• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.305-314
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• 2017

Recently, user authentication through biometric traits such as fingerprint and iris raise more and more attention especially in mobile commerce and fin-tech fields. In particular, commercialized authentication methods using fingerprint recognition are widely utilized mainly because customers are more adopted and used to fingerprint recognition applications. In the meantime, the security issues caused by fingerprint falsification bring lots of attention. In this paper, we propose a new method to improve the performance of fake fingerprint detection using CNN(Convolutional Neural Network). It is common practice to increase the amount of learning data by using affine transformation or horizontal reflection to improve the detection rate in CNN characteristics that are influenced by learning data. However, in this paper we propose an effective data augmentation method based on the database difficulty level. The experimental results confirm the validity of proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.545-554
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• 2006

RFID could be applied in the various fields such as distribution beside, circulation, traffic and environment on information communication outside. So this can speak as point of ubiquitous computing's next generation technology. However, it is discussed problem of RFID security recently, so we must prepare thoroughly about RFID security for secure information. In this paper, we proposed a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. Our method which is improved linear discriminant analysis has reduced dimension of feature information which has large size of data. Therefore, we can sore face feature information in small memory field of RFID tag. Our propose d algorithm has shown 92% recognition rate in experimental results and can be applied to entrance control management system, digital identification card and others.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.242-246
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• 2010

In this paper, we propose a quality assessment method of biometrics for estimating an authentication result in an user authentication system. The proposed quality assessment method is designed to compute a quality score called CIMR (Confidence Interval Matching Ratio) as a result by small-sample analysis like T-test. We use the C/MR-based quality assessment method for testing how to well draw a distinction between various biometrics in a multimodal biometric system. We also test a predictability for authentication results of obtained biometrics using the mean $\bar{X}$ and the variance $s^2$ in T-test-based CIMR. As a result, we achieved the maximum 88% accuracy for estimation of user authentication results.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.187-192
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• 2009

In this paper, we proposed an algorithm for personal identification of dorsal surface pattern of hand vein pattern using graph theory. Using dense ranee data images of the hand vein pattern, we used matching algorithm within the frame work of graph theory for the determination of the desired correspondence. Through preprocessing, the captured images are more sharp, clear and thinning. After thinning, the images are normalized and make graph with node and edge set. This normalized graph can make adjacent matrix. Each adjacent matrix from individual vein pattern are different. From examining the performance of individual vein patterns, we can approach performances well kind biometric technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1783-1798
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• 2011

Recently, a cryptographic construct, called fuzzy vault, has been proposed for crypto-biometric systems, and some implementations for fingerprint have been reported to protect the stored fingerprint template by hiding the fingerprint features. In this paper, we implement the fuzzy fingerprint vault, combining fingerprint verification and fuzzy vault scheme to protect fingerprint templates. To implement the fuzzy fingerprint vault as a complete system, we have to consider several practical issues such as automatic fingerprint alignment, verification accuracy, execution time, error correcting code, etc. In addition, to protect the fuzzy fingerprint vault from the correlation attack, we propose an approach to insert chaffs in a structured way such that distinguishing the fingerprint minutiae and the chaff points obtained from two applications is computationally hard. Based on the experimental results, we confirm that the proposed approach provides higher security than inserting chaffs randomly without a significant degradation of the verification accuracy, and our implementation can be used for real applications.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.421-426
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• 2019

Nowadays, various type of technologies are used for user authentication, such as knowledge based(ID/PW, etc.) authentication, biometric based(Iris/fingerprint/vein recognition) authentication, ownership based(OTP, security card, etc.) authentication. ID/PW authentication technology, a knowledge based authentication, despite the advantages of low in implementation and maintenance costs and being familiar to users, there are disadvantages of vulnerable to hacking attacks, Other authentication methods solve the vulnerability in ID/PW authentication technology, but they have high initial investment cost and maintenance cost and troublesome problem of reissuance. In this paper, we proposed to improve security and convenience over existing ID/PW based authentication technology, and to secure user authentication without restriction on the devices used for authentication.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.51-59
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• 2008

The biometrics has been researched as a means for authenticating user's identity. Among the biometrics schemes for face recognition, the eigenvector-based schemes, which use eigenvector made from training data for transforming test data to abstracted data, are widely adopted. From those schemes, however, it is hard to expect cancelable feature, which is a general concept for security in the biometrics. In this paper, we point out the security problem that is the recovery of valuable face information from the abstracted face data and consider a possible attack scenario by showing our experiment results.

• Convergence Security Journal
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• v.20 no.4
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• pp.209-215
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• 2020

The environment of the Internet provides an efficient communication of the things which are connected. While internet and online service provide us many valuable benefits, online services offered and accessed remotely through internet also exposes us to many different types of security threats. Most security threats were just related to information leakage and the loss of authentication on client-server environment. In 2016, Ahmed et al. proposed an efficient lightweight remote user authentication protocol. However, Kang et al. show that it's scheme still unstable and inefficient. It cannot resist offline identity guessing attack and cannot provide session key confirmation property. Moreover, there is some risk of biometric information's recognition error. In this paper, we propose an improved scheme to overcome these security weaknesses by storing secret data in device. In addition, our proposed scheme should provide not only security, but also efficiency since we only use hash function and XOR operation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1065-1071
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• 2023

In this paper discuss with research developing an LSTM model for classifying the behavior of occupants within a residence. The multi-sensor consists of an IAQ (Indoor Air Quality) sensor that measures indoor air quality, a UWB radar that tracks occupancy detection and location, and a Piezo sensor to measure occupants' biometric information, and collects occupant behavior data such as going out, staying, cooking, cleaning, exercise, and sleep by constructed an experimental environment similar to the actual residential environment. After the data with removed outliers and missing, the LSTM model is used to calculate accuracy, sensitivity, specificity of the occupant behavior classification model, T1 score.