• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.231-242
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• 2013

Recently, automated software testing methods such as fuzzing have been researched to find software vulnerabilities. The purpose of fuzzing is to disclose software vulnerabilities by providing a software with malformed data. In order to increase the probability of vulnerability discovery by fuzzing, we must solve the test suite reduction problem because the probability depends on the test case quality. In this paper, we propose a new method to solve the test suite reduction problem which is suitable for the long test case such as file. First, we suggested the length of test case as a measure in addition to old measures such as coverage and redundancy. Next we designed a test suite reduction algorithm using the new measure. In the experimental results, the proposed algorithm showed better performance in the size and length reduction ratio of the test suite than previous studies. Finally, results from an empirical study suggested the viability of our proposed measure and algorithm for file fuzzing.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.129-134
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• 2015

Since automatic social engineering based spam attacks induce for users to click or receive the short message service (SMS), e-mail, site address and make a relationship with an unknown friend, it is very easy for them to active in online social networks. The previous spam detection schemes only apply manual filtering of the system managers or labeling classifications regardless of the features of social networks. In this paper, we propose the spam detection metric after reflecting on a couple of features of social networks followed by analysis of real social network data set, Twitter spam. In addition, we provide the online social networks based unsupervised scheme for automated social engineering spam with self organizing map (SOM). Through the performance evaluation, we show the detection accuracy up to 90% and the possibility of real time training for the spam detection without the manager.

• Journal of KIISE:Software and Applications
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• v.29 no.12
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• pp.860-872
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• 2002

Fault tree analysis is the most widely used saftly analysis technique in industry. However, the analysis is often applied manually, and there is no systematic and automated approach available to validate the analysis result. In this paper, we demonstrate that a real-time model checker UPPAAL is useful in formally specifying the required behavior of safety-critical software and to validate the accuracy of manually constructed fault trees. Functional requirements for emergency shutdown software for a nuclear power plant, named Wolsung SDS2, are used as an example. Fault trees were initially developed by a group of graduate students who possess detailed knowledge of Wolsung SDS2 and are familiar with safety analysis techniques including fault tree analysis. Functional requirements were manually translated in timed automata format accepted by UPPAAL, and the model checking was applied using property specifications to evaluate the correctness of the fault trees. Our application demonstrated that UPPAAL was able to detect subtle flaws or ambiguities present in fault trees. Therefore, we conclude that the proposed approach is useful in augmenting fault tree analysis.

• Journal of Microbiology and Biotechnology
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• v.19 no.10
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• pp.1259-1264
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• 2009

We assessed the capacity of two liquid-medium culture methods with automated incubation and reading systems (MB/BacT ALERT 3D System and BACTEC MGIT 960 System) and one solid-medium culture method ($L\ddot{o}wenstein$-Jensen) to detect mycobacteria in different types of clinical samples. Out of 1,770 cultured clinical samples (1,519 of respiratory origin and 251 of non respiratory origin), mycobacteria were isolated in 156 samples (135 M. tuberculosis complex, 8 M. chelonae, 6 M. kansasii, 4 M. fortuitum, 2 M. gordonae, and 1 M. marinum) by at least one of the methods used. The BACTEC MGIT 960 System proved to be the most sensitive method (86.5%), especially in the detection of M. tuberculosis complex (89.1%). However, $L\ddot{o}wenstein$-Jensen culture was the most sensitive (76.2%) to detect nontuberculous mycobacteria. The BACTEC MGIT 960 System showed the lowest mean detection time for mycobacterial growth (15.3 days), significantly shorter than the other two methods. Highest sensitivity (95.5%) and specificity (99.6%) values were obtained using the BACTEC MGIT 960 System with the $L\ddot{o}wenstein$-Jensen culture method, which was also the only combination capable of detecting 100% of the nontuberculous mycobacteria.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.169-176
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• 2015

