• Convergence Security Journal
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• v.7 no.1
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• pp.63-75
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• 2007

Most of computer systems to be connected to network have been exposed to some network attacks and became to targets of system attack. System managers have established the IDS to prevent the system attacks over network. The previous IDS have decided intrusions detecting the requested connection packets more than critical values in order to detect attacks. This techniques have False Positive possibilities and have difficulties to detect the slow scan increasing the time between sending scan probes and the coordinated scan originating from multiple hosts. We propose the port scan detection rules detecting the RST/ACK flag packets to request some abnormal connections and design the data structures capturing some of packets. This proposed system is decreased a False Positive possibility and can detect the slow scan, because a few data can be maintained for long times. This system can also detect the coordinated scan effectively detecting the RST/ACK flag packets to be occurred the target system.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.2251-2255
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• 2014

Background: The aim of this study was to evaluate 10 years of false positive urine cytology records, along with follow-up histologic and cytologic data, to determine the significance of suspicious urine cytology findings. Materials and Methods: We retrospectively reviewed records of urine samples harvested between January 2002 and December 2012 from voided and catheterized urine from the bladder. Among the 21,283 urine samples obtained during this period, we located 1,090 eligible false positive findings for patients being evaluated for the purpose of confirming urothelial carcinoma (UC). These findings were divided into three categories: atypical, indeterminate, and suspicious of malignancy. Results: Of the 1,090 samples classified as false positive, 444 (40.7%) were categorized as atypical, 367 (33.7%) as indeterminate, and 279 (25.6%) as suspicious of malignancy. Patients with concomitant UC accounted for 105 (23.6%) of the atypical samples, 147 (40.1%) of the indeterminate samples, and 139 (49.8%) of the suspicious of malignancy samples (p<0.0001). The rate of subsequent diagnosis of UC during a 1-year follow-up period after harvesting of a sample with false positive urine cytology initially diagnosed as benign was significantly higher in the suspicious of malignancy category than in the other categories (p<0.001). The total numbers of UCs were 150 (33.8%) for atypical samples, 213 (58.0%) for indeterminate samples, and 199 (71.3%) for samples categorized as suspicious of malignancy. Conclusions: Urine cytology remains the most specific adjunctive method for the surveillance of UC. We demonstrated the clinical value of dividing false positive urine cytology findings into three categories, and our results may help clinicians better manage patients with suspicious findings.

• 대한예방의학회:학술대회논문집
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• 1994.02b
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• pp.142-149
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• 1994

Substitution of graphic representation for extensive lists of numerical statistical data is highly desirable by both editors and readers of medical journals, faced with an exploding abundance of contemporary medical literature. A novel graphic tool. the 'double-ring diagram', is described herein which permits visual representation of information regarding certain statistical variables used to describe the performance of a test or physical sign in the diagnosis of a disease. The diagram is relatively easy to construct on the basis of a number of primary data such as the prevalence and the true positive, true negative. false positive and false negative test results. These values are reflected in the diagram along with the values of other statistical variables derived from them. such as the sensitivity. specificity, predictive values for positive and negative test result. and accuracy. This diagram may be useful in visualizing a test's performance and facilitating visual comparison of performance of two or more tests.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.8
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• pp.878-882
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• 2010

DaaS model that surrogates their data has a problem of privacy leakage by service provider. In this paper, we analyze inference attack that can occur on encrypted data that consist of multiple column through index, and we suggest b-anonymity to protect data against inference attack. We use R+-tree technique to minimize false-positive that can happen when we use an index for efficiency of data processing.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.55-65
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• 2019

