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Emerging trends in Biometric Authentication
Christophe Rosenberger
GREYC Laboratory – France
ENSICAEN – University of Caen - CNRS
SHPCS’09
SHPCS’09
Authentication
Trends in biometric authentication
Achievements
Conclusion & perspectives
PLAN
SHPCS’09
Authentication
Definition: Authentication
Process whose objective is to guarantee the identity of a user or a
service given a set level of confidence.
User Authentication
Definition: Authentication factors
An authentication factor is an authenticator element:
what we know (password),
what we own (smartcard),
What we are or how we behave (biometrics).
SHPCS’09
Biometric modalities :
Biological analysis:
Odour, blood, DNA…
Behavioural analysis:
Keystroke dynamics, voice, gait, signature dynamics...
Morphological analysis:
Fingerprint, iris, palmprint, finger veins, face, ear…
Authentication
SHPCS’09
Properties: A biometric information must respect the following properties:
Universality: All individuals can be characterized by this
information ;
Uniqueness: The biometric information must be as dissimilar
as possible for two different individuals ;
Permanency: It must subsist during all individual’s life ;
Collectability: The biometric information must be easily
computed ;
Acceptability: Users must be ready to give this information.
Authentication
SHPCS’09
Enrolment
Individual’s checkin in the biometric system
Storage
Unique login
Biometric data
Sensor
+
System
Association
Biometric reference
Authentication
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Verification
Comparison between the capture and the
reference
login
biometric data
Sensor
+
System
Comparison
Result
Reference
Authentication
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Decision criterion
Similarity
Repartition
impostors genuine
Threshold
True
rejected Wrong
accepted
Low threshold : no problem for genuine
users but impostors might be authenticated
High threshold: no impostor
but genuine will be disturbed
Authentication
SHPCS’09
Performance evaluation
EER
FRR
FAR
FAR : False Acceptation Rate
FRR : False Rejection Rate
EER : Equal Error Rate
ROC curve: FAR vs FRR
Authentication
SHPCS’09
Authentication
Trends in biometric authentication
Achievements
Conclusion & perspectives
PLAN
SHPCS’09
Biometric technology could be more deployed for logical and
physical access control applications.
Needs:
High performance biometric systems ;
Embedded device
Low memory
Quick verification
Correctness
Trends in Biometric Authentication
SHPCS’09
Definition of unconstrained biometric systems ;
One capture enrolment systems
Easiness of use
Evaluation of biometric systems ;
Performance, acceptability, security
Definition of privacy preserving systems…
No storage of the biometric reference
Trends in Biometric Authentication
SHPCS’09
Authentication
Trends in biometric authentication
Achievements
Conclusion & perspectives
PLAN
SHPCS’09
Achievements
Facial Authentication
Enrolment:
only one image unconstrained acquisition (face detection)
extraction of local face characteristics
SHPCS’09
Verification :
C. Rosenberger, L. Brun "Similarity-Based Matching for Face Authentication", IEEE
International Conference on Pattern Recognition (ICPR), 2008.
Achievements
SHPCS’09
Results
Faces94 benchmark:
152 individuals,
20 images per individual.
EER = 0.14%
AR benchmark:
120 individuals: 65 men, 55 women,
26 images per individual.
EER = 9%
Achievements
SHPCS’09
Palm veins authentication
Enrolment with a single image
EER = 0% on a benchmark composed of 24 individuals
P.-O. Ladoux, C. Rosenberger, B. Dorizzi, "Hand Vein Verification System based on SIFT
matching", The 3rd IAPR/IEEE International Conference on Biometrics (ICB), 2009.
Achievements
SHPCS’09
Keystroke dynamics authentication
Use of release, press and inter keys times during the typing of a
password. 5 captures for the enrolment
EER = 6% on a database of 100 individuals
R. Giot, M. El-Abed, C. Rosenberger, "Keystroke Dynamics Authentication For
Collaborative Systems", The IEEE International Symposium on Collaborative
Technologies and Systems (CTS), 2009.
Achievements
SHPCS’09
4 captures of
the same
password
Achievements
SHPCS’09
Evaluation of biometric systems
Analysis the perception of users
F. Cherifi, B. Hemery, R. Giot, M. Pasquet, C. Rosenberger, "Performance Evaluation Of
Behavioural Biometric Systems", Book on Behavioural Biometrics for Human
Identification: Intelligent Applications, 21 pages, 2009.
Achievements
SHPCS’09
Biohashing
Storage of a
biocode computed given a random
number and a
biometric template
R. Belguechi, C. Rosenberger, "Study on the Convergence of FingerHashing and a
Secured Biometric System", Proceedings of the International conference CIIA, 2009.
Achievements
SHPCS’09
Authentication
Trends in biometric authentication
Achievements
Conclusion & perspectives
PLAN
SHPCS’09
Conclusion
Biometrics
Benefit:
Close relationship between the client and its authenticator
drawbacks:
performance (EER>0%)
acceptability of users
Perspectives:
increase the computing performance
improve algorithms (performance, robustness…)
respect the privacy of users
