• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.151-157
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• 2014

Diverse and complex facilities have been on the increase in urban areas in accordance with rapid urbanization. Along the lines of the increase in facilities, the risk of fire has increased. In particular, fire accidents as well as traffic accidents accounted for the highest rate in artificial disasters. Therefore, the National Fire Information Systems managed by the National Emergency Management Agency (NEMA) appeared for the effective fire management. The NEMA has provided the public with the Internet services regarding information about fire outbreak since 2007. This study acquired data from both NEMA and the Jinju City Fire Department. It constructed the fire data of Jinju City and calculated the change in spatial density targeting fire, occurred in Jinju city with a view to examining the fire risk of facilities by conducting a time series analysis on the trends of fire outbreak over a span of periods between 2007 and 2013. It also conducted an analysis of Moran's I, Getis-Ord Gi. Therefore, it came to select higher hot spots in terms of fire location and fire density. In addition, it attempted to calculate the levels of fire hazard by drawing up the matrix of personal injury and property damage, depending on facilities to present the methods, which can predict the risk of fire occurrence in urban areas.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.414-428
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• 2004

Many portable devices are coming to be commercially successful and provide useful services to mobile users. Mobile devices may request a variety of data types, including text and multimedia data, thanks to the rich content of the Internet. Different types of data and/or different classes of users may need to be treated with different qualities of service. The implementation of service differentiation in wireless networks is very difficult because of device mobility and wireless channel contention when the backoff algorithm is used to resolve contention. Modification of the t)mary exponential backoff algorithm is one possibility to allow the design of several classes of data traffic flows. We present a study of modifications to the backoff algorithm to support three classes of flows: sold, silver, and bronze. For example, the gold c]ass flows are the highest priority and should satisfy their required target bandwidth, whereas the silver class flows should receive reasonably high bandwidth compared to the bronze class flows. The mixture of the two different transport protocols, UDP and TCP, in ad hoc networks raises significant challenges when defining backoff algorithm modifications. Due to the different characteristics of UDP and TCP, different backoff algorithm modifications are applied to each class of packets from the two transport protocols. Nevertheless, we show by means of simulation that our approach of backoff algorithm modification clearly differentiates service between different flows of classes regardless of the type of transport protocol.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

• Journal of KIISE
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• v.41 no.10
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• pp.810-823
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• 2014

The wireless mesh network based on IEEE 802.11s provides a routing based on a destination address as it inherits legacy internet architecture. However, this architecture interested in not 'what' which is originally the users goal but 'where'. Futhermore, because of the rapid increase of the number of mobile devices recently, the mobile traffic increases geometrically. It reduces the network effectiveness as increasing many packets which have same payload in the situation of many users access to the same contents. In this paper, we propose an OpenFlow-based contents routing for the wireless mesh network(WMN) to solve this problem. We implement contents layer to the legacy network layer which mesh network uses and the routing technique based on contents identifier for efficient contents routing. In addition we provide flexibility as we use OpenFlow. By using this, we implement caching technique to improve effectiveness of network as decreasing the packet which has same payload in WSN. We measure the network usage to compare the flooding technique, we measure the delay to compare environment using caching and non caching. As a result of delay measure it shows 20% of performance improve, and controller message decrease maximum 89%.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.123-140
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• 2009

Collaborative filtering recommends products using customers' preferences, so it cannot recommend products to the new customer who has no preference information. This paper proposes a novel approach to new customer recommendations using the social network analysis which is used to search relationships among social entities such as genetics network, traffic network, organization network, etc. The proposed recommendation method identifies customers most likely to be neighbors to the new customer using the centrality theory in social network analysis and recommends products those customers have liked in the past. The procedure of our method is divided into four phases : purchase similarity analysis, social network construction, centrality-based neighborhood formation, and recommendation generation. To evaluate the effectiveness of our approach, we have conducted several experiments using a data set from a department store in Korea. Our method was compared with the best-seller-based method that uses the best-seller list to generate recommendations for the new customer. The experimental results show that our approach significantly outperforms the best-seller-based method as measured by F1-measure.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.145-154
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• 2004

The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7292-7301
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• 2014

With the development of IT Info-Communications technology, the vehicle with a combination of wireless-communication technology has resulted in significant research into the convergence of the component of existing traffic with information, electronics and communication technology. Intelligent Vehicle Communication is a Machine-to-Machine (M2M) concept of the Vehicle-to-Vehicle. The Vehicle-to-Infrastructure communication consists of safety and the ease of transportation. Security technologies must precede the effective Intelligent Vehicle Communication Structure, unlike the existing internet environment, where high-speed vehicle communication is with the security threats of a wireless communication environment and can receive unusual vehicle messages. In this paper, the Vehicle Identification number between the V2I and the secure message communication protocol was proposed using hash functions and a time stamp, and the validity of the vehicle was assessed. The proposed system was the performance evaluation section compared to the conventional technique at a rate VPKI aspect showed an approximate 44% reduction. The safety, including authentication, confidentiality, and privacy threats, were analyzed.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.10 s.352
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• pp.8-17
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• 2006

Recently, the high-speed Internet users increase rapidly and broadband networks have been widely deployed. However, the current TCP congestion control algorithm was designed for relatively narrowband network environments, and thus its performance is inefficient for traffic transport in broadband networks. To remedy this problem, the TCP having an enhanced congestion control algorithm is required for broadband networks. In this paper, we propose an improved TCP congestion control that can sufficiently utilize the large available bandwidth in broadband networks. The proposed algorithm predicts the available bandwidth by using ACK information and RTT variation, and prevents large packet losses by adjusting congestion window size appropriately. Also, it can rapidly utilize the large available bandwidth by enhancing the legacy TCP algorithm in congestion avoidance phase. In order to evaluate the performance of the proposed algorithm, we use the ns-2 simulator. The simulation results show that the proposed algorithm improves not only the utilization of the available bandwidth but also RTT fairness and the fairness between contending TCP flows better than the HSTCP in high bandwidth delay product network environment.

• Korean journal of communication and information
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• v.26
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• pp.259-289
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• 2004

In this study, the use of mainstream online news site and alternative online news site were compared in the aspects of users' characteristics, attitude on online news sites, and using pattern. A survey was conducted for 182 mainstream-only users, 46 alternative online news users, and 47 both sites users, Also, their traffic data of online news sites were analyzed during the 16th presidential election. As a result, it was found that both sites users had the highest political interest and the most progressive political position among the user groups. In the aspect of users' attitude, mainstream-only users were most positive to the mainstream online news site and both sires users were most positive and more involved in alternative online news site. But all user groups set higher credibility on alternative online news site than mainstream online news sire. In the comparison of user size, mainstream online news site has larger user size than alternative online site. However, the user royalty, such as time per person, pages per person, and visiting days per person, was lower than that of the latter. These results suggest thar small but differentiated news sires have royal users, and online news users be segmented according to news contents.