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Cited by 980

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Collusion-secure fingerprinting for digital data

Boneh, D., Shaw, J.·1998·IEEE Transactions on Information Theory

Abstract

This paper discusses methods for assigning code-words for the purpose of fingerprinting digital data, e.g., software, documents, music, and video. Fingerprinting consists of uniquely marking and registering each copy of the data. This marking allows a distributor to detect any unauthorized copy and trace it back to the user. This threat of detection will deter users from releasing unauthorized copies. A problem arises when users collude: for digital data, two different fingerprinted objects can be compared and the differences between them detected. Hence, a set of users can collude to detect the location of the fingerprint. They can then alter the fingerprint to mask their identities. We present a general fingerprinting solution which is secure in the context of collusion. In addition, we discuss methods for distributing fingerprinted data.

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Metadata

Authors
Boneh, D., & Shaw, J.
Venue
IEEE Transactions on Information Theory
Published
1998
Volume
44
Issue
5
Pages
1897-1905
ISSN
0018-9448 (ISSN-L)
OpenAlex
W2134195444
Cited by
980
References
0
FWCI
23.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Collusion-secure fingerprinting for digital data. https://app.cochat.ai/papers/10.1109/18.705568
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Boneh, D., & Shaw, J. (1998). Collusion-secure fingerprinting for digital data. IEEE Transactions on Information Theory. https://doi.org/10.1109/18.705568

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.