• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.5
• /
• pp.632-639
• /
• 2007

This paper presents a wavelet-based watermarking algorithm to securely hide biometric features such as face and fingerprint and effectively extract them with less distortion of the concealed data. To hide the biometric features, we proposed a determination method of insert location based on wavelet transform and adaptive weight method according to the image characteristics. The hidden features are effectively extracted by applying the inverse wavelet transform to the watermarked image. To show the effectiveness, we analyze the various performance such as PSNR and correlation of watermark features before and after applying watermarking. Also, we evaluate the effect of watermaking algorithm with respect to biometric system such as recognition rate. Recognition rate shows 98.67% for multimodal biometric systems consisted of face and fingerprint. From these, we confirm that the proposed method makes it possible to effectively hide and extract the biometric features without lowering recognition rate.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.4
• /
• pp.115-124
• /
• 2011

There has been significant research in security technology such as e-passport standards, as e-passports have been introduced internationally. E-passports combine the latest security technologies such as smart card, public key infrastructure, and biometric recognition, so that these technologies can prevent unauthorized copies and counterfeits. Biometric information stored in e-passports is the most sensitive personal information, and it is expected to bring the highest risk of damages in case of its forgery or duplication. The present e-passport standards cannot handle security features that verify whether its biometric information is copied or not. In this paper, we propose an e-passport security technology in which biometric watermarking is used to prevent the copy of biometric information in the e-passport. The proposed method, biometric watermarking, embeds the invisible date of acquisition into the original data during the e-passport issuing process so that the human visual system cannot perceive its invisibly watermarked information. Then the biometric sample, having its unauthorized copy, is retrieved at the moment of reading the e-passport from the issuing database. The previous e-passport security technology placed an emphasis on both access control readers and anti-cloning chip features, and it is expected that the proposed feature, copy protection of biometric information, will be demanded as the cases of biometric recognition to verify personal identity information has increased.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.1
• /
• pp.75-82
• /
• 2009

This paper propose a method to hide not only biometric features in the biometric image such as face and fingerprint for protecting them from unauthorized entity but also information of responsible person expressed as binary image which can be used to identify the responsibility of divulgence. For this, we investigate the recognition rates and bit error rates of extracted responsible person information watermark for the cases of using face and fingerprint images as cover images for fingerprint and face recognition which are the most popular biometric techniques. From these experiments, we confirm that the proposed method can be used for various application requiring to protect personal biometric information

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.2 s.314
• /
• pp.27-36
• /
• 2007

Changeable biometrics identify a person using transformed biometric data instead of original biometric data in order to enhance privacy and security in biometrics when biometric data is compromised. In this paper, a novel scheme which generates changeable face templates for statistical appearance-based face recognition is proposed. Two different original face feature vectors are extracted from two different appearance-based approaches, respectively, each original feature vector is normalized, and its elements are re-ordered. Finally a changeable face template is generated by weighted addition between two normalized and scrambled feature vectors. Since the two feature vectors are combined into one by a two to one mapping, the original two feature vectors are not easily recovered from the changeable face template even if the combining rule is known. Also, when we need to make new changeable face template for a person, we change the re-ordering rule for the person and make a new feature vector for the person. Therefore, the security and privacy in biometric system can be enhanced by using the proposed changeable face templates. In our experiments, we analyze the proposed method with respect to performance and security using an AR-face database.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.321-327
• /
• 2021

Mobile devices have recently developed to be an integral part of humans' daily lives because they meet business and personal needs. It is challenging to design a feasible and effective user authentication method for mobile devices because security issues and data privacy threats have significantly increased. Biometric approaches are more effective than traditional authentication methods. Therefore, this paper aims to analyze the existing biometric user authentication methods on mobile platforms, particularly those that use face recognition, to demonstrate the methods' feasibility and challenges. Next, this paper evaluates the methods according to seven characteristics: universality, uniqueness, permanence, collectability, performance, acceptability, and circumvention. Last, this paper suggests that solely using the method of biometric authentication is not enough to identify whether users are authentic based on biometric traits.

• Journal of Information Processing Systems
• /
• v.10 no.4
• /
• pp.555-567
• /
• 2014

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

• Journal of Korea Multimedia Society
• /
• v.20 no.2
• /
• pp.170-178
• /
• 2017

Biometric recognition is one of the major challenging topics which needs high performance of recognition accuracy. Most of existing methods rely on a single source of biometric to achieve recognition. The recognition accuracy in biometrics is affected by the variability of effects, including illumination and appearance variations. In this paper, we propose a new multimodal biometrics recognition using convolutional neural network. We focus on multimodal biometrics from face and periocular regions. Through experiments, we have demonstrated that facial multimodal biometrics features deep learning framework is helpful for achieving high recognition performance.

• Journal of Information Processing Systems
• /
• v.8 no.3
• /
• pp.483-494
• /
• 2012

Many recent events, such as terrorist attacks, exposed defects in most sophisticated security systems. Therefore, it is necessary to improve security data systems based on the body or behavioral characteristics, often called biometrics. Together with the growing interest in the development of human and computer interface and biometric identification, human face recognition has become an active research area. Face recognition appears to offer several advantages over other biometric methods. Nowadays, Principal Component Analysis (PCA) has been widely adopted for the face recognition algorithm. Yet still, PCA has limitations such as poor discriminatory power and large computational load. This paper proposes a novel algorithm for face recognition using a mid band frequency component of partial information which is used for PCA representation. Because the human face has even symmetry, half of a face is sufficient for face recognition. This partial information saves storage and computation time. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power. Furthermore, the proposed method reduces the computational load and storage significantly.

• Journal of Digital Convergence
• /
• v.12 no.1
• /
• pp.389-395
• /
• 2014

In a biometric signature scheme, a user's biometric key is used to sign the document. It also requires the user be authenticated with biometric recognition method, prior to signing the document. Because the biometric recognition is launched every time the signature session started, it is not suitable for electronic commerce applications such as shopping malls where large number of documents to sign are required. Therefore, to commercialize biometric based signature schemes, the new proxy signature scheme is needed to ease the burden of the signer. In the proxy signature scheme, the signer can delegate signing activities to trustful third parties. In this study, the biometric based signature delegation method is proposed. The proposed scheme is suitable for applications where a lot of signing are required. It is consisted of biometric key generation, PKI based mutual authentication, signature generation and verification protocols.

• Journal of KIISE:Software and Applications
• /
• v.34 no.4
• /
• pp.377-388
• /
• 2007

In this paper, we propose a multi-modal biometric system based on face, iris and fingerprint recognition system. To effectively aggregate two systems, we use statistical distribution models based on matching values for genuine and impostor, respectively. And then, We performed reveal fusion algorithms including weighted summation, Support Vector Machine(SVM), Fisher discriminant analysis, Bayesian classifier. From the various experiments, we found that the performance of multi-modal biometric system was influenced with the normalization methods and classifiers.