Implantable closed-loop epilepsy controllers require ideally both accurate epileptic seizure detection and low power consumption. On-chip oscillators can be used in implantable devices because they consume less power than other oscillators such as crystal oscillators. In this study, we investigated the tolerable error range of a lower power on-chip oscillator without losing the accuracy of seizure detection. We used 24 ictal and 14 interictal intracranial electroencephalographic segments recorded from epilepsy surgery patients. The performance variations with respect to oscillator frequency errors were estimated in terms of specificity, modified sensitivity, and detection timing difference of seizure onset using Generic Osorio Frei Algorithm. The frequency errors of on-chip oscillators were set at ${\pm}10%$ as the worst case. Our results showed that an oscillator error of ${\pm}10%$ affected both specificity and modified sensitivity by less than 3%. In addition, seizure onsets were detected with errors earlier or later than without errors and the average detection timing difference varied within less than 0.5 s range. The results suggest that on-chip oscillators could be useful for low-power implantable devices without error compensation circuitry requiring significant additional power. These findings could help the design of closed-loop systems with a seizure detector and automated stimulators for intractable epilepsy patients.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.287-298
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• 2013

To develop a technique classifying patients based on computerized clinical data followed by validity verification by comparing with nurse's examination. Class scores were determined by nurses for a day on 348 resident patients in 7 wards of a general hospital according to KPCS-1. The class scores were simultaneously evaluated by reviewing the computerized clinical data acquired from the hospital management information system. These two class scores were both significantly different among different departments as well as disease patterns. Intraclass correlation analysis resulted a very high correlation coefficient of 0.96(p<0.01) between the two scoring methods, but the clinical data scores were somewhat higher. An automated patient classification system seemed possible to be developed in future with further enhancement of the present results based on computerized clinical data without manual scoring, which can be applied for performance evaluation as well as workforce planning.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1960-1969
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• 2017

There have been ongoing researches to identify and analyze the patterns of electric power IoT data inside sensor nodes to supplement the stable supply of power and the efficiency of energy consumption. This study set out to propose an analysis process for electric power IoT data with the K-means algorithm, which is an unsupervised learning technique rather than a supervised one. There are a couple of problems with the old K-means algorithm, and one of them is the selection of cluster number K in a heuristic or random method. That approach is proper for the age of standardized data. The investigator proposed an analysis process of selecting an automated cluster number K through principal component analysis and the space division of normal distribution and incorporated it into electric power IoT data. The performance evaluation results show that it recorded a higher level of performance than the old algorithm in the cluster classification and analysis of pitches and rolls included in the communication bodies of utility poles.

• Journal of the Korean Society of Propulsion Engineers
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• v.8 no.2
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• pp.46-53
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• 2004

Ultrasonic testing method has been developed to evaluate flaw of adhesive layers in blast tube for the reliability of the rocket nozzle. The ultrasonic reflection from the interface between the steel sheet and the epoxy adhesive is measured with a high-frequency Pulse-echo setup in order to identify contact debonding and missing adhesive in epoxy layer between steel and FRP layers. The steel sheet is resonated by low-frequency ultrasound, and the gap size underneath the measuring location is estimated from the resonance responses. For practical application in industry an automated testing system has been developed where the proposed approach is implemented. The performance of the proposed approach has been verified by actual measurement of gap sizes from the cross-sections of cut specimens using an optical microscope.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.378-385
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• 2017

The aim of this study was to analyze cohesion and word information among different types of questions in the English reading section of the College Scholastic Ability Tests (CSAT). The types of questions were divided into three categories: macro reading, micro reading, and indirect writing. Reading texts from 1994 to 2017 CSAT were analyzed by Coh-Metrix, an automated evaluation program of text and discourse. The findings of this study indicated that there were statistical differences among the three categories of questions for noun overlap, stem overlap, adversative and contrastive connective, additive connective, pronoun incidence, age of acquisition, concreteness for content word, imagability, and meaningfulness. The information of the findings bore pedagogic implications for developing textbooks, questions for CSAT, and reading strategies by students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.686-691
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• 2016

In welded steel structures, there are many stress concentration sites such as weld beads, and welding defects are likely to occur at the welded parts. When a repeated fatigue load acts on a stress concentration site, fatigue crack occurs and propagates, leading to fatigue fracture. Therefore, it is necessary to understand fatigue life, crack initiation life, and crack propagation life in order to prevent fatigue failure. In this study, a compliance method was derived for use in the study of fatigue crack propagation characteristics. This compliance can be used for automated measurement of fatigue cracks. The compliance was calculated using an in-house FEM program for a CT specimen. The results of this calculation are presented in relation to a/W and compared with calculation results using the J integral and a program from a previous study. In addition, the strain distribution in the upward and downward directions was calculated from the center of the back face of the CT specimen. In this distribution, the strain tended to decrease from the center to the top and bottom. The compliance method was achieved from these calculations and can be used for automatic execution of crack propagation tests.