Binarized Multi-Factor Cognitive Detection of Bio-Modality Spoofing in Fog Based Medical Cyber-Physical System

Nishat I. Mowla, Inshil Doh, Kijoon Chae

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Bio-modalities are ideal for user authentication in Medical Cyber-Physical Systems. Various forms of bio-modalities, such as the face, iris, fingerprint, are commonly used for secure user authentication. Concurrently, various spoofing approaches have also been developed over time which can fail traditional bio-modality detection systems. Image synthesis with play-doh, gelatin, ecoflex etc. are some of the ways used in spoofing bio-identifiable property. Since the bio-modality detection sensors are small and resource constrained, heavy-weight detection mechanisms are not suitable for these sensors. Recently, Fog based architectures are proposed to support sensor management in the Medical Cyber-Physical Systems (MCPS). A thin software client running in these resource-constrained sensors can enable communication with fog nodes for better management and analysis. Therefore, we propose a fog-based security application to detect bio-modality spoofing in a Fog based MCPS. In this regard, we propose a machine learning based security algorithm run as an application at the fog node using a binarized multi-factor boosted ensemble learner algorithm coupled with feature selection. Our proposal is verified on real datasets provided by the Replay Attack, Warsaw and LiveDet 2015 Crossmatch benchmark for face, iris and fingerprint modality spoofing detection used for authentication in an MCPS. The experimental analysis shows that our approach achieves significant performance gain over the state-of-The-Art approaches.

Original languageEnglish
Title of host publication33rd International Conference on Information Networking, ICOIN 2019
PublisherIEEE Computer Society
Pages43-48
Number of pages6
ISBN (Electronic)9781538683507
DOIs
StatePublished - 17 May 2019
Event33rd International Conference on Information Networking, ICOIN 2019 - Kuala Lumpur, Malaysia
Duration: 9 Jan 201911 Jan 2019

Publication series

NameInternational Conference on Information Networking
Volume2019-January
ISSN (Print)1976-7684

Conference

Conference33rd International Conference on Information Networking, ICOIN 2019
Country/TerritoryMalaysia
CityKuala Lumpur
Period9/01/1911/01/19

Keywords

  • Bio-modality spoofing
  • Ensemble Learning
  • Feature selection
  • Fog computing
  • MCPS
  • Spoofing Detection

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