Sexual Abuse

Sexual abuse, encompassing child sexual abuse material (CSAM) and broader forms of sexual harassment and violence, is a significant global problem demanding innovative solutions. Current research focuses on developing automated detection systems for CSAM and other forms of online sexual abuse using deep learning models, including end-to-end classifiers and self-supervised learning approaches for scene recognition, to mitigate the risks associated with manual review of such material. These efforts aim to improve the efficiency and safety of investigations while also providing insights into the characteristics of abusive imagery and judicial attitudes towards victims. The development and application of these technologies hold significant potential for enhancing law enforcement capabilities and informing policy decisions related to combating sexual abuse.