Alignment defenses adapted from DPO and GRPO mitigate property inference attacks on LLMs while preserving utility.
Proceedings of the 20th International Conference on Security and Cryptography - SECRYPT , year=
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Fair fine-tuning under Equalized Odds yields a tight bound Adv(A, M_f) ≤ Δ_EO · W on adversarial advantage in distribution inference attacks, with empirical reductions below detection threshold across six datasets.
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Alignment Defends LLMs from Property Inference Attacks
Alignment defenses adapted from DPO and GRPO mitigate property inference attacks on LLMs while preserving utility.
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Fair Finetuning Mitigates Distribution Inference Attacks
Fair fine-tuning under Equalized Odds yields a tight bound Adv(A, M_f) ≤ Δ_EO · W on adversarial advantage in distribution inference attacks, with empirical reductions below detection threshold across six datasets.