Securing Large Language Models: Threats, Vulnerabilities and Responsible
  Practices
Sara Abdali Richard Anarfi CJ Barberan Jia He
Large language models (LLMs) have significantly transformed the landscape of
Natural Language Processing (NLP). Their impact extends across a diverse
spectrum of tasks, revolutionizing how we approach language understanding and
generations. Nevertheless, alongside their remarkable utility, LLMs introduce
critical security and risk considerations. These challenges warrant careful
examination to ensure responsible deployment and safeguard against potential
vulnerabilities. This research paper thoroughly investigates security and
privacy concerns related to LLMs from five thematic perspectives: security and
privacy concerns, vulnerabilities against adversarial attacks, potential harms
caused by misuses of LLMs, mitigation strategies to address these challenges
while identifying limitations of current strategies. Lastly, the paper
recommends promising avenues for future research to enhance the security and
risk management of LLMs.