• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.426-430
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• 1987

The reliability is the critical issue in many computer applications, particularly in process control system. In this paper we describe how to achieve the reliability improvement in controller system based multiprocessor. The proposed method is accomplished by using the techniques of fault detection, fault isolation, safe action, and fault diagnosis.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.13-20
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• 2009

Techniques for change detection using satellite images enable efficient detection of natural and artificial changes in use of land through multi-phase images. As for change detection, different results are made based on methods of calibration of satellite images, types of input data, and techniques in change analysis. Thus, an analytic technique that is appropriate to objectives of a study shall be applied as results are different based on diverse conditions even when an identical satellite and an identical image are used for change detection. In this study, Normalized Difference Vegetation Index (NDVI) and Principal Component Analysis (PCA) were conducted after geometric calibration of satellite images which went through absolute and relative radiometric calibrations and change detection analysis was conducted using Image Difference (ID) and Image Rationing (IR). As a result, ID-NDVI showed excellent accuracy in change detection related to vegetation. ID-PCA showed 90% of accuracy in all areas. IR-NDVI had 90% of accuracy while it was 70% and below as for paddies and dry fields${\rightarrow}$grassland. IR-PCA had excellent change detection over all areas.

• The Journal of Information Systems
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• v.15 no.4
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• pp.211-224
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• 2006

This study investigates the application of data mining techniques such as artificial neural networks, rough sets, and induction teaming to the intrusion detection systems. To maximize the effectiveness of data mining for intrusion detection systems, we introduced the asymmetric costs with false positive errors and false negative errors. And we present a method for intrusion detection systems to utilize the asymmetric costs of errors in data mining. The results of our empirical experiment show our intrusion detection model provides high accuracy in intrusion detection. In addition the approach using the asymmetric costs of errors in rough sets and neural networks is effective according to the change of threshold value. We found the threshold has most important role of intrusion detection model for decreasing the costs, which result from false negative errors.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.89-96
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• 2014

MANET has been applied to a wide variety of areas because it has advantages which can build a network quickly in a difficult situation to build a network. However, it is become a victim of malicious nodes because of characteristics such as mobility of nodes consisting MANET, limited resources, and the wireless network. Therefore, it is required to lightweight attack detection technique which can accurately detect attack without causing a large burden to the mobile node. In this paper, we propose a multistage attack detection techniques that attack detection takes place in routing phase and data transfer phase in order to increase the accuracy of attack detection. The proposed attack detection technique is composed of four modules at each stage in order to perform accurate attack detection. Flooding attack and packet discard or modify attacks is detected in the routing phase, and whether the attack by modification of data is detected in the data transfer phase. We assume that nodes have a public key and a private key in pairs in this paper.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.2
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• pp.359-363
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• 2019

As commercial drones have been widely used, concerns for collision accidents with people and invading secured properties are emerging. The detection of drone is a challenging problem. The deep learning based object detection techniques for detecting drones have been applied, but limited to the specific cases such as detection of drones from bird and/or background. We have tried not only detection of drones, but classification of different drones with an end-to-end model. YOLOv2 is used as an object detection model. In order to supplement insufficient data by shooting drones, data augmentation from collected images is executed. Also transfer learning from ImageNet for YOLOv2 darknet framework is performed. The experimental results for drone detection with average IoU and recall are compared and analysed.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.97-116
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• 2003

Frequency of attacks on web services and the resulting damage continue to grow as web services become popular. Techniques used in web service attacks are usually different from traditional network intrusion techniques, and techniques to protect web services are badly needed. Unfortunately, conventional intrusion detection systems (IDS), especially those based on known attack signatures, are inadequate in providing reasonable degree of security to web services. An application-level IDS, tailored to web services, is needed to overcome such limitations. The first step in developing web application IDS is to analyze known attacks on web services and characterize them so that anomaly-based intrusion defection becomes possible. In this paper, we classified known attack techniques to web services by analyzing causes, locations where such attack can be easily detected, and the potential risks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.68-80
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• 2013

Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.107-122
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• 2014

The DDoS attacks and the APT attacks occurred by the zombie computers simultaneously attack target systems at a fixed time, caused social confusion. These attacks require many zombie computers running attacker's commands, and unknown malware that can bypass detecion of the anti-virus products is being executed in those computers. A that time, many methods have been proposed for the detection of unknown malware against the anti-virus products that are detected using the signature. This paper proposes a method of unknown malware detection using digital forensic techniques and describes the results of experiments carried out on various samples of malware and normal files.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.585-591
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• 2020

The adaptive transmission techniques are efficient method for underwater acoustic communication to improve the system efficiency by varying transmission parameters according to channel conditions. In this paper, we construct four transmission modes with different data rates using the convolutional codes, which is freely set to size of information bits. On the receiver side, one critical component of adaptive system is to find which mode has best performance. In this paper, we proposed threshold detection algorithm to decide appropriate mode and applied turbo equalization method based on BCJR decoder in order to improve performance. We analyzed the performance of four modes based on threshold detection algorithm through the lake experiment.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.222-227
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• 2002

This research will examine into the capabilities of KOMPSAI-1 EOC image application in the field of urban environment and at the same time, with that as its foundation, come to understand the urban changes of the study areas. This research is constructed in three stages: Firstly, for application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, change detection method is applied fur the systematic monitoring of land use changes, which utilizes multi-temporal EOC images. Lastly, by using the results of the application of land use changes, the existing land use map is updated. Consequently, the land-use change patterns are monitored, which utilize multi-temporal panchromatic EOC image data; and application potentials of ancillary data fur updating existing data can be presented. In this research, with the use of the land use change, monitoring of urban growth has been carried out, and the potential for the application of KOMPSAT-1 EOC images and the scope of application was examined. Henceforth, the future expansion of the scope of application of KOMPSAT-1 EOC image is anticipated.