Although crack on concrete exists from its early formation, crack requires attention as it affects stiffness of structure and can lead demolition of structure as it grows. Detecting cracks on concrete is needed to take action prior to performance degradation of structure, and deep learning can be utilized for it. In this study, transfer learning, one of the deep learning techniques, was used to detect the crack, as the amount of crack's image data was limited. Pre-trained Inception-v3 was applied as a base model for the transfer learning. Web scrapping was utilized to fetch images of concrete wall with or without crack from web. In the recognition of crack, image post-process including changing size or removing color were applied. In the visualization of crack, source images divided into 30px, 50px or 100px size were used as input data, and different numbers of input data per category were applied for each case. With the results of visualized crack image, false positive and false negative errors were examined. Highest accuracy for the recognizing crack was achieved when the source images were adjusted into 224px size under gray-scale. In visualization, the result using 50 data per category under 100px interval size showed the smallest error. With regard to the false positive error, the best result was obtained using 400 data per category, and regarding to the false negative error, the case using 50 data per category showed the best result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2341-2348
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• 2009

An intrusion detection technique based on host consider system call sequence or system call arguments. These two ways are suitable when system call sequence or order and length of system call arguments are out of order. However, there are two disadvantages which a false positive rate and a false negative rate are high. In this paper we propose the T-N2SCD detection model based on Time Window in order to reduce false positive rate and false negative rate. Data for using this experiment is provided from DARPA. As experimental results, the proposed model showed that the false positive rate and the false negative rate are lowest at an interval of 1000ms than at different intervals.

• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1265-1276
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• 2019

Data deduplication is a common method to improve cloud storage efficiency and save network communication bandwidth, but it also brings a series of problems such as privacy disclosure and dictionary attacks. This paper proposes a secure deduplication scheme for cloud storage based on Bloom filter, and dynamically extends the standard Bloom filter. A public dynamic Bloom filter array (PDBFA) is constructed, which improves the efficiency of ownership proof, realizes the fast detection of duplicate data blocks and reduces the false positive rate of the system. In addition, in the process of file encryption and upload, the convergent key is encrypted twice, which can effectively prevent violent dictionary attacks. The experimental results show that the PDBFA scheme has the characteristics of low computational overhead and low false positive rate.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.442-449
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• 2020

Objective: To compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) versus ultrasonography (US) in symptomatic patients with dense breasts, while using histology as the gold standard. Materials and Methods: After obtaining approval from the local ethics board, this prospective study collected data from patients with symptomatic breasts who underwent CESM and US examinations from May 1, 2017 to September 30, 2017. We then selected those with dense breasts and pathological results as our sample population. Both CESM and US results were classified by a radiologist through the Breast Imaging Reporting and Data System, and the results were compared with their corresponding histological results. The chi-square test was conducted to compare the diagnostic performance of CESM and US, and the receiver operating characteristic curves for the two imaging modalities were obtained. Results: A total of 131 lesions from 115 patients with dense breasts were included in this study. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 93.8%, 88.1%, 88.2%, 93.7%, and 90.8% for CESM, and 90.6%, 82.1%, 82.9%, 90.2%, and 86.3% for US, respectively. The p values for sensitivity, specificity, PPV, NPV, and accuracy were 0.687, 0.388, 0.370, 0.702, and 0.238, respectively. The area under the curve of CESM (0.917) was comparable with that of US (0.884); however, the differences between CESM and US were not statistically significant (p = 0.225). Eight false-positive cases and 4 false-negative cases for breast cancer were found in CESM, while 12 false-positive cases and 6 false-negative cases were found in US. Conclusion: The diagnostic performances of CESM and US are comparable in symptomatic women with dense breasts; however, the routine use of additional US imaging is questionable for lesions that can be detected by CESM.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.373-382
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• 2017

As the number of scientific and technical contents increases, services that support efficient search of scientific and technical contents are required. When an author's affiliation is used as a keyword, not only the contents produced by the affiliation can be searched, but also the identification rate of the search result using the author and the term as keyword can be improved. Because of the ambiguity and vagueness of the data used as a search keyword, the search result may include false negative or false positive. However, the previous research on the control through identification of the search keyword is mainly focused on the author data and terminology data. In this paper, we propose the algorithm to identify affiliations and experiment with show the experiment with scientific and technological contents held by the Korea Institute of Science and Technology Information.