• Title/Summary/Keyword: false negative

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A Real Time Scan Detection System against Attacks based on Port Scanning Techniques (포트 스캐닝 기법 기반의 공격을 탐지하기 위한 실시간 스캔 탐지 시스템 구현)

  • 송중석;권용진
    • Journal of KIISE:Information Networking
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    • v.31 no.2
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    • pp.171-178
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    • 2004
  • Port scanning detection systems should rather satisfy a certain level of the requirement for system performance like a low rate of “False Positive” and “False Negative”, and requirement for convenience for users to be easy to manage the system security with detection systems. However, public domain Real Time Scan Detection Systems have high rate of false detection and have difficulty in detecting various scanning techniques. In addition, as current real time scan detection systems are based on command interface, the systems are poor at user interface and thus it is difficult to apply them to the system security management. Hence, we propose TkRTSD(Tcl/Tk Real Time Scan Detection System) that is able to detect various scan attacks based on port scanning techniques by applying a set of new filter rules, and minimize the rate of False Positive by applying proposed ABP-Rules derived from attacker's behavioral patterns. Also a GUI environment for TkRTSD is implemented by using Tcl/Tk for user's convenience of managing network security.

Evaluation of Usefulness for Diagnosis of Lung Cancer on Integrated PET-MRI Using Decision Matrix (판정행렬을 기반한 일체형 PET-MRI의 폐암 진단 유용성 평가)

  • Kim, Jung-Soo;Yang, Hyun-Jin;Kim, Yoo-Mi;Kwon, Hyeong-Jin;Park, Chanrok
    • Journal of radiological science and technology
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    • v.44 no.6
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    • pp.635-643
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    • 2021
  • The results of empirical researches on the diagnosis of lung cancer are insufficient, so it is limited to objectively judge the clinical possibility and utilization according to the accuracy of diagnosis. Thus, this study retrospectively analyzed the lung cancer diagnostic performance of PET-MRI (Positron Emission Tomography-Magnetic Resonance Imaging) by using the decision matrix. This study selected and experimented total 165 patients who received both hematological CEA (Carcinoembryonic Antigen) test and hybrid PET-MRI (18F-FDG, 5.18 MBq/kg / Body TIM coil. VIVE-Dixon). After setting up the result of CEA (positive:>4 ㎍/ℓ. negative:<2.5㎍/ℓ) as golden data, the lung cancer was found in the image of PET-MRI, and then the SUVmax (positive:>4, negative:<1.5) was measured, and then evaluated the correlation and significance of results of relative diagnostic performance of PET-MRI compared to CEA through the statistical verification (t-test, P>0.05). Through this, the PET-MRI was analyzed as 96.29% of sensitivity, 95.23% of specificity, 3.70% of false negative rate, 4.76% of false positive rate, and 95.75% of accuracy. The false negative rate was 1.06% lower than the false positive rate. The PET-MRI that significant accuracy of diagnosis through high sensitivity and specificity, and low false negative rate and false positive rate of lung cancer, could acquire the fusion image of specialized soft tissue by combining the radio-pharmaceuticals with various sequences, so its clinical value and usefulness are regarded as latently sufficient.

AI-Based Intelligent CCTV Detection Performance Improvement (AI 기반 지능형 CCTV 이상행위 탐지 성능 개선 방안)

  • Dongju Ryu;Kim Seung Hee
    • 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..

Histopathologic Comparative Study of Aspiration Biopsy Cytology from 139 Thyroid Nodules (갑상선결절(甲狀腺結節)에서의 흡인세포학적(吸引細胞學的) 소견(所見)과 병리조직학적(病理組織學的) 진단(診斷)에 대한 비교연구(比較硏究))

  • Kim Kwang-Chul;Wang Hee-Jung;Suh Yeon-Lim;Chang Surk-Hyo;Lee Hyuck-Sang
    • Korean Journal of Head & Neck Oncology
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    • v.8 no.2
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    • pp.97-105
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    • 1992
  • One hundred and thirty-nine thyroid nodules were evaluated by aspiration biopsy cytology (ABC) and were compared with the postoperative histologic diagnosis during the period from May 1, 1986 through Aug. 31, 1992. The correlation betwen the two diagnoses proved to be comparable with a low incidence of false-negative diagnoses, but with a relatively high incidence of false-positive ones. The sensitivity was 93.5%, specificity 89.6%, false-negative rate 6.5%, false-positive rate 10.4%, positive predictability 87.9%, negative predictability 94.5%, and overall diagnostic accuracy 91.4%.

