Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices

arXiv:2403.12503v1 Announce Type: cross
Abstract: 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 …

abstract arxiv challenges cs.ai cs.cr cs.lg diverse impact landscape language language models language processing language understanding large language large language models llms natural natural language natural language processing nlp practices processing responsible risk security spectrum tasks threats type understanding utility vulnerabilities