Biometrics: a tool for information security

By Anil K. Jain, Arun A. Ross, Sharath Pankanti. 2006

1,245 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing

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Citations in the corpus

Biometric Template Security (2008, background): “Figure 3: Fish-bone model for categorizing biometric system vulnerabilities (adapted from [1]).”
A review of biometric technology along with trends and prospects (2014, methodology): “Fusion levels in multi-modal systems [5]: (a) Feature level (b) Score level (c) Decision level”
A survey on biometric cryptosystems and cancelable biometrics (2011, background): “Besides the fact that subjects share biometric traits rather reluctantly, the common use of biometrics is often considered as a threat to privacy [209].”
Biometric Antispoofing Methods: A Survey in Face Recognition (2014, background): “…and passwords, you are your own key'', researchers from many different fields such as image processing , computer vision or pattern recognition, have applied the newest techniques in each of these areas to improve the 1 Figures do not lie, but liars do figure. performance of biometric systems [4].”
Biometric Authentication: A Review (2009, methodology): “Now live finger print readers based on optical, thermal, silicon or ultrasonic principles [1, 2, 3, 4] are used for this purpose.”
CloudID: Trustworthy cloud-based and cross-enterprise biometric identification (2015, background): “Substitution of biometrics for passwords in authentication and identiﬁcation systems received attention in security systems (Jain, Ross, & Pankanti, 2006).”
On the vulnerability of face verification systems to hill-climbing attacks (2010, background): “This has resulted in the establishment of a new research and technology area known as biometric recognition, or simply biometrics [1].”
FlowSAN: Privacy-Enhancing Semi-Adversarial Networks to Confound Arbitrary Face-Based Gender Classifiers (2019, background): “The increasing use of face recognition in various applications has brought the issue of data privacy to the forefront [5]–[18].”
Biometrics Systems Under Spoofing Attack: An evaluation methodology and lessons learned (2015, background): “Each modality has its own strengths and weaknesses [1].”
Pattern Recognition Systems under Attack: Design Issues and Research Challenges (2014, methodology): “When online learning is used, the learning algorithm is periodically rerun on novel data during operation.”
Spoofing and countermeasures for speaker verification: A survey (2015, background): “Various distinctive and measurable physiological and behavioural traits have been investigated for biometric recognition (Jain et al., 2006).”
Understanding OSN-based facial disclosure against face authentication systems (2014, background): “OSNFD provides abundant exploitable resources affecting the applicability of face authentication as it compromises its conﬁdentiality, which is one of fundamental requirements for authentication [14, 18].”
Security evaluation of biometric authentication systems under real spoofing attacks (2012, background): “Such belief is based on the intuitive argument that, to evade a multimodal system, the attacker needs to spoof all the corresponding biometric traits simultaneously [18].”
An evaluation of indirect attacks and countermeasures in fingerprint verification systems (2011, methodology): “Biometric systems are becoming popular in our society, as they provide a convenient method for user authentication and access to secure environments (Jain et al., 2006).”
Biometric-rich gestures: a novel approach to authentication on multi-touch devices (2012, background): “However, users have been known to choose weak passwords [15].”
Face Recognition on Consumer Devices: Reflections on Replay Attacks (2015, background): “This authenticates the actual person and not merely the possession of objects or knowledge [4].”