• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3199-3218
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• 2019

Location-based services (LBSs) have become popular in recent years due to the ever-increasing usage of smart mobile devices and mobile applications through networks. Although LBS application provides great benefits to mobile users, it also raises a sever privacy concern of users due to the untrusted service providers. In the lack of privacy enhancing mechanisms, most applications of the LBS may discourage the user's acceptance of location services in general, and endanger the user's privacy in particular. Therefore, it is a great interest to discuss on the recent privacy-preserving mechanisms in LBSs. Many existing location-privacy protection-mechanisms (LPPMs) make great efforts to increase the attacker's uncertainty on the user's actual whereabouts by generating a multiple of fake-locations together with user's actual positions. In this survey, we present a study and analysis of existing LPPMs and the state-of-art privacy measures in service quality aware LBS applications. We first study the general architecture of privacy qualification system for LBSs by surveying the existing framework and outlining its main feature components. We then give an overview of the basic privacy requirements to be considered in the design and evaluation of LPPMs. Furthermore, we discuss the classification and countermeasure solutions of existing LPPMs for mitigating the current LBS privacy protection challenges. These classifications include anonymization, obfuscation, and an encryption-based technique, as well as the combination of them is called a hybrid mechanism. Finally, we discuss several open issues and research challenges based on the latest progresses for on-going LBS and location privacy research.

• 한국멀티미디어학회논문지
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• 제17권8호
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• pp.946-952
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• 2014

Mobility prediction is one of hot topics using location history information. It is useful for not only user-level applications such as people finder and recommendation sharing service but also for system-level applications such as hand-off management, resource allocation, and quality of service of wireless services. Most of current prediction techniques often use a set of significant locations without taking into account possible location information changes for prediction. Markov-based, LZ-based and Prediction by Pattern Matching techniques consider interesting locations to enhance the prediction accuracy, but they do not consider interesting location changes. In our paper, we propose an algorithm which integrates the changing or emerging new location information. This approach is based on Active LeZi algorithm, but both of new location and all possible location contexts will be updated in the tree with the fixed depth. Furthermore, the tree will also be updated even when there is no new location detected but the expected route is changed. We find that our algorithm is adaptive to predict next location. We evaluate our proposed system on a part of Dartmouth dataset consisting of 1026 users. An accuracy rate of more than 84% is achieved.

• 한국산업정보학회논문지
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• 제16권5호
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• pp.45-54
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• 2011

현재 스마트 기기 용도의 다양한 시내버스관련 어플리케이션이 있으며, 시내버스의 도착시간, 노선정보 등의 정보를 제공하고 있다. 하지만, 사용자의 이동에 따른 다양한 방법을 제공하지 못 하고 있다. 이에 본 연구에서는 사용자의 6가지 패턴을 알고리즘으로 설계하고, 이를 이용하여 구현된 Server와 Android Application이 서로 교신하면서 사용자가 가고자하는 목적지로 이동하는 방법을 제공한다. 또 구글 맵과 위치기반정보를 통하여 탑승지와 환승지, 그리고 도착지를 지도상에 출력함과 동시에 사용자의 현재 위치도 함께 제공한다. 보다 실용적이고 효율적인 정보를 제공함으로써 사용자는 시내버스를 보다 쉽게 이용할 수 있다.

• 한국인터넷방송통신학회논문지
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• 제23권6호
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• pp.171-177
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• 2023

중앙 통제 서버 없이 앱만으로 MDM 서비스를 구성하는 경우, 보안 통제가 필요한 직장의 위치 정보를 MDM 앱에 내장하여 배포함으로써 직장의 보안 영역과 충분히 떨어진 지역에서는 GPS 신호를 기반으로 보안 통제를 해제할 수 있도록 하는 방식이 일반적으로 적용되고 있다. 본 연구에서는 직장 등 특정 구역의 위치 정보를 MDM 앱에 내장하여 배포하지 않고 배포된 앱에서 각 개인이 자신에게 필요한 보안 통제구역의 위치 정보를 직접 입력하여 설정 정보로써 유지하는 방식을 제안하였다. 본 연구에서 제안한 방법을 통해 MDM 서비스의 보편성과 호환성을 향상하여 구축 비용을 최소화할 수 있으며, 추가적인 기능 구현을 통해 보안 통제 수준 또한 향상할 수 있다.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2007년도 춘계학술대회
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• pp.47-54
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• 2007

