949 research outputs found
A New Biometric Template Protection using Random Orthonormal Projection and Fuzzy Commitment
Biometric template protection is one of most essential parts in putting a
biometric-based authentication system into practice. There have been many
researches proposing different solutions to secure biometric templates of
users. They can be categorized into two approaches: feature transformation and
biometric cryptosystem. However, no one single template protection approach can
satisfy all the requirements of a secure biometric-based authentication system.
In this work, we will propose a novel hybrid biometric template protection
which takes benefits of both approaches while preventing their limitations. The
experiments demonstrate that the performance of the system can be maintained
with the support of a new random orthonormal project technique, which reduces
the computational complexity while preserving the accuracy. Meanwhile, the
security of biometric templates is guaranteed by employing fuzzy commitment
protocol.Comment: 11 pages, 6 figures, accepted for IMCOM 201
Security and accuracy of fingerprint-based biometrics: A review
Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper
Security and accuracy of fingerprint-based biometrics: A review
Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper
State of the Art in Biometric Key Binding and Key Generation Schemes
Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems
DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution
Recent research has demonstrated the vulnerability of fingerprint recognition
systems to dictionary attacks based on MasterPrints. MasterPrints are real or
synthetic fingerprints that can fortuitously match with a large number of
fingerprints thereby undermining the security afforded by fingerprint systems.
Previous work by Roy et al. generated synthetic MasterPrints at the
feature-level. In this work we generate complete image-level MasterPrints known
as DeepMasterPrints, whose attack accuracy is found to be much superior than
that of previous methods. The proposed method, referred to as Latent Variable
Evolution, is based on training a Generative Adversarial Network on a set of
real fingerprint images. Stochastic search in the form of the Covariance Matrix
Adaptation Evolution Strategy is then used to search for latent input variables
to the generator network that can maximize the number of impostor matches as
assessed by a fingerprint recognizer. Experiments convey the efficacy of the
proposed method in generating DeepMasterPrints. The underlying method is likely
to have broad applications in fingerprint security as well as fingerprint
synthesis.Comment: 8 pages; added new verification systems and diagrams. Accepted to
conference Biometrics: Theory, Applications, and Systems 201
A New Hybrid Embedding Method in Iris Biometric System
The challenging part in achieving high security biometrics data is viewed from the engineering perspective which includes security, accuracy, speeds and application size. The objective of this paper is to increase the accuracy through an embedding technique. A combination of modified pixel value differencing and wavelet decomposition techniques were used in this study. The pixels were scanned in a new direction embedded with the wavelet difference matrix. The system is developed using both eyes and each eye is enrolled with 10 snaps. The embedding process creates the embedded iris feature and the reverse process of embedding is known as de-embedding. Two thousands iris from CASIA database are used. The application is developed using MATLAB and executed for 5-20 iterations. The new hybrid system shows better performance in accuracy in terms of False Acceptance Rate (FAR), embedding capacity and Peak Signal to Noise Ratio (PSNR) values as benchmarked with the existing method. The finding shows that the output of the embedding capacity is 743801 and 41.10dB of PSNR. The good PSNR value is between 40-50 dB. The implication of this study contributes to a higher accuracy in iris biometric security. Future work should focus on the genetic algorithm to recognize human iris in biometric system
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