• ETRI Journal
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• v.43 no.1
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

• Spatial Information Research
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• v.20 no.5
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• pp.57-66
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• 2012

Recent development in wireless communication technology like GPS as well as mobile equipments like PDA and cellular phone makes location-based services (LBSs) popular. However, because users request a query to LBS servers by using their exact locations while moving on the road network, users' privacy may not be protected in the LBSs. Therefore, a mechanism for users' privacy protection is required for the safe and comfortable use of LBSs by mobile users. For this, we, in this paper, propose a road network distance based cloaking scheme supporting user privacy protection in location-based services. The proposed scheme creates a cloaking area by considering road network distance, in order to support the efficient and safe LBSs on the road network. Finally, we show from our performance analysis that our cloaking scheme outperforms the existing cloaking scheme in terms of cloaking area and service time.

• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.18-27
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• 2010

In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.97-102
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• 2008

A wireless sensor network consists of many sensors that collect and transmit physical or environmental conditions at different locations to a server continuously. Many researches mainly focus on processing continuous queries on real-time data stream. However, they do not concern the problem of storing the historical data, which is mandatory to the historical queries. In this paper, we propose two time-based storage methods to store the sensor data stream and reduce the managed tuples without any loss of information, which lead to the improvement of the accuracy of query results.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.99-110
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• 2009

Currently, there are many applications being developed based on sensor network technology. A tracking method for moving objects in sensor network is one of the main issue of this field. There is a little research on this issue, but most of the existing work has two problems. The first problem is a communication overhead for visiting sensor nodes many times to track a moving object. The second problem is an disability for dealing with many moving objects at a time. To resolve the problems, we, in this paper, propose a signature-based tracking method using efficient data aggregation for moving objects, called SigMO-TRK. For this, we first design a local routing hierarchy tree to aggregate moving objects' trajectories efficiently by using a space filtering technique. Secondly, we do the tracking of all trajectories of moving objects by using signature in a efficient way, our approach generates signatures to method. In addition, by extending the SigMO-TRK, we can retrieve the similar trajectories of moving objects for given a query. Finally, by using the TOSSIM simulator, we show that our signature-based tracking method outperforms the existing tracking method in terms of energy efficiency.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.251-258
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• 1998

The purpose of this study is to develop the District-level Planning Support System (DPSS) by using GIS. The district-level planning which is related for district-level control of city, needs the various parcel-level information which is composing the urban physical environment. The information has to be stored and analyzed for recognizing the study area, then the district-level planning will be efficiently managed. The use of GIS in the process of district-level planning is restricted for the creation of thematic map. GIS is not used for the analysis of spatial patterns and planning process. This study evaluates the characteristics of current district-level planning and the basic components of urban physical environment. And the database model is built. The topology among components is defined by using the spatial relationship. Then the spatial query machine for district-level planing is developed by using ArcView 3.1, Avenue and Dialog Extension. This spatial query machine is applied for case study. This study shows 1) the possibility of the district-level planning support system for analyzing spatial relationship, 2) the needs of the up-to-date topographic map showing current building's footlines and the complete integration with cadastral maps, it will reduce the uncertainty in the spatial decision making process, 3) the methodology for the construction of spatial decision making rules, 4) the further study for the using of raster, network, image and three dimension data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.19-29
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• 2003

This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.56-61
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• 2006

최근 공간 네트워크 데이터베이스를 위한 질의처리 알고리즘에 관한 연구가 많이 진행되어 왔다. 그러나 현재 좌표-기반 질의에 대한 연구는 활발히 진행중인 반면, 경로-기반 질의에 대한 연구는 매우 미흡한 실정이다. 공간 네트워크 데이터베이스에서는 이동객체가 공간 네트워크상에서만 이동하기 때문에 경로-기반 질의의 유용성이 매우 증대되므로, 경로-기반 질의에 대한 효율적인 질의처리 알고리즘 연구가 필수적이다. 따라서 본 논문에서는 경로-기반 질의의 대표적인 방법인 In-Route Nearest Neighbor 질의처리 알고리즘을 분석하여 기존 연구에서 고려하지 않은 시간 및 공간제약을 고려한 경로-기반 질의처리 알고리즘을 설계한다.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.55-62
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• 2009

In u-GIS environment, we collect spatial data needed through sensor network and provide them with information real-time processed or stored. When information through Internet is requested on Web based applications, it is transmitted in XML. Especially, when requested information includes spatial data, GML, S-XML, and other document that can process spatial data are used. In this processing, real-time stream data processed in DSMS is transformed to S-XML document type and spatial information service based on web receive S-XML document through Internet. Because most of spatial application service use existing spatial DBMS as a storage system, The data used in S-XML and SDBMS needs transformation between themselves. In this paper, we propose S-XML a transformation method using caching of spatial data. The proposed method caches the spatial data part of S-XML to transform S-XML and relational spatial database for providing spatial data efficiently and it transforms cached data without additional transformation cost when a transformation between data in the same region is required. Through proposed method, we show that it reduced the cost of transformation between S-XML documents and spatial information services based on web to provide spatial information in u-GIS environment and increased the performance of query processing through performance evaluation.