AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Spherical Minimax Location Problem
Computational Optimization and Applications
Similarity Searching in Medical Image Databases
IEEE Transactions on Knowledge and Data Engineering
Fast and Effective Retrieval of Medical Tumor Shapes
IEEE Transactions on Knowledge and Data Engineering
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Rights Protection for Relational Data
IEEE Transactions on Knowledge and Data Engineering
Privacy Preserving Data Classification with Rotation Perturbation
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Rights Protection for Discrete Numeric Streams
IEEE Transactions on Knowledge and Data Engineering
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
The Applicability of the Perturbation Model-based Privacy Preserving Data Mining for Real-world Data
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Watermarking relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A Triangulation Method for the Sequential Mapping of Points from N-Space to Two-Space
IEEE Transactions on Computers
Privacy-Preserving SVM classification on vertically partitioned data
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Rights protection of trajectory datasets with nearest-neighbor preservation
The VLDB Journal — The International Journal on Very Large Data Bases
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Protection of one's intellectual property is a topic with important technological and legal facets. The significance of this issue is amplified nowadays due to the ease of data dissemination through the internet. Here, we provide technological mechanisms for establishing the ownership of a dataset consisting of multiple objects. The objects that we consider in this work are shapes (i.e., two dimensional contours), which abound in disciplines such as medicine, biology, anthropology and natural sciences. The protection of the dataset is achieved through means of embedding of an imperceptible ownership 'seal', that imparts only minute visual distortions. This seal needs to be embedded in the proper data space so that its removal or destruction is particularly difficult. Our technique is robust to many common transformations, such as data rotation, translation, scaling, noise addition and resampling. In addition to that, the proposed scheme also guarantees that important distances between the dataset shapes/objects are not distorted. We achieve this by preserving the geodesic distances between the dataset objects. Geodesic distances capture a significant part of the dataset structure, and their usefulness is recognized in many machine learning, visualization and clustering algorithms. Therefore, if a practitioner uses the protected dataset as input to a variety of mining, machine learning, or database operations, the output will be the same as on the original dataset. We illustrate and validate the applicability of our methods on image shapes extracted from anthropological and natural science data.