• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.156-165
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• 2006

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-imbedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18$\%$ on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.918-928
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• 2007

The goal of this paper is to propose a new way to register CDA documents in CDR (Clinical Document Repository) that is proposed by the author earlier. One of the methods is to use a manifest archiving for seamless references and visualization of CDA related files. Another method is to enhance the CDA security level for supporting pseudonymization of CDA. The former is a useful method to support the bundled registration of CDA related files as a set. And it also can provide a seamless presentation view to end-users, once downloaded, without each HTTP connection. The latter is a new method of CDA registration which can supports a do-identification of a patient. Usually, CDA header can be used for containing patient identification information, and CDA body can be used for diagnosis or treatment data. So, if we detach each other, we can get good advantages for privacy protection. Because even if someone succeeded to get separated CDA body, he/she never knows whose clinical data that is. The other way, even if someone succeeded to get separated CDA header; he/she doesn't know what kind of treatment has been done. This is the way to achieve protecting privacy by disconnecting association of relative information and reducing possibility of leaking private information. In order to achieve this goal, the method we propose is to separate CDA into two parts and to store them in different repositories.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.603-614
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• 2013

The popularity of mobile devices provides their users with a circumstance that services and information can be accessed wherever and whenever users need. Accordingly, various studies have been proposed personalized methods to improve accessibility of mobile users to information. However, since these personalized methods require users' private information, they gives rise to problems on security. An efficient way to resolve security problems is to estimate user information by using their online and offline behavior. In this paper, for this purpose, it is proposed a novel user information identification system that identifies users' personal and social information by using both his/her behavior on social network services and proximity patterns obtained from GPS data. In the proposed system, personal information of a user like age, gender, and so on is estimated by analyzing SNS texts and POI (Point of Interest) patterns, while social information between a pair of users like family and friend is predicted with proximity patterns between the users. Each identification module is efficiently designed to handle the characteristics of user data like much noise in SNS texts and missing signals in GPS data. In experiments to evaluate the proposed system, our system shows its superiority against ordinary identification methods. This result means that the proposed system can efficiently reflect the characteristics of user data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.634-642
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• 2020

With the proliferation of Internet of Things (IoT) devices, using the Linux operating system in various architectures has increased. Also, security threats against Linux-based IoT devices are increasing, and malware variants based on existing malware are constantly appearing. In this paper, we propose a system where the binary data of a visualized Executable and Linkable Format (ELF) file is applied to Local Binary Pattern (LBP) image processing techniques and a median filter to classify malware in a Convolutional Neural Network (CNN). As a result, the original image showed the highest accuracy and F1-score at 98.77%, and reproducibility also showed the highest score at 98.55%. For the median filter, the highest precision was 99.19%, and the lowest false positive rate was 0.008%. Using the LBP technique confirmed that the overall result was lower than putting the original ELF file through the median filter. When the results of putting the original file through image processing techniques were classified by majority, it was confirmed that the accuracy, precision, F1-score, and false positive rate were better than putting the original file through the median filter. In the future, the proposed system will be used to classify malware families or add other image processing techniques to improve the accuracy of majority vote classification. Or maybe we mean "the use of Linux O/S distributions for various architectures has increased" instead? If not, please rephrase as intended.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.10-18
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• 2011

Medical asset protection is important in each medical institution especially because of the law on private medical record protection and face recognition for this protection is one of the most interesting and challenging problems. In recognizing human faces, the distortion of face images can be caused by the change of pose, illumination, expressions and scale. It is difficult to recognize faces due to the locations of lights and the directions of lights. In order to overcome those problems, this paper presents an analysis of coefficients of Gabor wavelets, kernel decision, feature point, size of kernel, for face recognition in CCTV surveillance. The proposed method consists of analyses. The first analysis is to select of the kernel from images, the second is an coefficient analysis for kernel sizes and the last is the measure of changes in garbo kernel sizes according to the change of image sizes. Face recognitions are processed using the coefficients of experiment results and success rate is 97.3%. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved in the face recognition area.

• Tunnel and Underground Space
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• v.25 no.2
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• pp.199-209
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• 2015

The rebound hardness test using the SilverSchmidt hammer was performed for diorite, granodiorite, and andesite exposed around the King Sejong Station, Barton peninsula. Then, the R-value and uniaxial compressive strength (UCS) of these rocks were estimated from the Q-values which were obtained from the SilverSchmidt hammer. The Q-value of diorite was distributed in the range from 67.0 to 89.5, granodiorite of the range from 57.5 to 89.0, and andesite of the range from 58.0 to 76.5. The average Q-values of diorite, granodiorite, and andesite were 76.0, 72.0, and 67.0, respectively. The converted UCS of diorite was distributed in the range from 118 to 195 MPa, granodiorite of the range from 91 to 193 MPa, and andesite of the range from 92 to 148 MPa. The average UCS of diorite, granodiorite, and andesite were 147, 136, and 117 MPa, respectively. The converted R-value of diorite was distributed in the range from 53.0 to 72.2, granodiorite of the range from 45.4 to 71.8, and andesite of the range from 45.8 to 60.9. The average Q-values of diorite, granodiorite, and andesite were 60.0, 58.0, and 53.0, respectively. The R-value was represented approximately 20% lower than the Q-value. In conclusion, it will be possibile that the R-value and UCS of rocks under the extreme area from the SilverSchmidt Q-value are evaluated.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.11-26
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• 2013

