Jaroslaw Kutylowski 1 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Robust Undetectable Interference Watermarks Ryszard Grząślewicz (WUT) Mirosław Kutyłowski (WUT) Jarosław Kutyłowski (HNI) Wojciech Pietkiewicz (WUT)

Jaroslaw Kutylowski 2 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Introduction Motivation undetectable watermarks cannot be detected in an image only the owner can prove his rights to an image using a secret private key not suited for web crawlers Key features of our scheme watermarks encoded in spatial domain resistant against attack preserving distance between points (filtering, rotation, JPEG compression) resistance against some attacks changing distance between points watermark can be reconstructed from a small part of image original image not needed for reconstruction large computational effort for reconstruction needed

Jaroslaw Kutylowski 3 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Physical motivation Interference – Young‘s experiment

Jaroslaw Kutylowski 4 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Scheme overview Watermark image Interference image Watermarked image Reconstructed watermark image Cover image

Jaroslaw Kutylowski 5 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Construction of simple interference image Watermark image all black with some white points white points are light source set of white points

Jaroslaw Kutylowski 6 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Construction of simple interference image Interference image interference image is placed at distance on top of watermark image each “light source” from influences each point of interference image distance and determine strength of influence this is approximation of real physical interference image drawback: visible pattern

Jaroslaw Kutylowski 7 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Construction of encrypted interference image Interference image consider the influence of one point from previously it influenced a point at distance with a ring at distance consists of cells of size intensity of each cell defined by value of hash function the angle is taken modulo – repetition of the same sequence key is needed for computation of values interference image does not contain visible patterns

Jaroslaw Kutylowski 8 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Scheme overview Watermark image Interference image Watermarked image Reconstructed watermark image Cover image

Jaroslaw Kutylowski 9 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Reconstruction of watermark General idea determine the intensity of each point of the watermark image –take the watermarked image (cover image + interference image) –generate interference image for point –compare them –if there is strong “similarity” – assign a high value watermarked imageinterference image for Low similarity small pixel value High similarity large pixel value Example with simple interference image not with encrypted – usually the encrypted would be used

Jaroslaw Kutylowski 10 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Reconstruction of watermark Idea (continued) look for the highest valued points check whether these points form a valid watermark –use equilateral triangles –certain number of triangles of specific edge length must be found to form a watermark Properties for the points actually in –there will be a large similarity between the watermarked image and the interference image there are points to check for each point operations are needed to compare the images key is needed for reconstruction

Jaroslaw Kutylowski 11 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Reconstruction of watermark Additional operations the reconstruction must be repeated for all rotations with degree –this yields resistance against rotations of the image the scale factor of the image must be determined –take a small part of the image –there should be at least one “white point” from in this part –check different scale factors and perform reconstruction of this image part for it –determine scale factor with largest peak value – this peak corresponds to a white point from the watermark –perform full reconstruction with this scale factor

Jaroslaw Kutylowski 12 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Experimental results Evaluation against StirMark 3 77 of 89 tests passed Cropping – all passed Removing rows/columns – only lighter one passed Flip – all passed Scaling – all passed Change aspect ratio – all passed Rotation with cropping – for rotation smaller than 30% passed Rotation with cropping and scalling – for rotation smaller than 30% passed Shearing – only simple ones passed Linear transformations – not passed StirMark – not passed Gaussian filtering – all passed Sharpening – all passed Median filtering – all passed LRAttack – all passed JPEG compression – all passed

Jaroslaw Kutylowski 13 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Conclusions Results robustness against attacks basing on filtering and local editions of image shown robustness against some linear transformations (rotating, scaling) shown Further work methods for detection of general linear transformations needed methods for detection of nonlinear transformations needed

Jaroslaw Kutylowski 14 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Thank you for your attention!