Cancelable Biometrics: a comprehensive survey
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Cancelable Biometrics: a comprehensive survey Manisha1 · Nitin Kumar1
© Springer Nature B.V. 2019
Abstract Biometric recognition is a challenging research field but suffers from privacy and security concerns. To address this concern, Cancelable Biometrics is suggested in literature in which a Biometric image of a sample is distorted or transformed in such a manner that it becomes difficult to obtain the original Biometric image from the distorted one. Another important characteristic of Cancelable Biometrics is that it can be reissued if compromised. In this research paper, we present a comprehensive survey of more than 120 techniques suggested by various researchers from time to time for Cancelable Biometrics and a novel taxonomy for the same is developed. Further, various performance measures used in Cancelable Biometrics are reviewed and their mathematical formulations are given. Cancelable Biometrics also suffer from various security attacks as given in literature. A review of these security attacks is carried out. We have also performed a review of databases used in literature for nine different Cancelable Biometrics viz. Face, Iris, Speech, Fingerprint, Signature, Palmprint, ECG, Palmvein and Fingervein. Lastly, we have also given future research directions in this field. This study shall be useful for the researchers and practitioners working in this fascinating research area. Keywords Taxonomy · Performance · Databases · Survey · Attacks
1 Introduction Biometric is derived from two Greek words viz. Bio means life and Metric means to measure. There are several traits or characteristics (Jain et al. 2004) such as Finger, Face, Ear, Iris, Gait, Palm, Hand Geometry etc., which are most widely used Biometrics. Biometric technology have been widely used in several applications (Jain et al. 2007) such as access control, border immigration control, corpse identification, surveillance, forensic sectors, human computer interaction, behavior analysis etc. Biometrics are divided into two categories i.e. (i) Physical and (ii) Behavioral. Physical Biometrics are based on measuring the physical characteristics
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Nitin Kumar [email protected] Manisha [email protected]
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Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, Srinagar, India
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Manisha, N. Kumar
Biometric Sensor
Feature Extraction
Matcher
Stored Features
Database
Stored Features
Database
Match / Non-Match
(a)
Biometric Sensor
Feature Extraction
Matcher
Identity
(b) Fig. 1 Biometric recognition process: a verification b identification
of a person such as Face, Iris, Finger etc. while Behavioral Biometrics are based on measuring behavioral traits of a person such as Gait, Hand Gesture, Speech etc. Biometric recognition refers to the activity of Identifying and/or Verifying the identity of a person. Biometric recognition usually work in two scenarios: (i) Verification and (ii) Identification. In Verification, the claimed identity by the user is matched with the already stored pattern/featu
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