Jailbreaking is an emerging adversarial attack that bypasses the safety alignment deployed
in off-the-shelf large language models (LLMs) and has evolved into multiple categories …

Penetration testing is essential to ensure Web security, which can detect and fix
vulnerabilities in advance, and prevent data leakage and serious consequences. The …

Large language models (LLMs) can transform natural language instructions into executable
commands for IoT devices like unmanned aerial vehicles (UAVs), creating new development …

Recently, large language models (LLMs) have demonstrated promising applications in the
autonomous driving (AD) domain, including language-based interactions and decision …

Jailbreaking attacks can effectively manipulate open-source large language models (LLMs)
to produce harmful responses. However, these attacks exhibit limited transferability, failing to …

Despite the implementation of safety alignment strategies, large language models (LLMs)
remain vulnerable to jailbreak attacks, which undermine these safety guardrails and pose …

Multimodal Large Language Models (MLLMs) bridge the gap between visual and textual
data, enabling a range of advanced applications. However, complex internal interactions …

The advancements in generative AI inevitably raise concerns about their risks and safety
implications, which, in return, catalyzes significant progress in AI safety. However, as this …

Large language models (LLMs) are widely applied in various fields of society due to their
powerful reasoning, understanding, and generation capabilities. However, the security …

Recently, the jailbreak attack, which generates adversarial prompts to bypass safety
measures and mislead large language models (LLMs) to output harmful answers, has …