Signed-Prompt: A New Approach to Prevent Prompt Injection Attacks Against LLM-Integrated Applications

Abstract

The critical challenge of prompt injection attacks in Large Language Models (LLMs) integrated applications, a growing concern in the Artificial Intelligence (AI) field. Such attacks, which manipulate LLMs through natural language inputs, pose a significant threat to the security of these applications. Traditional defense strategies, including output and input filtering, as well as delimiter use, have proven inadequate. This paper introduces the 'Signed-Prompt' method as a novel solution. The stu

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@inproceedings{suo2024signedprompt,
  title = {{Signed-Prompt: A New Approach to Prevent Prompt Injection Attacks Against LLM-Integrated Applications}},
  author = {X. Suo},
  year = {2024},
  month = jan,
  booktitle = {AIP Conference Proceedings},
  eprint = {2401.07612},
  archivePrefix = {arXiv},
  doi = {10.48550/arXiv.2401.07612},
  url = {https://www.semanticscholar.org/paper/2742c3d77c4aa6d023b7dfc77984ad10e6aae274}
}