Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Ealias, Aleena; Jayabalan, Bhuvana; Priya, Mohana Title A name given to the resource AI-Based Risk Profiling of Online Human Trafficking Victims: A Multimodal Framework for Proactive Detection Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings - 2025 International Conference on Transformative Computing Technologies, ICTCT 2025;pp.50-55 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICTCT69201.2025.00027" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICTCT69201.2025.00027</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037443495?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037443495?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ealias A., Christ University, Department of Computer Science, Bengaluru, India; Jayabalan B., Christ University, Department of Computer Science, Bengaluru, India; Priya M., Christ University, Department of Computer Science, Bengaluru, India Description An account of the resource Human trafficking is still a major worldwide crime that is made easier by digital channels, including social media, job advertisements, and websites that offer escort services. This study offers a thorough examination of artificial intelligence (AI) approaches to human trafficking detection and prevention, with a focus on identifying the most susceptible groups. From authorship attribution and geolocation extraction to social network analysis and multimodal detection, we analyze around 20 scholarly papers that include text, photos, audio, and network data. Lack of victim-focused profiling, data scarcity, bias in AI, and ethical deployment issues are some of the main research needs. In response, we provide a conceptual AI system that uses publicly available signals to evaluate individual vulnerability by combining network analysis, natural language processing, and weakly supervised learning. This work emphasizes the importance of ethically grounded AI systems to assist NGOs, law enforcement, and policymakers proactively identify at-risk individuals and prevent exploitation before it occurs. 2025 IEEE. Subject The topic of the resource ethical AI; Human trafficking detection; multimodal AI; social network analysis; victim risk profiling; weakly supervised learning Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833159195-3; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online