• Asian Oncology Nursing
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• v.12 no.1
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• pp.52-60
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• 2012

Purpose: This study is to determine knowledge about early detection and risk perception of cancer according to taking cancer screening tests in the general population. Methods: The participants were 151 people aged 40 years or older. A questionnaire consisted of knowledge about early detection (warning signs, cancer screening methods, general knowledge for early detection), cancer risk perception and history of cancer screening during past 2 years. Results: The percentages of correct answers were 64.7% in knowledge about warning signs, 73.7% in knowledge of cancer screening tests and 80.1% in general knowledge for early detection. Participants had the highest knowledge about screening methods for stomach cancer and the lowest for liver and colon cancer. The level of risk perception was medium. The participants who participated in cancer screening showed lower risk perception than those who did not. There was no significant relationship between knowledge and performance of cancer screening. The primary reason for not participating in cancer screening was patient's perception of their own health. Conclusion: These results suggest that cancer risk perception can affect the performance of cancer screening and we need to study how to handle this problem. Additionally screening programs should focus on liver cancer and colon cancer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.959-981
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• 2017

Existing Android malware detection approaches mostly have concentrated on superficial features such as requested or used permissions, which can't reflect the essential differences between benign apps and malware. In this paper, we propose a quantitative calculation model of application risks based on the key observation that the essential differences between benign apps and malware actually lie in the way how permissions are used, or rather the way how their corresponding permission methods are used. Specifically, we employ a fine-grained analysis on Android application risks. We firstly classify application risks into five specific categories and then introduce comprehensive risk, which is computed based on the former five, to describe the overall risk of an application. Given that users' risk preference and risk-bearing ability are naturally fuzzy, we design and implement a fuzzy logic system to calculate the comprehensive risk. On the basis of the quantitative calculation model, we propose a risk classification based approach for Android malware detection. The experiments show that our approach can achieve high accuracy with a low false positive rate using the RandomForest algorithm.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.91-102
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• 2012

Network port scan attack is the method for finding ports opening in a local network. Most existing IDSs(intrusion detection system) record the number of packets sent to a system per unit time. If port scan count from a source IP address is higher than certain threshold, it is regarded as a port scan attack. The degree of risk about source IP address performing network port scan attack depends on attack count recorded by IDS. However, the measurement of risk based on the attack count may reduce port scan detection rates due to the increased false negative for slow port scan. This paper proposes a method of summarizing 4 types of information to differentiate network port scan attack more precisely and comprehensively. To integrate the riskiness, we present a risk index that quantifies the risk of port scan attack by using PCA. The proposed detection method using risk index shows superior performance than Snort for the detection of network port scan.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• Korean Journal of Health Education and Promotion
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• v.26 no.1
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• pp.15-26
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• 2009

Objectives: The current study evaluated the effects of an integrated breast health program according to levels of breast cancer risk appraisal on knowledge on breast cancer, early detection behaviors, and diet patterns and attitudes in Korean healthy women. Method: A nonequivalent control group pre-posttest design was used. A total of 413 women aged 40-59, registering at the Life Long Health Center in two cities, were classified into intervention groups of 179 women and control groups of 234 women. The integrated breast health program included education, counseling on breast cancer, early detection behaviors, and appropriate diet with multimedia and individual practice session using breast models, reflecting characteristics of each level according to levels of risk appraisal. The knowledge on breast cancer, early detection behaviors, and diet were investigated using questionnaires at baseline and three months after intervention. Results: In both normal and borderline-risk group, intervention groups reported significantly higher scores of knowledge on breast cancer and higher stages of BSE behaviors than control groups. Conclusion: The results showed positive effects on knowledge and early detection behaviors of breast cancer in normal and borderline-risk groups. Further studies should investigate longitudinal effects of the intervention program on dietary change.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.159-162
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• 2001

In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.135-149
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• 2011

In this paper, we propose the high-risk group detection model for patients with high blood pressure using case-based reasoning. The proposed model can be applied for public health maintenance organizations to effectively manage knowledge related to high blood pressure and efficiently allocate limited health care resources. Especially, the focus is on the development of the model that can handle constraints such as managing large volume of data, enabling the automatic learning to adapt to external environmental changes and operating the system on a real-time basis. Using real data collected from local public health centers, the optimal high-risk group detection model was derived incorporating optimal parameter sets. The results of the performance test for the model using test data show that the prediction accuracy of the proposed model is two times better than the natural risk of high blood pressure.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.229-237
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• 2014

Background: Dentists are typically the first professionals who are approached to treat ailments within the oral cavity. Therefore they should be well-equipped in detecting suspicious lesions during routine clinical practice. This study determined the levels of knowledge on early signs and risk factors associated with oral cancer and identified which factors influenced dentist participation in prevention and early detection of oral cancer. Materials and Methods: A survey on dentists' knowledge and their practices in prevention and early detection of oral cancer was conducted using a 26-item self-administered questionnaire. Results and Conclusions: A response rate of 41.7% was achieved. The level of knowledge on early signs and risk habits associated with oral cancer was high and the majority reported to have conducted opportunistic screening and advised patients on risk habit cessation. Factors that influenced the dentist in practising prevention and early detection of oral cancer were continuous education on oral cancer, age, nature of practice and recent graduation. Notably, dentists were receptive to further training in the area of oral cancer detection and cessation of risk habits. Taken together, the study demonstrated that the dental clinic is a good avenue to conduct programs on opportunistic screening, and continuous education in these areas is necessary to adequately equip dentists in running these programs. Further, this study also highlighted knowledge deficits and practice shortcomings which will help in planning and developing programs that further encourage better participation of dentists in prevention and early detection of oral cancer.

• The Journal of the Korean dental association
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• v.52 no.8
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• pp.472-477
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• 2014

The new paradigm of dentistry require the detection of caries in their earlier stages. To achieve this, a high technology detection device and systematic and organized caries management system are needed. Caries management by risk assessment (CAMBRA) model is representative caries management system that satisfied new paradigm. Dental caries prevention and treatment according to CAMBRA model is patient-centered, risk-based, evidence-based practice. Therefore, individual caries management such as CAMBRA should be performed through accurate assessment of caries disease indicators and comprehensive assessment of caries risk factors and protective factors. Based on the CAMBRA better effectiveness of comprehensive dental caries management including non-surgical treatment will be accomplished.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.571-582
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• 2019

Purpose: To develop a risk metric for failure cause that can help determine the action priority of each failure cause in FMEA considering time sequence of cause- failure- detection. Methods: Assuming a quadratic loss function the unfulfilled mission period, a risk metric is obtained by deriving the failure time distribution. Results: The proposed risk metric has some reasonable properties for evaluating risk accompanied with a failure cause. Conclusion: The study may be applied to determining action priorities among all the failure causes in the FMEA sheet, requiring further studies for general situation of failure process.