Deception Detection Technologies: Current Advances andForensic Challenges

Deception detection remains a significant challenge in forensic, security, and legal contexts because traditional tools, such as the polygraph, measure physiological responses associated with stress rather than deception itself. This scoping review examines current deception-detection technologies, with particular emphasis on their technological advances, challenge and limitations in forensic applications, and future research directions. Following the PRISMA-ScR guidelines, searches were conducted in Scopus, PubMed, IEEE Xplore, and ScienceDirect to identify 80 journal articles and conference papers published over the past twenty years. Two independent reviewers selected the studies included in the review, and a Cohen’s kappa coefficient of 0.925 was obtained, indicating substantial inter-rater agreement. Five main technological families were identified: polygraphy, electroencephalography, functional magnetic resonance imaging, voice, facial, and body-movement analysis, and multimodal fusion based on artificial intelligence. Each technology involves trade-offs among accuracy, cost, portability, and forensic or legal admissibility. Although multimodal approaches report the highest accuracy levels, they also raise additional challenges related to governance and explainability. Currently, no single technology provides sufficient reliability to be used independently as forensic evidence. Future applications must address ethical, legal, and cultural considerations, particularly mental privacy, algorithmic transparency, and individual variability.