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Perfectly Secure Steganography Using Minimum Entropy Coupling

ICLR 2023 · Learning theory and algorithms › Prediction and decision losses · approach: Theory of neural network sensitivity · 12 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use iMEC for encoding instead of arithmetic coding, Meteor, or ADGInformation-theoretic steganography · GPT-2, WaveRNN, and Image Transformer covertext distributionsencoding efficiencyHelped
Use iMEC instead of arithmetic coding or ADGInformation-theoretic steganography · Covertext distributions evaluatedKL divergence between stegotext and covertextHelped
Use arithmetic coding or ADG instead of iMECInformation-theoretic steganography · Covertext distributions evaluatedKL divergence between stegotext and covertextHurt
Use iMEC with 20-bit blocks rather than smaller iMEC blocks (ablation)iMEC · GPT-2, WaveRNN, and Image Transformer covertext distributionsencoding efficiencyHelped
Increase iMEC block size from 10 bits to 16 or 20 bits (ablation)iMEC · Covertext distributions evaluatedencoding time: 10 bit blocks require an order of magnitude less time than model inference; 16 bit blocks require the same order of magnHurt
Use iMEC with a 16-bit block size (ablation)iMEC · Covertext distributions evaluatedencoding efficiencyMixed
Use iMEC with a 10-bit block size (ablation)iMEC · Covertext distributions evaluatedencoding efficiencyMixed
Use arithmetic coding instead of iMEC with 10- or 16-bit blocksInformation-theoretic steganography · Uniform covertextencoding efficiencyHelped
Use ADG instead of other methodsInformation-theoretic steganography · Uniform covertextencoding efficiencyHelped
Use ADG instead of other methodsInformation-theoretic steganography · Non-uniform covertext distributions, especially WaveRNNencoding efficiencyHurt
Use Meteor instead of iMEC variants or arithmetic codingInformation-theoretic steganography · Covertext distributions evaluatedencoding efficiencyHurt
Use Meteor:reorder instead of iMEC with 10-bit blocksInformation-theoretic steganography · GPT-2 90%encoding efficiencyHelped

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