Digital Watermarking for Telltale Tamper Proofing and AuthenticationRobust WatermarkFragile WatermarkRequirementsRequirements in detailsChoice of embedding domainEncoderDecoderEmbedding one bit in a coefficientNoise analysisMild distortionProbability of not detecting a changed bitImplementation: an example based on Haar waveletIncorporating host dependence in watermark messageSimulation: with mean filterSimulation: with JPEG compressionSimulation: image tampering (original image)Simulation: image tampering (tampered image)Bit error in watermark detected (at lower DWT level)Bit error in watermark detected (at higher DWT level)DiscussionsDigital Watermarking for Telltale Tamper Proofing and AuthenticationDeepa Kundur, Dimitrios HatzinakosPresentation by Kin-chung WongRobust Watermark•Able to recover embedded message from media even when attacked•Application: –Authenticates content source–Digital rights management (DRM)–Embed secret message (steganography)Fragile Watermark•Embedded in such a way that, when the media is modified, the watermark tells something about the nature and strength of modification•Application: tamper-proofing for court evidence, certificates, financial documentsRequirements1. Indicate whether distortion exists.2. Indicate relative magnitude of distortion3. Characterize type of distortion, especially distinguishing between compression and intentional tampering4. Validate and authenticate without generating metadata (non-image data sent along with an image file) … (*)(*) Uninformed users need not pass along metadata with the image. However, decoder still needs additional information from encoder, including original watermark bit sequence.Requirements in details•The watermark can be extracted from watermarked media (z) without explicit knowledge of host (f).•Difference between w and provide information on signal modification, in terms of nature and strength of distortion•User decides whether to accept content as authentic, based on the above informationw%w%Choice of embedding domain•Discrete wavelet transform•For N-bit watermark, select N coefficients in the wavelet domain, and embed one bit per coefficient using quantization index modulation•Advantage: tampering is detected with both spatial and frequency localization by observing where errors occur mostEncoderHost DWT: Watermark: Coefficient selection key:Watermark quantization parameter (*):(*) different from, but related to coefficient rounding of file format( ),,k lf m n( ), 1, 2,...,ww i i N=( ), 1, 2,...,wckey i i N=DDecoderExtraction: get at the coefficient indicated by ckey(i)Tamper assessment function: (TAF) = (Number of bits flipped) / (Total number of bits)( )w i%( ) ( ) ( )11,wNiwTAF w w w i w iN== ��% %Embedding one bit in a coefficientfQuantized fQ“bin” functionOriginalwavelet coef.Noise analysis•Mild distortion–Small additive Gaussian noise– small, we can take approximations•Severe distortion–Extracted watermark bits become unpredictable–Heavy filtering, least-significant-bit truncation, image region substitution, geometrical distortion–No correlation between w(i) and /vs D( )w i%vMild distortion     iziziLetRed: Changed but not detectedGreen: Changed and detectedProbability of not detecting a changed bitImplementation:an example based on Haar wavelet•Choosing based on coefficient roundingIncorporating host dependence in watermark message•Generate a quantization key qkey(i) from some image characteristics•Perform XOR with qkey(i) and w(i) to get w*(i) to be embeddedSimulation: with mean filterM: mean filter lengthsl: TAF detected at l-th DWT level (detail  … … …  approximate)TAF: tamper assessment function / fraction of watermark bits changedSimulation: with JPEG compressionSimulation: image tampering(original image)Simulation: image tampering(tampered image)Bit error in watermark detected(at lower DWT level)Bit error in watermark detected(at higher DWT