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ai-watermarking

AI-generated content watermarking and detection

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SystemTechniques · 4Primitives · 29 ai-watermarking Invisible watermarkingsecurity · medium: Embedding robust imperceptible marks in images/audio/video or token sampling for later detectionWavelet transformsignal-processing · medium: Discrete wavelet transforms (Haar, CDF 9/7 lifting) for compression and multiscale analysisHypothesis testingstatistics · medium: Pick a test statistic, compare it to its distribution under "no effect", read off a p-value, and control error rates across one test or many.›Sequential probability ratio teststatistics · medium: Add up the log-likelihood ratio per observation and stop when it crosses a fixed bound; the least data of any test with the same error rates (for two point hypotheses).›Convolutional networksml-training · low: Layers that slide a small shared kernel over a grid, giving translation equivariance and few parameters; still the most compute-efficient choice for many vision tasks.›Discrete cosine transformnumerics · low: Fast integer DCT/DST block transforms used by image and video codecsPRNGs (PCG, xoshiro)numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.›Byte-pair encoding (BPE) tokenizati…machine-learning · low: Learn a subword vocabulary by repeatedly merging the most frequent adjacent pair; byte-level BPE encodes any input losslessly with 32k-200k tokens.›Calibrationmachine-learning · low: Make predicted probabilities match observed frequencies: measure with ECE, fix post hoc with temperature, Platt or isotonic scaling on held-out data.›Data augmentationmachine-learning · low: Generate label-preserving variants of each training example on the fly to enlarge the effective dataset and bake in invariances.›Image codecsmedia · low: JPEG (DCT, Huffman), PNG, HEIF/AVIF decoding and encoding fundamentalsPerceptual quality metrics (PSNR, S…media · low: Full-reference scores that say how bad a compressed picture looks: PSNR (pixel error), SSIM (structure), VMAF (learned fusion), and when each one lies.›Token samplingml-training · low: Turn a vector of scores into one chosen item with temperature, top-k, top-p, min-p, repetition penalties and a seed.›Perceptual hashingsearch-sort · low: Compact fingerprints (64 to 256 bits) of an image that stay close under resizing and recompression, compared by Hamming distance; pHash, dHash and Meta's PDQ.›Cbor cosesecurity · low: CBOR binary encoding and COSE signing/encryption structures (WebAuthn, C2PA, attestation)Digital signatures (Ed25519)security · low: Small, fast, deterministic public-key signatures that prove who produced a message; the default for tokens, releases and protocols.›Message authentication codes (HMAC,…security · low: A keyed short tag proving a message is unmodified and came from a key holder; pick HMAC, CMAC, KMAC or a one-time polynomial MAC by what primitive you already have.›X509 certificatessecurity · low: Certificate chains, path validation, SANs, revocation and short-lived issuanceShort-time Fourier transform and sp…signal-processing · low: Slide a window over a signal and FFT each frame to get a time-frequency picture; the front end of audio ML, vibration and radar analysis.›Forward error correctionsignal-processing · low: Add redundancy (LDPC, Reed-Solomon, XOR parity) so receivers repair loss without retransmit+ 13 more primitives

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