• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.326-330
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• 2012

In 2011, There were about 25,000 people died because of heart disease. The aim of this paper is to design a heart attack situation monitoring and spreading system for patients. Wearable computer with a sensor is used to monitor heart rate. Heart rate is transffered to smartphone with bluetooth. After analyzing heart rate, smartphone spread out the emergency situation by various service including emergency call, SNS and SMS.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.17-22
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• 2017

In this paper, a password recognition system that can overcome a shoulder-surfing attack is developed. During the time period of password insertion, the developed system can prevent the attack and enhance the safety of the password. In order to raise the detection rate of the password image, the mopology technique is utilized. By adapting 4 times of the expansion and dilation, the niose from the binary image of the password is removed. Finally, the mobile phone application is also developed to recognize the one time password and the detection rate is measured. It is shown that the detection rate of 90% is achieved under the dark light condition.

• Fire Science and Engineering
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• v.24 no.5
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• pp.26-31
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• 2010

In this study, attack process and aerial control line construction type which were considered forest fire type and a case of operations were suggested using the experience of aerial fire attack of all type of forest fires. As the spread rate of forest fire is effected by terrain, slope, wind speed, forest species and etc., we needed to analyze spreading direction, behavior type and intensity before heli-team constructed a aerial control line. Especially, It is important to consider safety of attack team as a their views were obstructed. In this study, we suggested a 13 methods from type A to type M about attack and construction of aerial indirect control line.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.1014-1028
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• 2017

Social networking services (SNSs) such as Twitter, MySpace, and Facebook have become progressively significant with its billions of users. Still, alongside this increase is an increase in security threats such as cross-site scripting (XSS) threat. Recently, a few approaches have been proposed to detect an XSS attack on SNSs. Due to the certain recent features of SNSs webpages such as JavaScript and AJAX, however, the existing approaches are not efficient in combating XSS attack on SNSs. In this paper, we propose a machine learning-based approach to detecting XSS attack on SNSs. In our approach, the detection of XSS attack is performed based on three features: URLs, webpage, and SNSs. A dataset is prepared by collecting 1,000 SNSs webpages and extracting the features from these webpages. Ten different machine learning classifiers are used on a prepared dataset to classify webpages into two categories: XSS or non-XSS. To validate the efficiency of the proposed approach, we evaluated and compared it with other existing approaches. The evaluation results show that our approach attains better performance in the SNS environment, recording the highest accuracy of 0.972 and lowest false positive rate of 0.87.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.89-98
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• 2022

As deep learning technology was applied to various fields, research on adversarial attack techniques, a security problem of deep learning models, was actively studied. adversarial attacks have been mainly studied in the field of images. Recently, they have even developed a complete decision-based attack technique that can attack with just the classification results of the model. However, in the case of the audio field, research is relatively slow. In this paper, we applied several decision-based attack techniques to the audio field and improved state-of-the-art attack techniques. State-of-the-art decision-attack techniques have the disadvantage of requiring many queries for gradient approximation. In this paper, we improve query efficiency by proposing a method of reducing the vector search space required for gradient approximation. Experimental results showed that the attack success rate was increased by 50%, and the difference between original audio and adversarial examples was reduced by 75%, proving that our method could generate adversarial examples with smaller noise.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.23-35
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• 2015

When people stands near someone's mobile device, it can easily be seen by others. To rephrase this, attackers use human psychology to earn personal information or credit information or other. People are exposed by social engineering attacks. It is certain that we need more than just recommendation for the security to avoid social engineering attacks. This is why I proposed this paper. In this paper, I proposed an authentication technique using NFC and Hash function to stand against social engineering attack. Proposed technique result is showing that it could prevent shoulder surfing, touch event information, spyware attack using screen capture and smudge attack which relies on detecting the oily smudges left behind by user's fingers. Besides smart phone, IPad, Galaxy tab, Galaxy note and more mobile devices has released and releasing. And also, these mobile devices usage rate is increasing widely. We need to attend these matters and study in depth.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.391-394
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• 2004

Change of paradigm of network attack technique was begun by fast extension of the latest Internet and new attack form is appearing. But, Most intrusion detection systems detect informed attack type because is doing based on misuse detection, and active correspondence is difficult in new attack. Therefore, to heighten detection rate for new attack pattern, visibilitys to apply human immunity mechanism are appearing. In this paper, we create self-file from normal behavior profile about network packet and embody self recognition algorithm to use self-nonself discrimination in the human immune system to detect anomaly behavior. Sense change because monitors self-file creating anomaly detector based on Negative Selection Algorithm that is self recognition algorithm's one and detects anomaly behavior. And we achieve simulation to use DARPA Network Dataset and verify effectiveness of algorithm through the anomaly detection rate.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.154-158
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• 2000

Hydraultic experiments were performed in 2-D were flume to investigate the stability o the breakwaters, the destruction of armor blocks and overtopping under irregular wave attack on the structures armored by \`Core-Loc\`. Overtopping rate and stability were examined and compared when armored by Core-Loc and by T.T.P. Results shows both type of blocks are stable and overtopping rates are similar in the adopted experimental condition. Therefore Core-Loc can replace some portion of T.T.P. which is uniquely used in Korea. Further integrated experimental data with Core-loc are need for destruction mechanism or overtopping rate.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.1
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• pp.67-74
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• 2020

Objectives: Previous study has shown that the positive rate of latent tuberculosis infection(LTBI) among former workers in dusty environments was higher than that among high-risk groups of tuberculosis(TB). The objective of the present study was to identify the development of active TB among former workers in dusty environments diagnosed with LTBI. Methods: Between January 2015 and May 2017, 796 former workers in dusty environments who had been subjects of epidemiology research for work-related chronic obstructive pulmonary disease(COPD) had received the QuantiFERON-TB® Gold In-Tube(QFT-GIT) from the Institute of Occupation and Environment(IOE) under the Korea Workers' Compensation and Welfare Service(KCOMWEL). Among them, 437 participants who received a health examination for work-related pneumoconiosis between January 2015 and December 2018 were selected as study subjects. Active TB was defined as a positive result for active PTB and non-tuberculosis mycobacteria infection in the result of the Pneumoconiosis Examination Council's assessment by KCOMWEL. Results: A total of 437 subjects were followed up for 2.1 years. Four of them(4/437, 0.9%) developed active TB during the follow-up period. The attack rate of active TB among subjects who were diagnosed LTBI positive and those who were diagnosed LTBI negative were 0.9%(3/320) and 0.9%(1/115), respectively. Conclusions: Most previous studies reported that the attack rate of the development of active TB in subjects who had been diagnosed LTBI positive was higher than that among subjects who had been diagnosed LTBI negative. To the contrary, the present study found that the rate of developing active TB among former workers in dusty environments diagnosed as LTBI positive was not higher than that in those who were diagnosed LTBI negative.