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The Analysis of IDS Alarms based on AOI (AOI에 기반을 둔 침입탐지시스템의 알람 분석)

  • Jung, In-Chul;Kwon, Young-S.
    • IE interfaces
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    • v.21 no.1
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    • pp.33-42
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    • 2008
  • To analyze tens of thousands of alarms triggered by the intrusion detections systems (IDS) a day has been very time-consuming, requiring human administrators to stay alert for all time. But most of the alarms triggered by the IDS prove to be the false positives. If alarms could be correctly classified into the false positive and the false negative, then we could alleviate most of the burden of human administrators and manage the IDS far more efficiently. Therefore, we present a new approach based on attribute-oriented induction (AOI) to classify alarms into the false positive and the false negative. The experimental results show the proposed approach performs very well.

THE USEFULNESS OF BONE SCAN FOR EVALUATING JAW BONE EXTENSION OF ORAL CANCER (구강암의 악골 침윤 평가에 있어서 골스캔의 효과)

  • Park, Hong-Ju;Ryu, Sun-Youl
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.26 no.6
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    • pp.658-665
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    • 2000
  • Purpose : The present study was carried out to determine the diagnostic usefulness of bone scan for evaluating jaw bone extension of oral cancer. Materials and Methods : Medical records, preoperative bone scans, computerized tomographic (CT) scans, conventional radiographs, and findings of histopathologic sections of twenty patients who had been treated for oral malignant tumors by a resection of mandible and soft tissue at Chonnam University Hospital from January, 1994 to September, 1999 were analyzed. Results : In 13 cases which showed histopathologically positive, preoperative bone scans were positive in 12 (92.3%) and false negative in 1 (7.7%). Preoperative CT scans were positive in 9 (69.2%) and false negative in 4 (30.8%) of the 13 cases. Preoperative conventional radiographs were positive in 8 (61.5%) and false negative in 5 (38.5%) of the 13 cases. In 7 cases showing negative histopathologic findings, 1 (14.3%) was in CT scans and 2 (28.6%) were false positive in preoperative conventional radiographs. Conclusion : These results suggest that bone scan is more sensitive and reliable method for evaluating jaw bone extension of oral cancer than conventional radiographs or CT scans.

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False-Negative Results of Real-Time Reverse-Transcriptase Polymerase Chain Reaction for Severe Acute Respiratory Syndrome Coronavirus 2: Role of Deep-Learning-Based CT Diagnosis and Insights from Two Cases

  • Dasheng Li;Dawei Wang;Jianping Dong;Nana Wang;He Huang;Haiwang Xu;Chen Xia
    • Korean Journal of Radiology
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    • v.21 no.4
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    • pp.505-508
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    • 2020
  • The epidemic of 2019 novel coronavirus, later named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still gradually spreading worldwide. The nucleic acid test or genetic sequencing serves as the gold standard method for confirmation of infection, yet several recent studies have reported false-negative results of real-time reverse-transcriptase polymerase chain reaction (rRT-PCR). Here, we report two representative false-negative cases and discuss the supplementary role of clinical data with rRT-PCR, including laboratory examination results and computed tomography features. Coinfection with SARS-COV-2 and other viruses has been discussed as well.

Test Bed Design of Fire Detection System Based on Multi-Sensor Information for Reduction of False Alarms (화재감지 오보 감소를 위한 다중정보기반 시스템의 Test Bed 설계)

  • Lee, Kijun;Kim, Hyeong Gweon;Lee, Bong Woo;Kim, Tae-Ok;Shin, Dongil
    • Journal of the Korean Institute of Gas
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    • v.16 no.6
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    • pp.107-114
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    • 2012
  • Fire detection system is used for detection and alarm-generation of danger in case of fire. Most fire detection systems being used these days often malfunction from false positive and false negative errors. To improve detection reliability, an integrated fire detection algorithm using multi-senor information of heat, smoke and carbon monoxide detectors is suggested, then built and tested using the LabVIEW environment. Simulated using sensor measurement data offered by National Institute of Standards and Technology (NIST), possibility of reducing false positive and false negative errors is verified.

A Method for Synthesizing Features for the Accuracy of Predicting Cancer (암 예측의 정확성을 위한 특성 합성 방법)

  • Shin, SeungYeon;Kim, Hyunjin;Park, Sanghyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.10a
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    • pp.525-526
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    • 2016
  • machine learning 기법 중 하나인 logistic regression을 이용하여 benign sample과 breast cancer sample을 구분할 수 있는데, 이 연구를 통해 classification의 정확도를 높이고 false positive와 false negative의 비율을 줄이려고 했다. 그래서 logistic regression의 parameter 값을 바탕으로 regression function에 영향을 많이 주는 feature 들을 선택하고, 영향력 있는 feature 들을 더한 새로운 feature를 추가했다. 그 결과 정확도와 F-score가 증가했으며, false positive, false negative의 비율이 감소했다.

Design of T-N2SCD Detection Model based on Time Window (타임 윈도우 기반의 T-N2SCD 탐지 모델 구현)

  • Shin, Mi-Yea;Won, Il-Young;Lee, Sang-Ho
    • 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.