achievements in the study of improved rarefaction-pressure wave detection techniques. The rarefaction-pressure wave detection methods, effects of incomplete information conditions, the improvements of rarefaction-pressure wave detection techniques with modified factors and propagation mechanisms are comprehensively investigated. The disfigurements of rarefaction-pressure wave are analyzed. The corresponding methods for resolving such problems as ill diagnostic information and weak amplitude values are put forward. Several methods for stronger small leakage detection ability, higher leakage positioning precision, lower false alarm rates are proposed. The application of rarefaction-pressure wave detection techniques to safety protection of liquid pipelines is also introduced. Finally, the prospect of rarefaction-pressure wave detection techniques is predicted.


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