• The Journal of the Acoustical Society of Korea
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• v.23 no.8
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• pp.597-601
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• 2004

This paper introduces a pre-rejection technique for wireless channel distorted speech with application to automatic speech recognition (ASR) Based on analysis of distorted speech signals over a wireless communication channel. we propose a method to reject the channel distorted speech with a small computational load. From a number of simulation results. we can discover that tile pre-rejection algorithm enhances the robustness of speech recognition operation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.71-79
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• 2009

Currently much research is being done on host based intrusion detection using system calls which is a portion of kernel based data. Sequence based and frequency based preprocessing methods are mostly used in research for intrusion detection using system calls. Due to the large amount of data and system call types, it requires a significant amount of preprocessing time. Therefore, it is difficult to implement real-time intrusion detection systems. Despite this disadvantage, the frequency based method which requires a relatively small amount of preprocessing time is usually used. This paper proposes an effective method for detecting denial of service attacks using the frequency based method. Principal Component Analysis(PCA) will be used to select the principle system calls and a bayesian network will be composed and the bayesian classifier will be used for the classification.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.273-276
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• 2005

본 논문은 고유얼굴 방법을 이용한 얼굴인식 시스템의 성능을 분석하였다. 제안한 고유얼굴을 이용한 얼굴인식 방법은 훈련집합의 얼굴 이미지 사이의 중요한 변화를 가지고 있는 특징공간으로 투영시키면서 이루어진다. 중요한 특징들은 얼굴집합의 고유벡터(주성분)들이기 때문에 고유얼굴이라 한다. 특징 공간으로의 투영은 고유얼굴의 가중치의 합으로 입력얼굴을 기술할 수 있으며, 입력 얼굴의 인식은 훈련집합의 가중치와 입력 영상의 가중치를 비교하면서 이루어진다. 본 논문에서는 제안된 방법의 검증을 위해서 Harvard 데이터베이스를 이용하였으며, 시스템의 성능 분석을 위하여 조명에 대한 인식성능의 변화, 사용한 고유얼굴의 수에 대한 인식률의 변화, 전처리를 통하여 얻을 수 있는 인식률의 변화, 인식 거부 곡선을 통하여 시스템의 적용 가능성에 대한 실험을 수행하여 분석한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.400-405
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• 2005

This paper analyzes the performance of a face recognition algorithm using the eigenfaces method. In the absence of robust personal recognition schemes, a biometric recognition system has essentially researched to improve their shortcomings. A face recognition system in biometries is widely researched in the field of computer vision and pattern recognition, since it is possible to comprehend intuitively our faces. The proposed system projects facial images onto a feature space that effectively expresses the significant variations among known facial images. The significant features are known as 'eigenfaces', because they are the eigenvectors(principal components) of the set of faces. The projection operation characterizes an individual face by a weighted sum of the eigenface features, and to recognize a particular face it is necessary only to compare these weights to those of known individuals. In order to analyze the performance of the system, we develop a face recognition system by using Harvard database in Harvard Robotics Laboratory. We present the recognition rate according to variations on the lighting condition, numbers of the employed eigenfaces, and existence of a pre-processing step. Finally, we construct a rejection curve in order to investigate the practicability of the recognition method using the eigenfaces.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.53-60
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• 2008

Fingerprint verification method based on minutiae has been widely used for its speed and size stemming from utilizing only a few data, but it is vulnerable to some errors caused by the false minutiae extractions. A number of suggestions have been made to correct these problems. However, because it is very difficult to avoid all the external factors, such as noises that occur when fingerprints are collected, and all the internal factors that occur during the process of them, there is a limit in minimizing errors by improving the whole process. On the other hand, a fingerprint verification method based on images yields fewer errors because it makes direct comparison between images not using minutiae. Image-based fingerprint verification method has its limitations in aligning images with accuracy. Therefore, this paper proposes a new methodology to improve the performance utilizing both image-based and minutiae-based verification methods effectively. As the result of experimenting with both images and minutiae, the false accept rate and the false reject rate have been improved from 2.7% to 0.8% and from 6.5% to 5.5%, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.215-222
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• 2005

In this paper, we propose a fingerprint verification algorithm for the embedded system based on the minutia extracted using the image quality, the minutia structure, and the Sequency and the orientation of ridges. After the pre- and the post-processing, the true minutia are selected, thus it shows high reliability in the fingerprint verification. In matching process, we consider the errors caused by shift, rotation, and pressure when acquiring the fingerprint image and reduce the matching time by applying a local matching instead of a full matching to select the reference pair. The proposed algorithm has been designed and verified in Arm920T environment and various techniques for the realtime process have been applied. Time taken from the fingerprint registration through out the matching is 0.541 second that is relevant for the realtime applications. The FRR (False Reject Rate) and FAR (False Accept Rate) show 0.079 and 0.00005 respectively.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.33-40
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• 2007

In this paper, low-rate TCP attack as one of shrew attacks is considered and the scaling based dynamic time warping (S-DTW) algorithm is introduced. The low-rate TCP attack can not be detected by the detection method for the previous flooding DoS/DDoS (Denial of Service/Distirbuted Denial of Service) attacks due to its low average traffic rate. It, however, is a periodic short burst that exploits the homogeneity of the minimum retransmission timeout (RTO) of TCP flows and then some pattern matching mechanisms have been proposed to detect it among legitimate input flows. A DTW mechanism as one of detection approaches has proposed to detect attack input stream consisting of many legitimate or attack flows, and shown a depending method as well. This approach, however, has a problem that legitimate input stream may be caught as an attack one. In addition, it is difficult to decide a threshold for separation between the legitimate and the malicious. Thus, the causes of this problem are analyzed through simulation and the scaling by maximum auto-correlation value is executed before computing the DTW. We also discuss the results on applying various scaling approaches and using standard deviation of input streams monitored.

• Journal of Ginseng Research
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• v.33 no.4
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• pp.343-348
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• 2009

This study was conducted to produce a new red ginseng by steaming ginseng using a new pre-treatment method, so as to develop ginseng products with improved flavor and thereby expand ginseng's consumer base. The color parameters (Hunter value), free sugar contents, and ginsenoside contents of the powder from the dried red ginseng, and the sensory test of the semi-dried red ginseng and the decoction from the dried red ginseng, were measured to investigate the effect of acid (ascorbic acid or citric acid) impregnation pre-treatment on red ginseng. The powder from the acid-pretreated red ginseng became lighter and more yellow than the red ginseng that was not pre-treated, but the redness (avalue) of the powder from the acid-pre-treated red ginseng increased. The ginsenoside contents of $Rg_2+Rh_1$ and $Rg_3$ increased with the acid treatment. There was a significant difference in the color and sweetness of the semi-dried acidtreated and non-treated red ginsengs in the sensory test. As the results of the sensory test were expressed in the hedonic scale, however, there were significant differences in the degrees of bitterness, astringency, sourness, odor, and color of the red ginseng decollation. Especially, the acid-treated red ginseng extract tasted less bitter, which shows the potential of new red ginseng products with improved ginseng flavor.