Secure cognitive recognition: brain-based biometric cryptosystems using EEG

Secure cognitive recognition: brain-based biometric cryptosystems using EEG

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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
  • Security evaluation
  • 14.3.4 Exploiting multiple biometric representations: information fusion
  • AR modelling
  • MFCC modelling
  • 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

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