• Annual Conference of KIPS
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• 2004.05a
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• pp.1083-1086
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• 2004

Switched Network는 Shared Network 에 비해서 스니핑에 안전하다. 하지만 비교우위일뿐 절대적으로 스니핑에 안전한 것은 아니다. 이미 Switched Network 상에서 스니핑을 할 수 있는 공격툴들이 많이 소개되어 있다. 본 논문에서는 Switched Network 상에서 ARP(Address Resolution Protocol) 스푸핑을 통한 ARP 캐시 오염을 통하여 스니핑이 가능한 시나리오를 기술한다. 이러한 시나리오를 탐지하기 위한 기존의 방법은 DHCP와 같은 동적인 환경이 포함된 경우 False Positive 를 자주 발생시키기 때문에 문제가 된다. 여기에서는 이러한 False Positive를 줄인 탐지 방법을 제시하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.649-651
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• 2021

In recent years, O2O services for real estate sales are widely distributed in web platforms and apps. This allows sellers, buyers, and real estate brokers to quickly and conveniently conduct real estate sales and charter contracts. However, in the O2O-based real estate sales information system, it wastes time and money for real estate buyers due to the posting of fake information, partial correction of the sales information, and intentional non-posting of the sales information. Therefore, we propose a method of detecting the false or not of real estate property information that can occur on the web platform, and design and implement a proposal system for this. To this end, we propose a method of detecting personal identity and property information based on DID, a distributed identity authentication protocol. The false real estate sales information detection system proposed by us can determine the existence of real estate sales information, partially correct the false sales information, or prove whether or not intentionally unpublished in three steps.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.86-91
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• 1999

This paper presents the text-prompt method to overcome the weakness of text-dependent and text-independent speaker recognition. Enhanced dynamic time warping for speaker recognition algorithm is applied. For the real-time processing, we use a simple algorithm for end-point detection without increasing computational complexity. The test shows that the weighted-cepstrum is most proper for speaker recognition among various speech parameters. As the experimental results of the proposed algorithm for three prompt words, the speaker identification error rate is 0.02%, and when the threshold is set properly, false rejection rate is 1.89%, false acceptance rate is 0.77% and verification total error rate is 0.97% for speaker verification.

• Bulletin of the Korean Mathematical Society
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• v.48 no.3
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• pp.523-537
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• 2011

A receiver operating characteristic (ROC) curve plots the true positive rate of a classier against its false positive rate, both of which are accuracy measures of the classier. The ROC curve has several interesting geometrical properties, including concavity which is a necessary condition for a classier to be optimal. In this paper, we study the nonparametric maximum likelihood estimator (NPMLE) of a concave ROC curve and its modification to reduce bias. We characterize the NPMLE as a solution to a geometric programming, a special type of a mathematical optimization problem. We find that the NPMLE is close to the convex hull of the empirical ROC curve and, thus, has smaller variance but positive bias at a given false positive rate. To reduce the bias, we propose a modification of the NPMLE which minimizes the $L_1$ distance from the empirical ROC curve. We numerically compare the finite sample performance of three estimators, the empirical ROC curve, the NMPLE, and the modified NPMLE. Finally, we apply the estimators to estimating the optimal ROC curve of the variance-threshold classier to segment a low depth of field image and to finding a diagnostic tool with multiple tests for detection of hemophilia A carrier.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.235-242
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• 2004

In this paper, we proposed the algorithm for detection of microtalcification by automatic threshold decision based on region growing method. The region for optimal threshold is grown from local maximum pixel by increasing repeatedly threshold in microralcification candidate region. Then, the optimal threshold is automatically decided at the maximum value of the contrast and edge sharpness in this region. Microcalcifications could be efficiently detected as satisfied result that true positive ratio is 81.5% and average false positive numbers are 1.1 about total 299 microcalcifirations in real image. In a result, we showed that this algorithm can be used to aid diagnostic-radiologist for the diagnosis of the early phase of breast cancer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.1971-1977
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• 2001

