• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2193-2201
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• 2006

In related to mobile communication environment. Kesdogan and Pfitzmann[1,2,3] proposed solutions using temporary pseudonym identification, called TP(Temporary Pseudonym) to solve the problems concerning current locations of mobile users and exposure of their movements in the privacy aspect. After that, we proposed more improved method protecting mobile users from active attacks of network providers in [4]. But it is the case that mobile users are located in only home domain. As a more extended method. we propose new mobile terminated protocol protecting user privacy in case of moving from the home domain to the remote domain and analyze its security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5244-5259
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• 2019

With the continuous development of LBS (Location Based Service) applications, privacy protection has become an urgent problem to be solved. Differential privacy technology is based on strict mathematical theory that provides strong privacy guarantees where it supposes that the attacker has the worst-case background knowledge and that knowledge has been applied to different research directions such as data query, release, and mining. The difficulty of this research is how to ensure data availability while protecting privacy. Spatial multidimensional data are usually released by partitioning the domain into disjointed subsets, then generating a hierarchical index. The traditional data-dependent partition methods need to allocate a part of the privacy budgets for the partitioning process and split the budget among all the steps, which is inefficient. To address such issues, a novel two-step partition algorithm is proposed. First, we partition the original dataset into fixed grids, inject noise and synthesize a dataset according to the noisy count. Second, we perform IH-Tree (Improved H-Tree) partition on the synthetic dataset and use the resulting partition keys to split the original dataset. The algorithm can save the privacy budget allocated to the partitioning process and obtain a more accurate release. The algorithm has been tested on three real-world datasets and compares the accuracy with the state-of-the-art algorithms. The experimental results show that the relative errors of the range query are considerably reduced, especially on the large scale dataset.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1036-1054
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• 2019

Recently, concomitant with a surge in numbers of Internet of Things (IoT) devices with various sensors, mobile crowdsensing (MCS) has provided a new business model for IoT. For example, a person can share road traffic pictures taken with their smartphone via a cloud computing system and the MCS data can provide benefits to other consumers. In this service model, to encourage people to actively engage in sensing activities and to voluntarily share their sensing data, providing appropriate incentives is very important. However, the sensing data from personal devices can be sensitive to privacy, and thus the privacy issue can suppress data sharing. Therefore, the development of an appropriate privacy protection system is essential for successful MCS. In this study, we address this problem due to the conflicting objectives of privacy preservation and incentive payment. We propose a privacy-preserving mechanism that protects identity and location privacy of sensing users through an on-demand incentive payment and group signatures methods. Subsequently, we apply the proposed mechanism to one example of MCS-an intelligent parking system-and demonstrate the feasibility and efficiency of our mechanism through emulation.

• Spatial Information Research
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• v.18 no.3
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• pp.53-62
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• 2010

Recent development in wireless communication technology, like GPS, and mobile equipments, like PDA and cellular phone, make location-based services (LBSs) popular. However, because, users continuously request a query to a server in the LBSs by using their exact locations, privacy information could be in danger. 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 grid-based cloaking area creation scheme supporting continuous LBSs in peer-to-peer environment. The proposed scheme creates a cloaking area by using Chord protocol, so as to support the continuous LBSs in peer-to-peer environment. Finally, we show from a performance analysis that our cloaking scheme outperforms the existing cloaking schemes, in terms of service time.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.153-161
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• 2015

We propose a privacy-preserving location-based service (LBS) which supports top-k search service. The previous schemes hurt the privacy of either the user and the location of the objects because they are sent to the LBS server in a plaintext form. In the proposed method, by encrypting them with the fully-homomorphic encryption, we achieved the top-k search is possible while the information on them is not given to the LBS server. We performed a simulation on the proposed scheme with 16 locations where k is 3. The required time is 270 hours in a conventional desktop machine, which seems infeasible to be used in practice. However, as the progress of the hardware, the performance will be improved.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.758-760
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• 2013

