• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.1009-1015
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• 2017

Recently, the wide spread of IoT (Internet of Things) based technology enables the accumulation of big biometric data on livestock. The availability of big data allows the application of diverse machine learning based algorithm in the field of agriculture, which significantly enhances the productivity of farms. In this paper, we propose an abnormal livestock detection algorithm based on deep learning, which is the one of the most prominent machine learning algorithm. In our proposed scheme, the livestock are divided into two clusters which are normal and abnormal (disease) whose biometric data has different characteristics. Then a deep neural network is used to classify these two clusters based on the biometric data. By using our proposed scheme, the normal and abnormal livestock can be identified based on big biometric data, even though the detailed stochastic characteristics of biometric data are unknown, which is beneficial to prevent epidemic such as mouth-and-foot disease.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.779-790
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• 2022

Fuzzy extractor is a biometric encryption that generates keys from biometric data where input values are not always the same due to the noisy data, and performs authentication securely without exposing biometric information. However, if a user registers biometric data on multiple servers, various attacks on helper data which is a public information used to extract keys during the authentication process of the fuzzy extractor can expose the keys. Therefore many studies have been conducted on reusable fuzzy extractors that are secure to register biometric data of the same person on multiple servers. But as the key length increases, the studies presented so far have gradually increased the number of key recovery processes, making it inefficient and difficult to utilize in security systems. In this paper, we design an efficient and reusable fuzzy extractor based on LWE with the same or similar number of times of the authentication process even if the key length is increased, and show that the proposed algorithm is reusably-secure defined by Apon et al.[5].

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.2010-2026
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• 2013

The combination of biometrics and cryptography gains a lot of attention from both academic and industry community. The noisy biometric measurement makes traditional identity based cryptosystems unusable. Also the extraction of key from biometric information is difficult. In this paper, we propose an efficient biometric identity based signature scheme (Bio-IBS) that makes use of fuzzy extractor to generate the key from a biometric data of user. The component fuzzy extraction is based on error correction code. We also prove that the security of suggested scheme is reduced to computational Diffie-Hellman (CDH) assumption instead of other strong assumptions. Meanwhile, the comparison with existing schemes shows that efficiency of the system is enhanced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1911-1918
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• 2011

Internet banking, electronic financial services and internet telephony service can be available on smart phone recently. In this case, more robust authentication mechanisms should be provided for enhancing security on it. In this study, a facial biometric ID based one-time password generation mechanism is designed and implemented for enhancing user authentication on smart phone. After capturing a facial biometric data using camera module on smart phone, it is sent to server to generate one-time biometric ID. Finally one-time password will be generated by client module after receiving the one time biometric ID based challenge token from the server. Using proposed biometric ID based one-time password mechanism, it is possible for us to provide more secure user authentication service on smart phone for SIP protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.221-237
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• 2016

The wireless body area networks (WBANs) consist of wearable computing devices and can support various healthcare-related applications. There exist two crucial issues when WBANs are utilized for healthcare applications. One is the protection of the sensitive biometric data transmitted over the insecure wireless channels. The other is the design of effective medical management mechanisms. In this paper, a secure medical information management system is proposed and implemented on a TinyOS-based WBAN test bed to simultaneously address these two issues. In this system, the electronic medical record (EMR) is bound to the biometric data with a novel fragile zero-watermarking scheme based on the modified visual secret sharing (MVSS). In this manner, the EMR can be utilized not only for medical management but also for data integrity checking. Additionally, both the biometric data and the EMR are encrypted, and the EMR is further protected by the MVSS. Our analysis and experimental results demonstrate that the proposed system not only protects the confidentialities of both the biometric data and the EMR but also offers reliable patient information authentication, explicit healthcare operation verification and undeniable doctor liability identification for WBANs.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.107-113
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• 2016

In this paper, by managing the biometric data is changed with the passage of time, a systematic and scientifically propose a framework to increase the bio-vector generation efficiency of the smart health care. Increasing the development of human life as a medicine and has emerged smart health care according to this. Organic and efficient health management becomes possible to generate a vector when the biological domain to the wireless communication infrastructure based on the measurement of the health status and to take action in accordance with the change of the physical condition. In this paper, we propose a framework to create a bio-vector that contains information about the current state of health of the person. In the proposed framework, Bio vectors may be generated by collecting the biometric data such as blood pressure, pulse, body weight. Biometric data is the raw data from the bio-vector. The scope of the primary data can be set to active. As the collecting biometric data from multiple items of the bio-recognition vectors may increase. The resulting bio-vector is used as a measure to determine the current health of the person. Bio-vector generating the proposed framework, it can aid in the efficiency and systemic health of healthcare for the individual.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.83-90
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• 2010

Cancelable biometrics is a robust and secure biometric recognition method using revocable biometric template in order to prevent possible compromisation of the original biometric data. In this paper, we present a new cancelable bits extraction method for the facial data. We use our previous cancelable feature template for the bits extraction. The adopted cancelable template is generated from two different original face feature vectors extracted from two different appearance-based approaches. Each element of feature vectors is re-ordered, and the scrambled features are added. With the added feature, biometric bits string is extracted using helper data based method. In this technique, helper data is generated using statistical property of the added feature vector, which can be easily replaced with straightforward revocation. Because, the helper data only utilizes partial information of the added feature, our proposed method is a more secure method than our previous one. The proposed method utilizes the helper data to reduce feature variance within the same individual and increase the distinctiveness of bit strings of different individuals for good recognition performance. For a security evaluation of our proposed method, a scenario in which the system is compromised by an adversary is also considered. In our experiments, we analyze the proposed method with respect to performance and security using the extended YALEB face database

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1655-1662
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• 2007

Although the PKl-based user authentication solution has been widely used, the security of it can be deteriorated by a simple password. This is because a long and random private key may be protected by a short and easy-to-remember password. To handle this problem, many biometric-based user authentication solutions have been proposed. However, protecting biometric data is another research issue because the compromise of the biometric data will be permanent. In this paper, we present an implementation to improve the security of the typical PKI-based authentication by protecting the private key with a fingerprint. Compared to the unilateral authentication provided by the typical biometric-based authentication, the proposed solution can provide the mutual authentication. In addition to the increased security, this solution can alleviate the privacy issue of the fingerprint data by conglomerating the fingerprint data with the private key and storing the conglomerated data in a user-carry device such as a smart card. With a 32-bit ARM7-based smart card and a Pentium 4 PC, the proposed fingerprint-based PKI authentication can be executed within 1.3second.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1465-1472
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• 2005

There have been active researches utilizing Biometric informations such as fingerprints, face, iris and so on. but they have tended to use their own data formal and interfaces in processing Biometric informations, which causes the difficulties including sharing of Biometric informations and interoperability. To overcome such problems, we have studied XML applications such as XCBF and SOAP to process Biometric informations in the client-server environment. A method suitable to process and transfer Biometric informations in XML notation is proposed as a result.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.115-127
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• 2006

The purpose of this paper is evaluation of various normalization methods and fusion algorithms in addition to pattern classification algorithms for multi-biometric systems. Experiments are performed using various normalization functions, fusion algorithms and pattern classification algorithms based on Biometric Scores Set-Releasel(BSSR1) provided by NIST. The performance results are presented by Half Total Error Rate (WTER). This study gives base data for the study on performance enhancement of multiple-biometric system by showing performance results using single database and metrics.