• Journal of Industrial Technology
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• v.27 no.B
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• pp.77-82
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• 2007

A novel DDoS (Distributed Denial-of-Service) defense technique, Exaustiveness-Based Detection, is proposed in this work. It dispenses with the network congestion and the unfairness between users of the Defense-by-Offense technique by incorporating a kind of simple Detect-and-Block scheme (user identification), still improving the effectiveness of the defense in comparison to the original Defense-by-Offense technique. It uses SYN cookies to identify users in the granularity of ip address and to prevent ip address spoofing by the attacker. There can be, however, some probability of false negative (denying service to good clients), if the attacker wisely adapt to the new technique by saving some portion of its bandwidth resource and later mimicking good clients. Quantitative analysis the requirement for the good clients to be safe from the false negative is provided and a procedure to design the server capacity is explained.

• The Korean Journal of Cytopathology
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• v.18 no.2
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• pp.112-118
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• 2007

Fine needle aspiration cytology (FNAC) has become a highly preferred, minimally invasive diagnostic tool of choice in the diagnosis of a palpable breast mass owing to its sensitivity, specificity, cost-effectiveness, and expediency. Although breast needle biopsies have been widely employed recently due to the increased detection rate of non-palpable early lesions, the importance of the use of FNAC cannot be underestimated. It comprises part of the diagnostic triad for the breast along with a physical examination and mammography, which together contribute to an increasing diagnostic accuracy. The differential diagnosis of a benign and malignant lesion is of the utmost importance in the diagnosis of breast lesions, and therefore the understanding of the possible diagnostic pitfalls is of great importance.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.481-483
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• 2004

NIDS(Network Intrusion Detection System)는 공격 탐지 과정에서 대량의 로그가 발생하게 되는데 일반적인 침입탐지 시스템에서 탐지되어 하루에 남는 로그만으로도 시스템에 막대한 양을 차지한다 이러한 문제점은 관리자에게 많은 부담을 줄뿐만 아니라 그렇게 남겨진 로그에는 오탐율(False Positive) 비율이 높기 때문에 관리자가 실제로 위협적인 침입을 식별하고, 침입 행위에 대한 빠른 대응을 어렵게 만든다. 그러므로 NIDS와 특정 호스트가 가지고 있는 보안상 취약한 부분을 비교하여 판단할 수 있는 침입탐지시스템을 선택, 운용하는 것은 관리측면이나 대응측면에서 매우 중요한 일이라고 할 수 있다. 본 논문에서는 NIDS와 해당 호스트 취약점 정보를 이용해 작성된 데이터베이스(HVIDB : Host Vulnerability Information Database)를 이용하여 호스트의 취약성에 관한 로그만을 최종 경고해줌으로써 오탐율의 양을 감소시키고 호스트 보안성의 향상과 관리자가 로그분석 등의 IDS 업무를 효과적으로 할 수 있는 모델을 제시한다.

• Annual Conference of KIPS
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• 2002.04b
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• pp.927-930
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• 2002

본 논문에서는 중요 프로세스(privileged process)의 시스템 호출 순서(system call sequence)를 이용한 침입탐지 시스템을 제안한다. 기존 연구의 정상행위 기반 침입탐지 시스템은 정상행위를 모델링하여 시스템을 구성하고, 이와 비교를 통해 프로세스의 이상(anomaly) 여부를 결정한다. 이러한 방법은 모델링되지 않은 미지의 행위에 대한 적절한 판단을 행할 수 없으므로, 높은 오류율(false-positive/negative)을 보인다. 본 논문에서는 현재까지 알려진 공격에서 공통적으로 나타나는 윈도우들을 수집하여 침입예상윈도우를 구축하고, 이를 기존의 침입탐지 시스템에 부가적으로 사용하여 효과적으로 오류율(false-positive/negative)을 낮출 수 있음을 보인다. 실험 결과 제안된 방법을 통한 침입탐지는 기존의 방법에 비해 공격 탐지율은 증가하고 정상행위에 대한 오류율은 감소하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.313-329
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• 2011