위치기반 서비스에 관련된 기술 연구가 활발히 진행됨에 따라 다수의 사용자가 위치기반 앱 서비스를 이용하고 있다. 그러나 위치기반 앱 서비스를 이용하는 사용자가 점차 증가함에 따라 사용자의 위치정보가 노출될 확률이 높아지고 있다. 우리는 개인의 위치 정보를 보호하면서도 서버의 작업 부하를 줄일 수 있는 self-Privacy Protection Range (self-PR)을 제안한다. Self-PR은 클라이언트의 조건(ex. 배터리 상태, 모바일 기기의 성능 등)에 따라 보호 영역을 설정할 수 있기 때문에 이상적인 질의처리가 가능하다. 반면에 서버는 클라이언트의 self-PR이 증가할수록 서버는 데이터 탐색 경로가 짧아지기 때문에 작업부하를 줄일 수 있다. 그리고 서버는 클라이언트의 self-PR 확인하고 질의 결과를 전송하기 때문에 정확한 질의 결과를 전송할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9B
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• pp.848-856
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• 2006

Location Based Service (LBS) is a service provided to the subscribers based on their (or others') geographical location. Interest in LBS has increased not only in the aspect of promoting utilization, including the public usage such as emergency rescue, but also in the aspect of protecting the personal location information of the subscribers. This study aims to suggest and classify the business models for LBS services, focusing on the flow of the personal location information. Each business model is reviewed from the perspective of protecting the location privacy of the subscribers.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.217-236
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• 2015

The purpose of this study is to propose the effective location-based IoT service acceptance model by integrating ELM (Elaboration Likelihood Model) with UTAUT (Unified Theory of Acceptance and Use of Technology). The Partial Least Squares was used to analyze the causal relationships with respect to the effects of central route and peripheral route on acceptance intention. The results shows that central route has more significant impacts on perceived usefulness than peripheral route and CFIP (Concern for Information Privacy) weaken the relationship of acceptance intention and perceived usefulness. Our findings indicate some meaningful implications in the acceptance research of IOT services. First, we noted that the easy of use significantly affects the adoption of location-based IoT service. Furthermore, it is important to build the secured mechanism of privacy protection to adopt of location-based IoT service. Second, we tried to attempt the newly integrated approach to technical acceptance using UTAUT's variables and ELM by Petty and Cacioppo (1986). Finally this research empirically analyzed the adoption case of location-based IoT service which is not well-known yet within our country.

• The Journal of Society for e-Business Studies
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• v.17 no.3
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• pp.129-147
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• 2012

In this paper, we research on the personal information protection system in smart-phone based on mobile environment. This paper proposes the enhanced personal location privacy mechanism in location-based service environment of a smart phone operating system(iOS, Android) for the relevant regulations on location-based protection and utilization. Also, the result verified that possibility on a self-control mechanism of the personal information protection system's subject in the window platform throughout the experiment. Therefore, this study have drew a method that user positively can cope with a protection of personal location information by having a user's self-control method in the system under development or done by illegal location-based service providers and illegal application developer.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.31-38
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• 2017

Recently with the rapid development of LBS (Location-based Services) technology, approaches of protecting user's location have gained tremendous attentions. For using LBS, users need to forward their real locations to LBS server. However, if the user sends his/her real location to LBS server, the server will have the all the information about user in LBS. Moreover, if the user opens it to LBS server for a long time, the trajectory of user may be released. In this paper, we propose GTC (Grid-based Trajectory Cloaking) method to address the privacy issue. Different from existing approaches, firstly the GTC method sets the predicting trajectory and divides the map into $2^n*2^n$ grid. After that we will generate cloaking regions according to user's desired privacy level. Finally the user sends them to LBS server randomly. The GTC method can make the cost of process less than sequential trajectory k-anonymity. Because of confusing the departure and destination, LBS server could not know the user's trajectory any more. Thus, we significantly improve the privacy level. evaluation results further verify the effectiveness and efficiency of our GTC method.