• Title/Summary/Keyword: smart card data

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Relationship between Diurnal Patterns of Passenger Ridership and Passenger Trip Chains on the Metropolitan Seoul Metro System (수도권 광역도시철도 하루 시간대별 이용 빈도에 의해 구분된 역 집단과 통행자의 통행 연쇄 패턴 간 관계)

  • Lee, Keum-Sook;Park, Jong-Sook;Kim, Ho-Sung;Joh, Chang-Hyeon
    • Journal of the Korean Geographical Society
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    • v.45 no.5
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    • pp.592-608
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    • 2010
  • This study investigates the diurnal pattern of transit ridership in the Metropolitan Seoul area. For the purpose, we use a weekday Smart Card passenger transaction data in 2005. Eleven passenger trip patterns are found from 2.74 million passengers moving on the Metropolitan Seoul Metro system. Among them, we analyze 2.4 million passengers blonging to five trip types having only one or two transaction record during a day. A total of 357 metro stations are classified to four types according to their diurnal pattern of passenger riderships. We analyze the relationships between passenger's trip chain patterns and subway station's diurnal transit ridership patterns. The result shows that the ratio of the number of passengers of particular time of the day is hierarchically related with trip chain patterns.

e-Passport Security Technology using Biometric Information Watermarking (바이오정보 워터마킹을 이용한 전자여권 보안기술)

  • Lee, Yong-Joon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.4
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    • pp.115-124
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    • 2011
  • There has been significant research in security technology such as e-passport standards, as e-passports have been introduced internationally. E-passports combine the latest security technologies such as smart card, public key infrastructure, and biometric recognition, so that these technologies can prevent unauthorized copies and counterfeits. Biometric information stored in e-passports is the most sensitive personal information, and it is expected to bring the highest risk of damages in case of its forgery or duplication. The present e-passport standards cannot handle security features that verify whether its biometric information is copied or not. In this paper, we propose an e-passport security technology in which biometric watermarking is used to prevent the copy of biometric information in the e-passport. The proposed method, biometric watermarking, embeds the invisible date of acquisition into the original data during the e-passport issuing process so that the human visual system cannot perceive its invisibly watermarked information. Then the biometric sample, having its unauthorized copy, is retrieved at the moment of reading the e-passport from the issuing database. The previous e-passport security technology placed an emphasis on both access control readers and anti-cloning chip features, and it is expected that the proposed feature, copy protection of biometric information, will be demanded as the cases of biometric recognition to verify personal identity information has increased.

Outlier Detection Method for Mobile Banking with User Input Pattern and E-finance Transaction Pattern (사용자 입력 패턴 및 전자 금융 거래 패턴을 이용한 모바일 뱅킹 이상치 탐지 방법)

  • Min, Hee Yeon;Park, Jin Hyung;Lee, Dong Hoon;Kim, In Seok
    • Journal of Internet Computing and Services
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    • v.15 no.1
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    • pp.157-170
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    • 2014
  • As the increase of transaction using mobile banking continues, threat to the mobile financial security is also increasing. Mobile banking service performs the financial transaction using the dedicate application which is made by financial corporation. It provides the same services as the internet banking service. Personal information such as credit card number, which is stored in the mobile banking application can be used to the additional attack caused by a malicious attack or the loss of the mobile devices. Therefore, in this paper, to cope with the mobile financial accident caused by personal information exposure, we suggest outlier detection method which can judge whether the transaction is conducted by the appropriate user or not. This detection method utilizes the user's input patterns and transaction patterns when a user uses the banking service on the mobile devices. User's input and transaction pattern data involves the information which can be used to discern a certain user. Thus, if these data are utilized appropriately, they can be the information to distinguish abnormal transaction from the transaction done by the appropriate user. In this paper, we collect the data of user's input patterns on a smart phone for the experiment. And we use the experiment data which domestic financial corporation uses to detect outlier as the data of transaction pattern. We verify that our proposal can detect the abnormal transaction efficiently, as a result of detection experiment based on the collected input and transaction pattern data.

A Study on the Optimization of Suwon City Bus Route using GWR Model (GWR모델 이용한 수원시 일반버스노선 최적화에 관한 연구)

  • Park, Cheol Gyu;Cho, Seong Kil
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.1
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    • pp.41-46
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    • 2014
  • Bus service is easily adjusted to accommodate the changed demand. Despite the flexibility of that, its relocation should overcome the following problems: first, Bus line rearrangement should consider the balance between the demand and the supply to enhance the transit equity among the users scattered around the area that supply against demand imbalances. Second, the existing demand analysed is to crude since the demand was analysed based on TAZ. mainly based on the Dong unit. Utilization of the GWR and GIS-T data can resolve the problem. In this paper, the limitation of the conventional transit demand analysis model is overcome by deploying the GWR model which identifies the transit demand based on the geographic relation between the service location and those of the users. GWR model considers the spatial effect of the bus demand in accordance with the distance to the each bus stops using SCD(Smart Card Data) and BIS(Bus Information System). This demand map was then superimposes with the existing bus route which identified the areas where the balance between demand and supply is severly skewed. since the analysis was computed with SCD and BIS at every bus stops. the shortage and surplus of bus service of entire study area could computed. Further. based on this computational result and considering the entire bus service capacity data. Bus routes optimization from the oversupplied areas to the undersupplied area was illustrated thus this study clearly compared the benefits the GIS.