In the wireless Internet, it is so restrictive to use the IPSec. The MIPv4 IPSec's path cannot include wireless links. That is, the IPSec of the wireless Internet cannot protect an entire path of Host-to-Host connection. Also wireless circumstance keeps a path static during the shorter time, nevertheless, the IKE for IPSec SA agreement requires relatively long delay. The certificate management of IPSec PKI security needs too much burden. This means that IPSec of the wireless Internet is so disadvantageous. Our paper is to construct the Mobile IPSec proper to the wireless Internet which provides the host-to-host transport mode service to protect even wireless links as applying excellent WP-IBE scheme. For this, Mobile IPSec requires a dynamic routing over a path with wireless links. FA Forwarding is a routing method for FA to extend the path to a newly formed wireless link. The FA IPSec SA for FA Forwarding is updated to comply the dynamically extended path using Source Routing based Bind Update. To improve the performance of IPSec, we apply efficient and strong future Identity based Weil Pairing Bilinear Elliptic Curve Cryptography called as WP-IBE scheme. Our paper proposes the modified protocols to apply 6 security-related algorithms of WP-IBE into the Mobile IPSec. Particularly we focus on the protocols to be applied to construct ESP Datagram.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.226-234
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• 2007

In this paper, we develop a speech recognition system using a throat microphone. The use of this kind of microphone minimizes the impact of environmental noise. However, because of the absence of high frequencies and the partially loss of formant frequencies, previous systems developed with those devices have shown a lower recognition rate than systems which use standard microphone signals. This problem has led to researchers using throat microphone signals as supplementary data sources supporting standard microphone signals. In this paper, we present a high performance ASR system which we developed using only a throat microphone by taking advantage of Korean Phonological Feature Theory and a detailed throat signal analysis. Analyzing the spectrum and the result of FFT of the throat microphone signal, we find that the conventional MFCC feature vector that uses a critical pass filter does not characterize the throat microphone signals well. We also describe the conditions of the feature extraction algorithm which make it best suited for throat microphone signal analysis. The conditions involve (1) a sensitive band-pass filter and (2) use of feature vector which is suitable for voice/non-voice classification. We experimentally show that the ZCPA algorithm designed to meet these conditions improves the recognizer's performance by approximately 16%. And we find that an additional noise-canceling algorithm such as RAST A results in 2% more performance improvement.

• Smart Media Journal
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• v.4 no.4
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• pp.24-32
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• 2015

Recently, SDN is actively used as datacenter networks and gradually increase its applied areas. Along with this change of networking environment, research of deploying network security systems on SDN becomes highlighted. Especially, systems for detecting network flooding attacks by monitoring every packets through ports of OpenFlow switches have been proposed. However, because of the centralized management of a SDN controller which manage multiple switches, it may be substantial overhead that the attack detection system continuously monitors all the flows. In this paper, a sampling based network flooding attack detection and prevention system is proposed to reduce the overhead of monitoring packets and to achieve reasonable functionality of attack detection and prevention. The proposed system periodically takes sample packets of network flows with the given sampling conditions, analyzes the sampled packets to detect network flooding attacks, and block the attack flows actively by managing the flow entries in OpenFlow switches. As network traffic sampler, sFlow agent is used, and snort, an opensource IDS, is used to detect network flooding attack from the sampled packets. For active prevention of the detected attacks, an OpenDaylight application is developed and applied. The proposed system is evaluated on the local testbed composed with multiple OVSes (Open Virtual Switch), and the performance and overhead of the proposed system under various sampling condition is analyzed.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.21-35
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• 2009

KOMPSAT-2 is the seventh high-resolution image satellite in the world that provides both 1m-grade panchromatic images of the GSD and 4m-grade multispectral images of the GSD. It's anticipated to be used across many different areas including mapping, territory monitoring and environmental watch. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric images, such as satellite orbits and detailed mapping information. Therefore, this study aims to produce DEM and orthoimage by using the stereo images of KOMPSAT-2, and to explore the applicability of geo-spatial information with KOMPSAT -2. Orientation interpretations were essential for the production of DEM and orthoimage using KOMPSAT-2 images. In the study, they are performed by utilizing both RPC and GCP. In this study, the orientation interpretations are followed by the generation of DEM and orthoimage, and the analysis of their accuracy based on a 1:5,000 digital map. The accuracy analysis of DEM is performed and the results indicate that their altitudes are, in general, higher than those obtained from the digital map. The altitude discrepancies on plains, hills and mountains are calculated as 1.8m, 7.2m, and 11.9m, respectively. In this study, the mean differences between horizontal position between the orthoimage data and the digital map data are found to be ${\pm}3.081m$, which is in the range of ${\pm}3.5m$, within the permitted limit of a 1:5,000 digital map. KOMPSAT-2 images are used to produce DEM and orthoimage in this research. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.