http://iet.metastore.ingenta.com
1887

Secure cognitive recognition: brain-based biometric cryptosystems using EEG

Secure cognitive recognition: brain-based biometric cryptosystems using EEG

For access to this article, please select a purchase option:

Buy chapter PDF
£10.00
(plus tax if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
User-Centric Privacy and Security in Biometrics — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Cognitive biometric recognition systems, based on the exploitation of nervous tissues' responses as identifiers, have recently attracted an always-growing interest from the scientific community, thanks to the several advantages they could offer with respect to traditional biometric approaches based on physical or behavioral characteristics, such as fingerprint, face, signature, and so forth. Biosignals are in fact much more robust against presentation attacks, being hard, if not impossible, to covertly capture and then replicate them. Liveness detection is also inherently provided. Nevertheless, their usage could expose several sensitive information regarding people's health and capability, making the system prone to function creep issues. With the aim of guaranteeing proper privacy and security to the users of the such systems, different general cryptosystem architectures for cognitive biometric traits are therefore presented in this chapter. Their effectiveness is evaluated by applying the proposed approaches to brain signals sensed through electroencephalography (EEG). A multi-session EEG dataset comprising recordings taken in three distinct occasions from each of 50 subjects is employed to perform the reported experimental test.

Chapter Contents:

  • Abstract
  • 14.1 Introduction
  • 14.2 EEG-based biometric recognition
  • 14.3 Proposed cognitive biometric cryptosystems
  • 14.3.1 Preprocessing
  • 14.3.2 Unprotected systems
  • 14.3.3 Protected system
  • 14.3.3.1 Security evaluation
  • 14.3.4 Exploiting multiple biometric representations: information fusion
  • 14.3.4.1 AR modelling
  • 14.3.4.2 MFCC modelling
  • 14.3.4.3 Fusion strategies
  • 14.4 Experimental tests
  • 14.4.1 Experimental setup
  • 14.4.2 Experimental results
  • 14.5 Conclusions
  • References

Inspec keywords: electroencephalography; biological tissues; cognition; data privacy; cryptography; medical signal processing

Other keywords: brain-based biometric cryptosystems; cryptosystem architectures; brain signals; security; multisession EEG dataset; cognitive biometric traits; privacy; electroencephalography; liveness detection; nervous tissues responses; presentation attacks; biosignals; cognitive biometric recognition systems; secure cognitive recognition

Subjects: Bioelectric signals; Biology and medical computing; Signal processing and detection; Electrical activity in neurophysiological processes; Electrodiagnostics and other electrical measurement techniques; Digital signal processing; Cryptography; Data security

Preview this chapter:
Zoom in
Zoomout

Secure cognitive recognition: brain-based biometric cryptosystems using EEG, Page 1 of 2

| /docserver/preview/fulltext/books/sc/pbse004e/PBSE004E_ch14-1.gif /docserver/preview/fulltext/books/sc/pbse004e/PBSE004E_ch14-2.gif

Related content

content/books/10.1049/pbse004e_ch14
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address