To provide a seamless network to customers, Internet service providers must promptly detect and control abnormal traffic. One approach is to shorten the traffic information measurement cycle. However, performance degradation is inevitable if traffic measurement servers merely shorten the cycle and measure all traffic. This paper presents a software architecture that can measure traffic more frequently without degrading performance by estimating the level of abnormal traffic. The algorithm in the architecture estimates the values of the interface group objects in MIB by using the IP group objects thereby reducing the number of measurements and the size of measured data. We evaluated this architecture on part of Internet service provider's IP network. When the traffic was measured 5 times more than before, the CPU usage and TPS of the proposed scheme was 7% and 41% less than that of the original scheme while the false positive rate and false negative rate were 3.2% and 2.7% respectively.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.13-18
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• 2019

This paper analyzes the signal acquisition performance of the legacy GNSS spreading codes and a polyphase code. The code length and chip rate of a polyphase code are assumed to be same as those of the GPS L1 C/A and Galileo E1C codes. The autocorrelation and cross correlation characteristics are analyzed. In addition, a way to calculate a more accurate probability of false alarm for a code with sidelobe non-zero auto-correlation function is proposed. Finally, we estimate the probability of detection and the mean acquisition time for a given signal strength and the probability of false alarm.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.22-29
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• 2021

This study evaluates the accuracy of corrective feedback from Grammarly, an online grammar checker, on essays written by cyber university learners in terms of detected errors, suggested replacement forms, and false alarms.The results indicate that Grammarly has a high overall error detection rate of over 65%, being particularly strong at catching errors related to articles and prepositions. In addition, on the detected errors, Grammarly mostly provide accurate replacement forms and very rarely make false alarms. These findings suggest that Grammarly has high potential as a useful educational tool to complement the drawbacks of teacher feedback and to help learnersimprove grammatical accuracy in their written work. However, it is still premature to conclude that Grammarly can completely replace teacher feedback because it has the possibility (approximately 35%) of failing to detect errors and the limitationsin detecting errors in certain categories. Since the feedback from Grammarly is not entirely reliable, caution should be taken for successful integration of Grammarly in English writing classes. Teachers should make judicious decisions on when and how to use Grammarly, based on a keen awareness of Grammarly's strengths and limitations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.652-654
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• 2021

Attacks such as DDoS are detected by the intrusion detection system and can be prevented early. DDoS attack traffic was analyzed using the decision tree. Deterministic features with high importance were found, and the accuracy was verified by proceeding the decision tree for only those properties. And the contents of false positive and false negative traffic were analyzed. As a result, the accuracy of one attribute was 98% and the two attributes were 99.8%, respectively.

• Food Science of Animal Resources
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• v.34 no.5
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• pp.665-673
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• 2014

We compared standard culture methods as well as conventional PCR and real-time PCR for the detection of Listeria monocytogenes (L. monocytogenes) in milk, cheese, fresh-cut vegetables, and raw beef that have different levels of background microflora. No statistical differences were observed in sensitivity between the two selective media in all foods. In total, real-time PCR assay exhibited statistically excellent detection sensitivity (p<0.05) and was less time consuming and laborious as compared with standard culture methods. Conventional culture methods showed poor performance in detecting L. monocytogenes in food with high levels of background microflora, generating numerous false negative results. While the detection of L. monocytogenes in fresh cut vegetable by culture methods was hindered only by L. innocua, various background microflora, such as L. innocua, L. welshimeri, L. grayi, and Enterococcus faecalis appeared on the two selective media as presumptive positive colonies in raw beef indicating the necessity of improvement of current selective media. It appears that real-time PCR is an effective and sensitive presumptive screening tool for L. monocytogenes in various types of foods, especially foods samples with high levels of background microflora, thus complementing standard culture methodologies.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.