In this study, we consider the movement-based registration (MBR), location-based registration (LBR) and distance-based registration (DBR) schemes. Analytical models based on a 2-dimensional random walk in a hexagonal cell configuration are considered to analyze and compare the performances of these three schemes. We focus on the derivation of the registration costs of LBR and DBR using an analytical method and then show that DBR always outperforms both MBR and LBR. Numerical results are provided to demonstrate the validity of our models under various circumstances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.71-76
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• 2006

With the rapid development of spatial infrastructure in US, Europe, Japan, China and India, there is no doubt that the next generation Global Navigation Satellite System (GNSS) will improve the integrity, accuracy, reliability and availability of the position solution. GNSS is becoming an essential element of personal, commercial and public infrastructure and consequently part of our daily lives. However, the applicability of GPS in supporting a range of location-sensitive applications such as location based services in an urban environment is severely curtailed by the interference of the 3D urban settings. To characterize and gain in-depth understanding of such interferences and to be able to provide location-based optimization alternatives, a high-fidelity 3D urban model of Melbourne CBD built with ArcGIS and large scale high-resolution spatial data sets is used in this study to support a comprehensive simulation of current and future GNSS signal performance, in terms of signal continuity, availability, strength, geometry, positioning accuracy and reliability based on a number of scenarios. The design, structure and major components of the simulator are outlined. Useful time-stamped spatial patterns of the signal performance over the experimental urban area have been revealed which are valuable for supporting location based services applications, such as emergency responses, the optimization of wireless communication infrastructures and vehicle navigation services.

• 한국공간정보시스템학회 논문지
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• 제10권4호
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• pp.1-10
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• 2008

최근 무선 인터넷에서 사용자의 위치정보가 다양한 애플리케이션의 정보 요소로 활용되기 시작하였다. 이러한 애플리케이션의 하나로 위치기반 서비스(Location-Based Service)가 주목을 받고 있다. 그러나 위치기반 서비스에서는 서비스를 요청하는 사용자가 자신의 정확한 위치 정보를 데이터베이스 서버로 보내기 때문에 사용자의 개인 정보가 노출될 수 있는 취약성을 지니고 있다. 이에 모바일 사용자가 안전하고 편리하게 위치기반 서비스를 사용하기 위한 개인 정보 보호 방법이 요구된다. 이를 위해 본 논문에서는 K-anonymity 및 L-diversity를 고려한 cloaking 기법을 제안한다. 이 기법은 먼저 사용자가 요구하는 L개의 건물을 탐색하는 L-diversity를 수행한 뒤, K명의 사용자를 탐색하는 K-anonymity를 수행하여 최소한의 넓이는 가지는 cloaking 영역을 생성한다. 이를 위해, R*-트리 기반의 색인 구조를 사용하며, 특히 효율적인 cloaking 영역 생성을 위해 필터링 방법을 사용한다. 마지막으로 성능평가를 통해 본 논문에서 제안한 cloaking 기법이 기존의 그리드 기법보다 우수함을 보인다.

• Journal of Communications and Networks
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• 제18권5호
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• pp.837-845
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• 2016

Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.

• 한국산업정보학회논문지
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• 제18권6호
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• pp.1-8
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• 2013

스마트폰의 사용이 일상화되면서, 그 휴대성에 의해서 소셜 네트워크 서비스(SNS, Social Network Service) 어플리케이션의 사용이 매우 활발하다. 또한 위치 이동에 따른 정보의 활용이 가능한 위치 기반 서비스(Location based Service)의 수요가 확대되면서 SNS와 결합된 형태의 서비스가 스마트폰의 사용성을 향상시키고 있다. 본 논문에서는 사용자의 위치를 실시간으로 추적하여 이동하는 위치에 따라 작성되어진 SNS를 위한 정보를 자동으로 알려주는 LBSNS(Location Based Social Networking Service)가 가능한 어플리케이션을 구현한다.