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Ownership protection of shape datasets with geodesic distance preservation

Published: 25 March 2008 Publication History

Abstract

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.

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Cited By

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  • (2017)Advancements in GIS map copyright protection schemes - a critical reviewMultimedia Tools and Applications10.1007/s11042-016-3441-z76:10(12205-12231)Online publication date: 1-May-2017
  • (2015)Analysis of an EMST-based path for 3D meshesComputer-Aided Design10.1016/j.cad.2015.02.00564:C(22-32)Online publication date: 1-Jul-2015
  • (2010)Rights protection of trajectory datasets with nearest-neighbor preservationThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-010-0178-619:4(531-556)Online publication date: 1-Aug-2010

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cover image ACM Other conferences
EDBT '08: Proceedings of the 11th international conference on Extending database technology: Advances in database technology
March 2008
762 pages
ISBN:9781595939265
DOI:10.1145/1353343
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 March 2008

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View all
  • (2017)Advancements in GIS map copyright protection schemes - a critical reviewMultimedia Tools and Applications10.1007/s11042-016-3441-z76:10(12205-12231)Online publication date: 1-May-2017
  • (2015)Analysis of an EMST-based path for 3D meshesComputer-Aided Design10.1016/j.cad.2015.02.00564:C(22-32)Online publication date: 1-Jul-2015
  • (2010)Rights protection of trajectory datasets with nearest-neighbor preservationThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-010-0178-619:4(531-556)Online publication date: 1-Aug-2010

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