• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.383-388
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• 2006

Most of GIS services have been operated in single applications, and as data processing and computer and mobile technologies have developed rapidly, users request for efficient sharing between each GIS's own data and various different GIS's. However, since many GIS applications maintain their own data formats, they are incapable of processing data formats different with each other, and do not have a filtering function for mobile GIS. This paper designs an integrated preprocessor, SMP to accept features of various current formats of geographic information such as DXF(Drawing eXchange Format), DWG(DraWinG), SHP(SHaPefile), etc., and to extract core information for describing maps. The geographic information extracted by SMP(Synthetic Map Preprocessor) shows consistency in various formats by visualizing through the integrated view. By generating the extracted core data in GML, it supports rapid access to mobile devices and extensibility of file formats overcoming heterogeneity.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.253-258
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• 2014

Recently, the development of cloud computing technology is developed as soon as smartphones is increases, and increased that users want to receive big data service. Hadoop framework of the big data service is provided to hadoop file system and hadoop mapreduce supported by data-intensive distributed applications. But, smpartphone service using hadoop system is a very vulnerable state to data authentication. In this paper, we propose a initial authentication protocol of hadoop system assisted by smartphone service. Proposed protocol is combine symmetric key cryptography techniques with ECC algorithm in order to support the secure multiple data processing systems. In particular, the proposed protocol to access the system by the user Hadoop when processing data, the initial authentication key and the symmetric key instead of the elliptic curve by using the public key-based security is improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.93-97
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• 2005

Sea operation monitoring system is a system for the automatic ship operation that is used on the variety sea operations such as laying optical cables on the sea between the countries, laying cables on the seabed for a remote island, laying pipelines for the natural gas, and so forth. This system processes data which optained through setting up environment and input from several sensors, and display GPS information with ENC data. And this system processes not only data of root file about sea operation, but also realtime information from PDA of client wirelessly connected with AP on wireless LAN, In addition, this system can improve efficiency of the operation as a result of enabling free movement within valid range. This paper design and Implementation Monitoring system from above appropriate to the embedded system, and improve competitive power of ship through prevention of a ship accident, to keep minimizing operation loads and support both the automatic ship operation and the safety voyage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.38-46
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• 2017

In this study, a query language was developed to supplement the information retrieval and model regeneration in the case of Industry Foundation Classes (IFC)-based civil infrastructure information models. First, the IFC objects to represent the structural components, entities to manage the related properties, and relationships to connect with the mentioned elements were analyzed in a point of information flow. The results confirmed that the end-users could have problems with access and comprehend the properties and its relationships in the IFC file. Second, the IfcPropertySet-focused query method and applicable stand-alone module were proposed referring to the previous Building Information Model Query Language (BimQL). The availabilities of the proposed method were examined using the rail and sleeper information models through information retrieval and model regeneration. The most important advantage of the proposed approach is the IFC-based information retrievals that can guarantee the interoperability between software packages.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.593-600
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• 2018

Owing to the advancement of Internet and smart devices, access to various media such as social media became easy; thus, a large amount of big data is being produced. Particularly, the companies that provide various Internet services are analyzing the big data by using the MapReduce-based big data analysis techniques to investigate the customer preferences and patterns and strengthen the security. However, with MapReduce, when the big data is analyzed by defining the number of reducer objects generated in the reduce stage as one, the processing rate of big data analysis decreases. Therefore, in this paper, a MapReduce-based split big data analysis method is proposed to improve the log analysis processing rate. The proposed method separates the reducer partitioning stage and the analysis result combining stage and improves the big data processing rate by decreasing the bottleneck phenomenon by generating the number of reducer objects dynamically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.371-378
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• 2014

As people are taking part in more versatile social activities, it becomes more frequent and more important for people to share personal information each other in appropriate level. Unfortunately, although the rapid spread of smart devices and advance of network technologies have brought many applications for information sharing into our hands, they do not provide effective mechanism for sharing personal information on collocated people. In this paper, we introduce an android application named WhoAmI which provides the functionality of sharing personal information on nearby users over Wi-Fi Direct as well as Wi-Fi network environment. According to the predefined access level such as business, community or friend, WhoAmI naturally provides profile information to accessible users. In addition, the information such as music, photo, movie can be effectively shared through the application.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.397-406
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• 2003

As the information technology grows interests in the intrusion detection system (IDS), which detects unauthorized usage, misuse by a local user and modification of important data, has been raised. In the field of anomaly-based IDS several artificial intelligence techniques such as hidden Markov model (HMM), artificial neural network, statistical techniques and expert systems are used to model network rackets, system call audit data, etc. However, there are undetectable intrusion types for each measure and modeling method because each intrusion type makes anomalies at individual measure. To overcome this drawback of single-measure anomaly detector, this paper proposes a multiple-measure intrusion detection method. We measure normal behavior by systems calls, resource usage and file access events and build up profiles for normal behavior with hidden Markov model, statistical method and rule-base method, which are integrated with a rule-based approach. Experimental results with real data clearly demonstrate the effectiveness of the proposed method that has significantly low false-positive error rate against various types of intrusion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6282-6289
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• 2015

Today, there is an increasing number of cases in which certificate information is leak, and accordingly, electronic finance frauds are prevailing. As certificate and private key a file-based medium, are easily accessible and duplicated, they are vulnerable to information leaking crimes by cyber-attack using malignant codes such as pharming, phishing and smishing. Therefore, the use of security token and storage toke' has been encouraged as they are much safer medium, but the actual users are only minimal due to the reasons such as the risk of loss, high costs and so on. This thesis, in an effort to solve above-mentioned problems and to complement the shortcomings, proposes a system in which digital signature for Internet banking can be made with a simply bio-authentication process. In conclusion, it was found that the newly proposed system showed a better capability in handling financial transitions in terms of safety and convenience.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.3
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• pp.115-138
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• 2017

Electronic record types are becoming diverse, and "composite electronic records," which are made up of various types of electronic records associated with functionality or user interaction that does not exist in current electronic document formats, are increasing. To ensure a continuous access to composite electronic records, metadata construction is a prerequisite for electronic records archiving. In this paper, we propose a metadata that can support archiving of composite electronic records associated with interactive functionality. The common elements were derived from an analysis of both domestic and international file format registry projects, and metadata elements related to functional requirements were identified from the analysis of the records on nursing education e-learning contents. We proposed the metadata elements for archiving composite electronic records, which consist of 25 high-level elements and 138 subelements.