Multipath Rayleigh fading channels for mobile radio transmission can be represented by the linear filter model, and depending on the delay path characteristics, only a selected number of taps may have significance in the receiver structure design. By using tap-selective equalization, reduction in both processing complexity and power consumption can be obtained. In this paper, we present an optimal tap selection method for a given channel model, and demonstrate the performance improvement over an existing method. We show the method performs the CFAR (Constant False Alarm Rate) detection when the noise power information is available, and derive exact expressions of the error probability for the case of noise power estimation. Using the derived formulas and simulation results, it is demonstrated that the error probability quickly approaches to the optimal performance as the number samples used for the noise power estimation increases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1104-1120
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• 2020

The chest X-rays are a common way to diagnose lung cancer or pneumonia. In particular, the finding of a lung nodule is the most important problem in the early detection of lung cancer. Recently, a lot of automatic diagnosis algorithms have been studied to find the lung nodules missed by doctors. The algorithms are typically based on segmentation network like U-Net. However, the occurrence of false positives that similar to lung nodules present outside the lungs can severely degrade performance. In this study, we propose a multi-task learning method that simultaneously learns the lung region and nodule-labeled data based on the prior knowledge that lung nodules exist only in the lung. The proposed method significantly reduces false positives outside the lung and improves the recognition rate of lung nodules to 83.8 F1 score compared to 66.6 F1 score of single task learning with U-net model. The experimental results on the JSRT public dataset demonstrate the effectiveness of the proposed method compared with other baseline methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1169-1193
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• 2010

In this paper, we present and compare two different multiple camera collaboration strategies to reduce false association in finding the correspondence of objects. Collaboration matrices are defined with the required minimum separation for an effective collaboration because homographic lines for objects association are ineffective with the insufficient separation. The first strategy uses the collaboration matrices to select the best pair out of many cameras having the maximum separation to efficiently collaborate on the object association. The association information in selected cameras is propagated to unselected cameras by the global information constructed from the associated targets. While the first strategy requires the long operation time to achieve the high association rate due to the limited view by the best pair, it reduces the computational cost using homographic lines. The second strategy initiates the collaboration process of objects association for all the pairing cases of cameras regardless of the separation. In each collaboration process, only crossed targets by a transformed homographic line from the other collaborating camera generate homographic lines. While the repetitive association processes improve the association performance, the transformation processes of homographic lines increase exponentially. The proposed methods are evaluated with real video sequences and compared in terms of the computational cost and the association performance. The simulation results demonstrate that the proposed methods effectively reduce the false association rate as compared with basic pair-wise collaboration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1801-1816
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• 2014

Because HTTP-related ports are allowed through firewalls, they are an obvious point for launching cyber attacks. In particular, malware uses HTTP protocols to communicate with their master servers. We call this an HTTP-based command and control (C&C) server. Most previous studies concentrated on the behavioral pattern of C&Cs. However, these approaches need a well-defined white list to reduce the false positive rate because there are many benign applications, such as automatic update checks and web refreshes, that have a periodic access pattern. In this paper, we focus on finding new discriminative features of HTTP-based C&Cs by analyzing HTTP activity sets. First, a C&C shows a few connections at a time (low density). Second, the content of a request or a response is changed frequently among consecutive C&Cs (high content variability). Based on these two features, we propose a novel C&C analysis mechanism that detects the HTTP-based C&C. The HAS-Analyzer can classify the HTTP-based C&C with an accuracy of more than 96% and a false positive rate of 1.3% without using any white list.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.1-9
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• 2018

In this paper, we propose a face recognition method which is not sensitive to illumination change and prevents false recognition of photographs. The proposed method uses infrared and depth images at the same time, solves sensitivity of illumination change by infrared image, and prevents false recognition of two - dimensional image such as photograph by depth image. Face detection method using infrared and depth images simultaneously and feature extraction and matching method for face recognition are realized. Simulation results show that accuracy of face recognition is increased compared to conventional methods.