Large Language Models for Blockchain Security: A Systematic Literature Review
arxiv(2024)
摘要
Large Language Models (LLMs) have emerged as powerful tools in various
domains involving blockchain security (BS). Several recent studies are
exploring LLMs applied to BS. However, there remains a gap in our understanding
regarding the full scope of applications, impacts, and potential constraints of
LLMs on blockchain security. To fill this gap, we conduct a literature review
on LLM4BS.
As the first review of LLM's application on blockchain security, our study
aims to comprehensively analyze existing research and elucidate how LLMs
contribute to enhancing the security of blockchain systems. Through a thorough
examination of scholarly works, we delve into the integration of LLMs into
various aspects of blockchain security. We explore the mechanisms through which
LLMs can bolster blockchain security, including their applications in smart
contract auditing, identity verification, anomaly detection, vulnerable repair,
and so on. Furthermore, we critically assess the challenges and limitations
associated with leveraging LLMs for blockchain security, considering factors
such as scalability, privacy concerns, and adversarial attacks. Our review
sheds light on the opportunities and potential risks inherent in this
convergence, providing valuable insights for researchers, practitioners, and
policymakers alike.
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