Rapid advancements in artificial intelligence (AI) have sparked growing concerns among
experts, policymakers, and world leaders regarding the potential for increasingly advanced …

AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …

Large generative AI models (LGAIMs), such as ChatGPT, GPT-4 or Stable Diffusion, are
rapidly transforming the way we communicate, illustrate, and create. However, AI regulation …

Instruction tuning is an effective technique to align large language models (LLMs) with
human intent. In this work, we investigate how an adversary can exploit instruction tuning by …

Large language models (LLMs) have skyrocketed in popularity in recent years due to their
ability to generate high-quality text in response to human prompting. However, these models …

Large language models for code have recently shown remarkable performance in
generating executable code. However, this rapid advancement has been accompanied by …

The powerful ability to understand, follow, and generate complex language emerging from
large language models (LLMs) makes LLM-generated text flood many areas of our daily …

Although machine learning is widely used in practice, little is known about practitioners'
understanding of potential security challenges. In this work, we close this substantial gap …

The recent O-RAN specifications promote the evolution of RAN architecture by function
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …

Speech deepfakes are artificial voices generated by machine learning models. Previous
literature has highlighted deepfakes as one of the biggest security threats arising from …