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Shared Secret

Cryptographic technique that divides a secret into multiple shares distributed among different participants, where no individual share reveals information about the secret, but a predefined threshold of shares allows its reconstruction.

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Random Masking

Protection method consisting of adding random values to gradients before transmission, with a guaranteed global zero sum ensuring that the final aggregation remains unchanged while masking individual contributions.

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Compliance Verification

Cryptographic mechanism allowing verification that gradients submitted by clients follow the expected protocol without revealing their exact content, thus detecting malicious behavior or transmission errors.

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BGW Protocol

Secure multi-party computation protocol developed by Ben-Or, Goldwasser and Wigderson, allowing participants to collectively evaluate an arithmetic function on their private inputs without revealing them.

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SPDZ Protocol

Advanced secure computation framework offering active security against malicious adversaries, combining secret sharing, MAC authentication and preprocessing to guarantee the integrity of distributed computations.

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Differentially Private Aggregation

Approach integrating differential privacy into the aggregation process, adding controlled noise to aggregated gradients to ensure that individual contributions cannot be inferred from the final model.

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Gaussian Noise

Random noise distribution following a normal law, used in differential privacy mechanisms to mask individual contributions while preserving the global statistical properties of aggregations.

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Exponential Mechanism

Differential privacy algorithm that selects an output with a probability exponentially proportional to its utility score, offering an optimal trade-off between utility and privacy protection.

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Yao's Protocol

Fundamental secure two-party computation protocol allowing two participants to evaluate a function on their private inputs without revealing them, using boolean circuits and cryptographic gates.

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Secure Multi-Party Computation

Cryptographic paradigm allowing a group of participants to jointly compute a function on their private inputs without revealing these inputs beyond the function's result.

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Cryptographic Hash Function

One-way mathematical function transforming an arbitrary-sized input into a fixed-size output, used to guarantee the integrity and authenticity of messages transmitted in aggregation protocols.

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Digital Signature

Cryptographic mechanism based on asymmetric cryptography allowing authentication of the origin and integrity of transmitted gradients, ensuring that only an authorized entity can submit updates.

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Zero-Knowledge Proof

Cryptographic protocol allowing a prover to demonstrate knowledge of information without revealing that information, used to verify the validity of calculations without compromising confidentiality.

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Program Obfuscation

Technique transforming a program into a functionally equivalent but structurally complex version, making its analysis or reverse engineering difficult to protect aggregation algorithms.

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Secure Weighted Aggregation

Variant of secure aggregation where client contributions are weighted according to metrics like data quality or computing power, while maintaining the confidentiality of individual weights.

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Secure Gradient Compression

Technique combining gradient compression and cryptography to reduce necessary bandwidth while preserving confidentiality, often using secure quantization and entropy coding methods.

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Accusation Protocol

Mechanism allowing participants to report abnormal or malicious behaviors during aggregation, with cryptographic proofs ensuring the authenticity of accusations without compromising confidentiality.

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Differential Update

Approach where clients transmit only the differences between their current and previous gradients, reducing disclosed information and enabling more efficient aggregation with better privacy protection.

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