  With the advent of accessible interfaces for interacting with large language
models, there has been an associated explosion in both their commercial and
academic interest. Consequently, there has also been an sudden burst of novel
attacks associated with large language models, jeopardizing user data on a
massive scale. Situated at a comparable crossroads in its development, and
equally prolific to LLMs in its rampant growth, blockchain has emerged in
recent years as a disruptive technology with the potential to redefine how we
approach data handling. In particular, and due to its strong guarantees about
data immutability and irrefutability as well as inherent data provenance
assurances, blockchain has attracted significant attention as a means to better
defend against the array of attacks affecting LLMs and further improve the
quality of their responses. In this survey, we holistically evaluate current
research on how blockchains are being used to help protect against LLM
vulnerabilities, as well as analyze how they may further be used in novel
applications. To better serve these ends, we introduce a taxonomy of blockchain
for large language models (BC4LLM) and also develop various definitions to
precisely capture the nature of different bodies of research in these areas.
Moreover, throughout the paper, we present frameworks to contextualize broader
research efforts, and in order to motivate the field further, we identify
future research goals as well as challenges present in the blockchain for large
language model (BC4LLM) space.
