Malicious Content Generation

Malicious content generation, encompassing the creation of harmful text, images, and code using AI models like large language models and diffusion models, is a growing concern. Current research focuses on developing methods to detect and mitigate this threat, including improving content filters, exploring concept removal techniques in image generation, and employing graph convolutional networks for detecting malicious code embedded in hardware. This research is crucial for addressing the ethical and security risks posed by increasingly sophisticated AI systems, impacting fields ranging from cybersecurity to social media moderation.