How To Simulate It - A Tutorial on the Simulation Proof Technique

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Secure Single-Server Aggregation with (Poly)Logarithmic Overhead (2020, methodology): “note that the proof of security uses a standard simulation-based approach [20, 28] similar to the one by Bonawitz et al.”
Privacy-Preserving Distributed Linear Regression on High-Dimensional Data (2017, methodology): “To prove security, we use a simulation-based approach [30, 47] where one argues that a protocol is secure if it can be simulated in an ideal environment in which there is no data leakage by definition.”
Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference (2022, methodology): “We provide security against a static semi-honest probabilistic polynomial time adversary A following the simulation paradigm [11, 22, 38].”
Fast Private Set Intersection from Homomorphic Encryption (2017, background): “For a formal definition of simulation based security in the semi-honest setting, we refer the reader to [40].”
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges (2022, methodology): “Note that We refer to SFL protocols as FL protocols that attains the security in the simulation-based framework used to formalize the notion of security [132, 133, 134].”
CrypTFlow2: Practical 2-Party Secure Inference (2020, methodology): “Semi-honest security of the protocol will follow trivially from sequential composibility of individual sub-protocols [18, 32, 47].”