• Proceedings of the Korea Information Assurance Society Conference
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• 2004.05a
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• pp.327-331
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• 2004

The new cyber world has created by Internet that is prosperous rapidly. But with the expansion of Internet the hacking and intrusion are also increased very much. Actually there were many incidents in Internet, but the damage was restricted within a local area and local system. However, the Great 1.25 Internet Disturbance has paralyzed the national wide Internet environment. It because the Slammer Worm. The worm is a malformed program that uses both of the hacking and computer virus techniques. It autonomously attacks the vulnerability of Windows system, duplicates and spreads by itself. Jus like the Slammer Worm, almost every worms attack the vulnerability of Windows systems that installed in personal PC. Therefore, the vulnerability in personal PC could destroy the whole Internet world. So, in this paper we propose a Internet Worm Expanding Prevention System that could be installed in personal PC to prevent from expanding the Internet Worm. And we will introduce the results of developed system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.93-106
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• 2011

In this paper we describe an efficient and easy to use internet stopper, which is called AINS (Automatic Internet Stopper), which uses ARP spoofing scheme. Instead of forwarding packets to router for the case of hacking, in ARP spoofing, the AINS ignores all the packets so that internet stopping operates. The AINS program needs to be installed only in manager computer that does not require additional agent program. In addition to setting manually the stopping computer list, it is able to indentify network nodes automatically by analyzing broadcasting packets. The experimental results show that less than 4 secs for spoofing interval is enough for blocking internet usage regardless the number of computers and therefore network overhead is negligible. The AINS can indentify and control network nodes not only on same subnet but also on different subnet only if they are connected onto same ethernet switch physically. It is being used for an efficient tool for controling internet usage of university computer laboratory and also for an efficient network management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.701-720
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• 2023

Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.

• Korean Management Science Review
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• v.20 no.1
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• pp.25-36
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• 2003

Now that many organizations have invested a tremendous amount of money and efforts to operate Web sites on the Internet, there is a strong demand to understand the effectiveness of such investments. In other words, one of most frequent and important questions about their Web sites is "Will the current Web site management policy be effective enough to have more visitors come to our Web site\ulcorner" In this paper, a system which predicts the degree of user interest in the future to Web sites is constructed. The degree of user interest to a Web site is defined to be the visit counts for the Web site in the system. With higher the visit counts, the related site is considered to be more interesting. However, the figures of the visit counts themselves cannot explain properly the degree of user Interest in the future to the related Web sites (i.e. the effectiveness of the related Web sites). Therefore, the system also uses mechanisms which use the concept of the Moving Averages, which have been used frequently in the stock exchanges. In this paper. two prediction mechanisms are proposed and compared. The first mechanism uses the Golden Cross/the Dead Cross of the Moving Averages, while the second mechanism uses the changes of upward/downward direction of the Moving Averages. Experimental results show that the two prediction mechanisms proposed in this paper predict the degree of user interest in the future to the related Web sites very well in most cases. However, the first one is considered to be better than the second one In the sense that the second one is too much sensitive to the changes of visit counts.it counts.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.195-202
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• 2013

Many communications and broadcast media have emerged by the rapid development of wireless communication and broadcasting technologies, so the radio resources are insufficient for these services. DMB can use the regional integrated channel due to the SFN broadcasting network, so DMB uses the frequency efficiently. However, the domestic DMB uses the existing analog TV frequency band and uses a plurality of channels in some areas because of the interference with the analog TV. However, the broadcasting of the analog TV was terminated, so the channel reallocation of the terrestial DMB is necessary for the efficient use of frequencies. This paper proposes the channel reallocation method of the terrestial DMB and analyzes the change of transmission and reception environments by using simulations.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.47-53
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• 2017

In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.91-99
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• 2018

A growing body of research has focused on the negative effects of Internet gaming. This issue has become an increased public health concern in Korea. However, little is known regarding the positive effect of Internet gaming and its etiology. This study examined the effects of gaming motivations on gaming behaviors based on self-determination theory. Specifically, we investigated the associations of intrinsic and extrinsic gaming motivations with adaptive and maladaptive game uses. A cross-sectional data collected from a sample of 3,000 young adults using 2016 Korean Video Gaming Survey was analyzed. Measurement model analysis and structural equation modeling were conducted as primary analyses. The findings highlight the different effects of intrinsic and extrinsic motivations on gaming behaviors, such as adaptive and maladaptive game uses. Intrinsic motivations, such as experience-seeking and achievement-seeking, were associated with adaptive game use. Meanwhile, extrinsic motivations, such as sensation-seeking and monetary reward-seeking, were associated with maladaptive game use. The findings provide a better understanding of video gaming in light of both adaptive and maladaptive game uses. The implications for practice and policy were discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.99-105
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• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.113-118
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• 2017

As interest in mobile devices and networks has increased recently, voice over internet protocol (VoIP) service, which is a technology for transmitting voice data using an existing internet protocol (IP) network, has rapidly spread, Cheap voice call service has become possible. As the digital broadcasting service becomes popular, hybrid fiber coaxial (HFC) network technology, which uses broadband cable network through fusion of broadcasting and communication, utilizes existing communication system and network equipment to provide various new services such as interactive broadcasting service. Therefore, if UGS-AD is applied to VoCM and RTPS is applied to MTA in order to guarantee the quality of voice data in actual HFC Internet service network, it is possible to smoothly perform voice data transmission in narrow upstream band which is a problem in actual commercial HFC network We also proposed a method to improve VoIP service by improving QoS of voice data in HFC Internet service network.