Status and prospects of Knowledge Information Security Industry (지식정보보안 산업의 현황과 전망)

  • Choi, Jeong-Il;Chang, Ye-Jin;Lee, Ok-Dong
    • Korean Security Journal
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    • no.39
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    • pp.269-294
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    • 2014
  • Korea is concerned with information security industry due to recent leak-out private information of 3 card companies. Executives are aware of damage from breach of security such as personal data spill, is more dangerous than any other financial risks. The information security industry, which was limited in physical security and network security formerly, is evolving into convergence security of public and facility security industry. The field of interest has also been changed into security of smart phone and intelligence image recently, from firewall or Anti-virus. The convergence security is originally about access control of facility, but recently its demand has been increased mostly by public institutions and major companies. The scope of the industry also varies from finance, education, distribution, national defense, medical care to automobile industry. The market of convergence security has been expanded and new various products and services of security of intelligent vehicle, 'U' healthcare, finance, smart grid and key industries are also developed. It is required to create and enhance of new curriculum and cultivate human resources for the development of knowledge information security industry. Raising standard of education and security consciousness of the nation is also necessary to strengthen the global competitiveness.

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Analysis of Spatial Trip Regularity using Trajectory Data in Urban Areas (도시부 경로자료를 이용한 통행의 공간적 규칙성 분석)

  • Lee, Su jin;Jang, Ki tae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.6
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    • pp.96-110
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    • 2018
  • As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

A Statistical Fitness Test of Newell's 3-detector Simplification Method for Unexpected Incident Detection in the Expressway Traffic Flow (고속도로 돌발상황 검지를 위한 삼연속검지기 단순화 해법의 통계적 적합성 검정)

  • OH, Chang-Seok;RHO, Jeong Hyun;PARK, Young Wook
    • Journal of Korean Society of Transportation
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    • v.34 no.2
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    • pp.146-157
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    • 2016
  • The objective of this study is to actualize a statistical model of the 3-detector simplification model, which was proposed to detect outbreak situations by Daganzo in 1997 and to verify the statistical appropriacy thereof. This study presents the calculation process of the 3-detector simplification model and realizes the process using a statistics program. Firstly, the model was applied using data on detector of the main highways on which there is no entrances or exits. Moreover, in order to statistically verify the 3-detector simplification model, accumulative traffics for 30 seconds period, which reflects the dynamic changes of traffics due to shock wave, were estimated for outbreak traffics and steady flow, and the error of acquired data was statistically compared with that of the actual accumulative traffics. As a result, the error ratio between steady and incident cumulative flows has reached its maximum after 2-3 hours from an accident. Moreover, the incident traffic flows by accidents and the stade flows are heterogeneous in terms of their dispersion and means.

Impacts of Land Use and Urban Design Characteristics on Transit Ridership in the Seoul Rail Station Areas (서울시 역세권에서의 토지이용 및 도시설계특성이 대중교통이용증대에 미치는 영향 분석)

  • Sung, Hyung-Gon;Kim, Dong-Jun;Park, Jee-Hyung
    • Journal of Korean Society of Transportation
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    • v.26 no.4
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    • pp.135-147
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    • 2008
  • One of the efforts both to prevent urban sprawling development patterns and to promote use of public transportation is known as Transit-Oriented Development (TOD), including such planning elements as the density and diversity of land use and pedestrian-friendly urban design around a transit center. The aim of this study is thus to conduct impact analyses of TOD planning elements on transit ridership in the Seoul rail station areas. First, the authors investigate and draw out various actual elements of TOD planning by using GIS-based data and Smart Card data. Then the authors analyze impacts of TOD planning elements on transit ridership for the Seoul rail station areas. After condensing 34 variables presumably influencing transit ridership into seven factors by using factor analyses, the study utilizes multiple regression modeling methods to identify their impacts on transit ridership. The analysis results demonstrate that transit ridership tends to increase more in rail station areas where there is a non-residential high density, mixed use of land and narrow and small-size road network patterns. The implementation of TODs should be a useful method in inducing a Transit-Oriented City through redevelopment and new development.

Establishment and Application of Subway Line Chain OD Using SSA (SSA를 이용한 지하철 노선 Chain OD 구축 및 활용)

  • Lee, Mee Young;Nam, Doohee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.5
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    • pp.100-111
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    • 2019
  • The existing selected station analysis (SSA) method analyzes the link transfer mode data between origin and destination of individuals passing through stations from a microscopic standpoint. As such, existing SSA is insufficient as it uses integrated analysis using macroscopic data such as subway lines. This research builds a line chain OD based on path search of individual passenger's movement through the subway, and explores means to utilize the findings. First, a method is proposed that searches the traversed subway path from the linked passage modes that the passenger uses and applies the results to SSA line analysis. Compared to the existing SSA, this method provides for analysis of commonly conflicting features such as the line on which the station is passed, and the stations included on the line thanks to the presence of complete information of the individual passenger's traversed path. It also allows for integrated observation of the line chain OD that approaches a certain station. For enhanced understanding, Seoul Metro Line 9 is used as a case study to demonstrate the integrated formulation concept of line chain OD centered around a certain station as well as the macroscopic features of the traversed path that approaches stations included on the line.

A Study on the Regional Characteristics of Broadband Internet Termination by Coupling Type using Spatial Information based Clustering (공간정보기반 클러스터링을 이용한 초고속인터넷 결합유형별 해지의 지역별 특성연구)

  • Park, Janghyuk;Park, Sangun;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.45-67
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    • 2017
  • According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.