Background Artificial intelligence (AI) image generation has opened up endless possibilities for creativity, allowing architects, designers, and artists to produce visual models rapidly. However, this technology is responsible for creating deepfakes, which are highly realistic but fake images and videos. Deepfakes can be used to spread misinformation,...

In the rapidly advancing landscape of deep reinforcement learning (RL), recent studies have highlighted vulnerabilities in control policies learned through deep RL. These vulnerabilities raise concerns surrounding adversarial attacks, especially in risk-sensitive domains such as autonomous driving. In these scenarios, the learned policies become susceptible...

­Background Growing applications of generative models have led to new threats such as malicious personation and digital copyright infringement. One solution to these threats is model attribution, i.e., the identification of user-end models where the contents under question are generated from. Existing studies showed empirical feasibility of attribution...