A Dynamic Sliding Window Encoding for Secured DNA Data Storage Compliant With Biological and Indexing Constraints
In this paper, we propose a novel dynamic sliding window encoding for storing encrypted data in a DNA form taking into account biological constraints (G-C content and homopolymers) and prohibited nucleotide motifs used for data indexing. Its originality is twofold. First, it stands on a new dynamic encoding (DE) which takes advantage of variable length DNA codewords to encode binary data and to avoid homopolymers longer than N bases. Second, DE is combined with a sliding window strategy to detect whether a prohibited motif is about to appear. In this case, our proposal will add a non-coding base to the sequence to prevent the encoding of this motif. Unlike existing schemes, its scaling for high values of N and of prohibited motifs is extremely simple. It is furthermore independent of the cryptosystem. We provide the theoretical information rate of our proposal for a given number of prohibited motifs and a maximum homopolymer length. In general, it offers much higher performances, particularly in terms of information rate, than existing schemes while controlling G-C content with an extremely high probability. Moreover, experiments conducted with a recent DNA storage chain simulator show that our proposal does not require more copies than other encoding strategies for the correct reading of DNA sequences.
Authors
- Sahar Haddad (ORCID: https://orcid.org/0000-0001-5974-1266)
- Gouenou Coatrieux (ORCID: https://orcid.org/0000-0002-5643-0224)
- Reda Bellafqira (ORCID: https://orcid.org/0000-0002-1131-4115)
- Chloé Berton (ORCID: https://orcid.org/0000-0001-8792-8634)
- Dominique Lavenier
- Hélène Gasnier
Institutions
- Institut national de recherche en sciences et technologies du numérique (FR)
- Inserm (FR)
- Institut de Recherche en Informatique et Systèmes Aléatoires (FR)
- Anton Proksch Institut (AT)
- IMT Atlantique (FR)
- Laboratoire de Traitement de l'Information Médicale (FR)
- Université de Rennes (FR)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3560387
- Primary Topic
- DNA and Biological Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agence Nationale de la Recherche