Black-Box Reconstruction Attacks on LLMs: A Preliminary Study in Code Summarization

Author:

Russodivito Marco,Spina Angelica,Scalabrino Simone,Oliveto Rocco

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Al-Kaswan, A., Izadi, M., van Deursen, A.: Targeted attack on GPT-neo for the SATML language model data extraction challenge. arXiv:2302.07735 (2023)

2. Al-Kaswan, A., Izadi, M., Van Deursen, A.: Traces of memorisation in large language models for code. In: IEEE/ACM International Conference on Software Engineering, pp. 1–12 (2024)

3. Carlini, N., Liu, C., Erlingsson, Ú., Kos, J., Song, D.: The secret sharer: evaluating and testing unintended memorization in neural networks. In: USENIX Security Symposium, pp. 267–284 (2019)

4. Carlini, N., et al.: Extracting training data from large language models. In: USENIX Security Symposium, pp. 2633–2650 (2021)

5. Fredrikson, M., Jha, S., Ristenpart, T.: Model inversion attacks that exploit confidence information and basic countermeasures. In: ACM SIGSAC Conference on Computer and Communications Security (CCS), pp. 1322–1333 (2015)

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