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Gene Tagging and the Data Hiding Rate
Author(s)
Date Issued
2012-06-28
Date Available
2012-10-04T15:39:15Z
Abstract
We analyze the maximum number of ways in which one can intrinsically tag
a very particular kind of digital asset: a gene, which is just a DNA sequence that encodes
a protein. We consider gene tagging under the most relevant biological constraints:
protein encoding preservation with and without codon count preservation. We show
that our finite and deterministic combinatorial results are asymptotically—as the length
of the gene increases— particular cases of the stochastic Gel’fand and Pinsker capacity
formula for communications with side information at the encoder, which lies at the
foundations of data hiding theory. This is because gene tagging is a particular case of
DNA watermarking.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
The Institution of Engineering and Technology
Copyright (Published Version)
2012, The Institution of Engineering and Technology
Subject – LCSH
Genes
DNA
Data encryption (Computer science)
Digital watermarking
Combinatorial analysis
Language
English
Status of Item
Peer reviewed
Conference Details
23nd IET Irish Signals and Systems Conference, Maynooth, Ireland, 28-29th June, 2012
This item is made available under a Creative Commons License
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