Biomolecule-Driven Two-Factor Authentication Strategy for Access Control of Molecular Devices.

DNA nanotechnology DNA strand displacement molecular devices nicking enzyme nucleic acids

Journal

ACS nano
ISSN: 1936-086X
Titre abrégé: ACS Nano
Pays: United States
ID NLM: 101313589

Informations de publication

Date de publication:
26 09 2023
Historique:
medline: 27 9 2023
pubmed: 13 9 2023
entrez: 13 9 2023
Statut: ppublish

Résumé

The rise of DNA nanotechnology is promoting the development of molecular security devices and marking an essential change in information security technology, to one that can resist the threats resulting from the increase in computing power, brute force attempts, and quantum computing. However, developing a secure and reliable access control strategy to guarantee the confidentiality of molecular security devices is still a challenge. Here, a biomolecule-driven two-factor authentication strategy for access control of molecular devices is developed. Importantly, the two-factor is realized by applying the specificity and nicking properties of the nicking enzyme and the programmable design of the DNA sequence, endowing it with the characteristic of a one-time password. To demonstrate the feasibility of this strategy, an access control module is designed and integrated to further construct a role-based molecular access control device. By constructing a command library composed of three commands (Ca, Cb, Ca and Cb), the authorized access of three roles in the molecular device is realized, in which the command Ca corresponds to the authorization of role A, Cb corresponds to the authorization of role B, and Ca and Cb corresponds to the authorization of role C. In this way, when users access the device, they not only need the correct factor but also need to apply for role authorization in advance to obtain secret information. This strategy provides a highly robust method for the research on access control of molecular devices and lays the foundation for research on the next generation of information security.

Identifiants

pubmed: 37703447
doi: 10.1021/acsnano.3c05070
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

18178-18189

Auteurs

Xiaokang Zhang (X)

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Yuan Liu (Y)

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Bin Wang (B)

Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian 116622, China.

Shihua Zhou (S)

Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian 116622, China.

Peijun Shi (P)

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Ben Cao (B)

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Yanfen Zheng (Y)

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Qiang Zhang (Q)

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Nikola Kirilov Kasabov (N)

Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1010, New Zealand.
Intelligent Systems Research Center, Ulster University, Londonderry BT48, United Kingdom.
IICT, Bulgarian Academy of Sciences, Sofia 1040, Bulgaria.

Articles similaires

Comparative assessment of physics-based in silico methods to calculate relative solubilities.

Adiran Garaizar Suarez, Andreas H Göller, Michael E Beck et al.
1.00
Solvents Solubility Quantum Theory Molecular Dynamics Simulation Thermodynamics
Humans Brain Neuroimaging Quantum Theory Neurosciences
Proteins Quantum Theory Databases, Protein Protein Folding

Classifications MeSH