Traditional techniques for detecting deception, such as the 'lie-detector test' (or polygraph), are based upon the idea that lying is associated with stress. However, it is possible that people telling the truth will experience stress, whereas not all liars will. Because of this, the validity of such methods is questionable. As an alternative, a knowledge-based approach known as the 'Concealed Information Test' has been developed which investigates whether the examinee recognizes secret information - for example a crime suspect recognizing critical crime details that only the culprit could know. The Concealed Information Test has been supported by decades of research, and is used widely in Japan. This is the first book to focus on this exciting approach and will be of interest to law enforcement agencies and academics and professionals in psychology, criminology, policing and law.

Traditional techniques for detecting deception, such as the 'lie-detector test' (or polygraph), are based upon the idea that lying is associated with stress. However, it is possible that people telling the truth will experience stress, whereas not all liars will. Because of this, the validity of such methods is questionable. As an alternative, a knowledge-based approach known as the 'Concealed Information Test' has been developed which investigates whether the examinee recognizes secret information - for example a crime suspect recognizing critical crime details that only the culprit could know. The Concealed Information Test has been supported by decades of research, and is used widely in Japan. This is the first book to focus on this exciting approach and will be of interest to law enforcement agencies and academics and professionals in psychology, criminology, policing and law.

Improve your confidence in the validity of your test results! Detection of Response Bias in Forensic Neuropsychology examines strategies and procedures for determining the validity of results and the patient's motivation during neuropsychological testing. The book discusses procedures to help a clinician assess factors that can affect test accuracy. Developers and researchers present unique insights into each strategy's utility in clinical practice and each procedure's performance in light of factors defined by the United States Supreme Court. Detection of Response Bias in Forensic Neuropsychology examines the increasing need for practicing clinical neuropsychologists to identify response bias in their evaluations of a patient's neuropsychological impairment. The book presents major response bias detection strategies, addressing in each: whether the theory or technique has been tested; if it has been subjected to peer review and publication; the known or potential rate of error in applying the method; and to what extent the method has been accepted by the relevant scientific community. Each strategy represents a logical, scientific approach in forensic settings that can be applied in neuropsychological assessments. Detection of Response Bias in Forensic Neuropsychology includes comprehensive reviews of current procedures in wide usage to evaluate the validity of test results. Procedures covered include: Portland Digit Recognition Test Computerized Assessment of Response Bias (CARB) Warrington Recognition Memory Test Halstead-Reitan Battery Rey's strategies for detecting malingering validity scales of the Minnesota Multiphasic Personality Inventory (MMPI-2) Victoria Symptom Validity Test (VSVT) Test of Memory Malingering (TOMM) Word Memory Test (WMT) Category Test validity indicators much more! Detection of Response Bias in Forensic Neuropsychology is an essential resource for forensic professionals in determining patient compliance and motivation during testing.

This book, drawing on recent literature, highlights several methodologies for the detection of outliers and explains how to apply them to solve several interesting real-life problems. The detection of objects that deviate from the norm in a data set is an essential task in data mining due to its significance in many contemporary applications. More specifically, the detection of fraud in e-commerce transactions and discovering anomalies in network data have become prominent tasks, given recent developments in the field of information and communication technologies and security. Accordingly, the book sheds light on specific state-of-the-art algorithmic approaches such as the community-based analysis of networks and characterization of temporal outliers present in dynamic networks. It offers a valuable resource for young researchers working in data mining, helping them understand the technical depth of the outlier detection problem and devise innovative solutions to address related challenges.

This book presents state-of-the-art contributions from both scientists and practitioners working in intrusion detection and prevention for mobile networks, services, and devices. It covers fundamental theory, techniques, applications, as well as practical experiences concerning intrusion detection and prevention for the mobile ecosystem. It also includes surveys, simulations, practical results and case studies.

Deception is a ubiquitous phenomenon in social interactions and has attracted a significant amount of research during the last decades. The majority of studies in this field focused on how deception modulates behavioral, autonomic, and brain responses and whether these changes can be used to validly identify lies. Especially the latter question, which historically gave rise to the development of psychophysiological “lie detection” techniques, has been driving research on deception and its detection until today. The detection of deception and concealed information in forensic examinations currently constitutes one of the most frequent applications of psychophysiological methods in the field. With the increasing use of such methods, the techniques for detecting deception have been controversially discussed in the scientific community. It has been proposed to shift from the original idea of detecting deception per se to a more indirect approach that allows for determining whether a suspect has specific knowledge of crime-related details. This so-called Concealed Information Test is strongly linked to basic psychological concepts concerning memory, attention, orienting, and response monitoring. Although research in this field has intensified with the advancement of neuroimaging techniques such as PET and fMRI in the last decade, basic questions on the psychological mechanisms underlying modulatory effects of deception and information concealment on behavioral, autonomic, and brain responses are still poorly understood. This Research Topic brings together contributions from researchers in experimental psychology, psychophysiology, and neuroscience focusing on the understanding of the broad concept of deception including the detection of concealed information, with respect to basic research questions as well as applied issues. This Research Topic is mainly composed of originalresearch articles but reviews and papers elaborating on novel methodological approaches have also been included. Experimental methods include, but are not limited to, behavioral, autonomic, electroencephalographic or brain imaging techniques that allow for revealing relevant facets of deception on a multimodal level. While this Research Topic primarily includes laboratory work, relevant issues for the field use of such methods are also discussed.

Increased public awareness of traumatic brain injuries has fueled a number of significant developments: on the one hand, more funding and more research related to these injuries and their resulting deficits; on the other, the possibility of higher stakes in personal injury suits—and more reasons for individuals to feign injury. Expanding both the conceptual and clinical knowledge base on the subject, the Second Edition of Detection of Malingering during Head Injury Litigation offers the latest detection tools and techniques for veteran and novice alike. As in its initial incarnation, this practical revision demonstrates how to combine clinical expertise, carefully-gathered data, and the use of actuarial models as well as common sense in making sound evaluations and reducing ambiguous results. And, the book navigates the reader through the many caveats that come with the job, beginning with the scenario that an individual may be malingering despite having an actual brain injury. Among the updated features: •Specific chapters on malingering on the Halstead-Reitan, Luria-Nebraska, and MMPI-2. •A framework for distinguishing genuine from factitious PTSD in head injury cases. •Detailed information regarding performance on the WMT, MSVT, and NV-MSVT by children with developmental disabilities. •Guidelines for explaining symptom validity testing to the trier of fact. •Entirely new chapters on mild TBI and on malingering of PTSD symptoms in the context of TBI litigation. Professional neuropsychologists and forensic psychologists will appreciate this new edition of Detection of Malingering during Head Injury Litigation as an invaluable source of refinements to their craft, and improvement as an expert witness.

This book constitutes the refereed proceedings of the 13th International Symposium on Recent Advances in Intrusion Detection, RAID 2010, held in Ottawa, Canada, in September 2010. The 24 revised full papers presented together with 15 revised poster papers were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on network protection, high performance, malware detection and defence, evaluation, forensics, anomaly detection as well as web security.

This book constitutes the refereed proceedings of the 13th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2016, held in San Sebastián, Spain, in July 2016. The 19 revised full papers and 2 extended abstracts presented were carefully reviewed and selected from 66 submissions. They present the state of the art in intrusion detection, malware analysis, and vulnerability assessment, dealing with novel ideas, techniques, and applications in important areas of computer security including vulnerability detection, attack prevention, web security, malware detection and classification, authentication, data leakage prevention, and countering evasive techniques such as obfuscation.