Abstract

Recently, Physically Unclonable Functions (PUFs) received considerable attention in order to developing security mechanisms for applications such as Internet of Things (IoT) by exploiting the natural randomness in device-specific characteristics. This approach complements and improves the conventional security algorithms that are vulnerable to security attacks due to recent advances in computational technology and fully automated hacking systems. In this project, we propose a new authentication mechanism based on a specific implementation of PUF using metallic dendrites. Dendrites are nanomaterial devices that contain unique, complex and unclonable patterns (similar to human DNAs). We propose a method to process dendrite images. The proposed framework comprises several steps including denoising, skeletonizing, pruning and feature points extraction. The feature points are represented in terms of a tree-based weighted algorithm that converts the authentication problem to a graph matching problem. The test object is compared against a database of valid patterns using a novel algorithm to perform user identification and authentication. The proposed method demonstrates a high level of accuracy and a low computational complexity that grows linearly with the number of extracted points and database size. It also significantly reduces the required in-network storage capacity and communication rates to maintain database of users in large-scale networks.

Original languageEnglish (US)
Title of host publicationProceedings of Computing Conference 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages863-870
Number of pages8
Volume2018-January
ISBN (Electronic)9781509054435
DOIs
StatePublished - Jan 8 2018
Event2017 SAI Computing Conference 2017 - London, United Kingdom
Duration: Jul 18 2017Jul 20 2017

Other

Other2017 SAI Computing Conference 2017
CountryUnited Kingdom
CityLondon
Period7/18/177/20/17

Fingerprint

Authentication
Nanostructured materials
Computational complexity
DNA
Communication
Hardware security
Internet of things

Keywords

  • Authentication
  • Graph-Matching
  • Image-Processing
  • Information-Security

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Software
  • Artificial Intelligence

Cite this

Valehi, A., Razi, A., Cambou, B., Yu, W., & Kozicki, M. (2018). A graph matching algorithm for user authentication in data networks using image-based physical unclonable functions. In Proceedings of Computing Conference 2017 (Vol. 2018-January, pp. 863-870). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAI.2017.8252196

A graph matching algorithm for user authentication in data networks using image-based physical unclonable functions. / Valehi, Ali; Razi, Abolfazl; Cambou, Bertrand; Yu, Weijie; Kozicki, Michael.

Proceedings of Computing Conference 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 863-870.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Valehi, A, Razi, A, Cambou, B, Yu, W & Kozicki, M 2018, A graph matching algorithm for user authentication in data networks using image-based physical unclonable functions. in Proceedings of Computing Conference 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 863-870, 2017 SAI Computing Conference 2017, London, United Kingdom, 7/18/17. https://doi.org/10.1109/SAI.2017.8252196
Valehi A, Razi A, Cambou B, Yu W, Kozicki M. A graph matching algorithm for user authentication in data networks using image-based physical unclonable functions. In Proceedings of Computing Conference 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 863-870 https://doi.org/10.1109/SAI.2017.8252196
Valehi, Ali ; Razi, Abolfazl ; Cambou, Bertrand ; Yu, Weijie ; Kozicki, Michael. / A graph matching algorithm for user authentication in data networks using image-based physical unclonable functions. Proceedings of Computing Conference 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 863-870
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