• Journal of Communications and Networks
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• 제15권2호
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• pp.153-163
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• 2013

In recent years, more and more researches have been focusing on trust management of vehicle ad-hoc networks (VANETs) for improving the safety of vehicles. However, in these researches, little attention has been paid to the location privacy due to the natural conflict between trust and anonymity, which is the basic protection of privacy. Although traffic safety remains the most crucial issue in VANETs, location privacy can be just as important for drivers, and neither can be ignored. In this paper, we propose a beacon-based trust management system, called BTM, that aims to thwart internal attackers from sending false messages in privacy-enhanced VANETs. To evaluate the reliability and performance of the proposed system, we conducted a set of simulations under alteration attacks, bogus message attacks, and message suppression attacks. The simulation results show that the proposed system is highly resilient to adversarial attacks, whether it is under a fixed silent period or random silent period location privacy-enhancement scheme.

• 디지털융복합연구
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• 제15권12호
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• pp.265-272
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• 2017

스마트폰의 위치기반서비스가 활발히 사용됨에 따라 사용자들이 자신의 위치정보의 노출에 대한 염려가 커지고 있다. 본 연구는 프라이버시 계산 이론에 기반하여 스마트폰 사용자들이 자신의 위치정보의 제공을 어떻게 받아들이는지 확인하고자 연구모형을 개발하였다. 대학생을 대상으로 수집한 데이터를 SmartPLS를 이용하여 분석한 결과 프라이버시 계산 관점의 기존 연구와는 다른 결과를 얻었다. 프라이버시 계산이론은 인간은 합리적인 존재이며, 위험과 효과 측면을 고려하여 프라이버시 정보의 제공을 결정한다고 본다. 본 연구의 결과는 프라이버시 염려는 위험에 유의하게 영향을 미치나, 사용의도는 효과에 의해서 유의하게 영향을 미쳤다. 이러한 결과는 감정적 판단과 행동적 판단이 서로 상이한 요인에 의해서 영향을 받는다는 행동경제학적 관점과 일치한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3438-3457
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• 2022

As location-based services (LBS) are widely used in vehicular ad-hoc networks (VANETs), location privacy has become an utmost concern. Spatial cloaking is a popular location privacy protection approach, which uses a cloaking area containing k-1 collaborative vehicles (CVs) to replace the real location of the requested vehicle (RV). However, all CVs are assumed as honest in k-anonymity, and thus giving opportunities for dishonest CVs to submit false location information during the cloaking area construction. Attackers could exploit dishonest CVs' false location information to speculate the real location of RV. To suppress this threat, an edge-assisted Trusted Collaborative Anonymity construction scheme called TCA is proposed with trust mechanism. From the design idea of trusted observations within variable radius r, the trust value is not only utilized to select honest CVs to construct a cloaking area by restricting r's search range but also used to verify false location information from dishonest CVs. In order to obtain the variable radius r of searching CVs, a multiple linear regression model is established based on the privacy level and service quality of RV. By using the above approaches, the trust relationship among vehicles can be predicted, and the most suitable CVs can be selected according to RV's preference, so as to construct the trusted cloaking area. Moreover, to deal with the massive trust value calculation brought by large quantities of LBS requests, edge computing is employed during the trust evaluation. The performance analysis indicates that the malicious response of TCA is only 22% of the collaborative anonymity construction scheme without trust mechanism, and the location privacy leakage is about 32% of the traditional Enhanced Location Privacy Preserving (ELPP) scheme.

• Spatial Information Research
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• 제11권2호
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• pp.131-142
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• 2003

GIS와 정보통신기술과 연계된 위치기반서비스는 개인의 위치정보를 측정하고 이용한다. 위치정보는 특정된 개인의 현재 위치와 그 위치를 통한 개인의 행동 등을 추정할 수 있는 정보로서 프라이버시 침해 가능성이 매우 높은 정보이므로 강력한 보호 제도가 필요하다. 이러한 배경에서 정보통신부가 추진하고 있는 위치정보보호법안은 개인정보 보호와 위치기반서비스 사업 활성화라는 상충되는 두 가지 목적에 대한 합의점을 제대로 찾지 못하고 있어 실질적인 개인정보 보호 대책으로 부족하며 지속적 보완이 필요하다. 본 연구는 효과적인 지리정보의 유통과 활용의 관점에서 개인의 위치정보 보호 문제를 고찰하고 합리적인 대안을 모색하였다.

• 한국컴퓨터정보학회논문지
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• 제26권12호
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• pp.19-27
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• 2021

본 논문에서는 지역 차분 프라이버시(Local Differential Privacy, LDP) 기법을 이용하여 프라이버시를 보호하면서 수집한 차량 위치 데이터와 딥러닝 기법을 이용하여 교통량을 예측하기 위한 기법을 제시한다. 제시한 기법은 데이터를 수집하는 과정과 수집한 데이터를 이용하여 교통량을 예측하는 과정으로 구성된다. 첫 번째 단계에서는 데이터 수집 과정 중에 발생할 수 있는 프라이버시 침해 문제를 해결하기 위해 LDP 기법을 적용하여 차량의 위치 데이터를 수집한다. LDP 기법은 데이터 수집 시 원본 데이터에 노이즈를 추가해 사용자의 민감한 데이터가 외부에 노출되는 것을 방지한다. 이를 통해 운전자의 프라이버시를 보존하면서 차량의 위치 데이터를 수집할 수 있다. 두 번째 단계에서는 첫 번째 단계에서 수집한 데이터에 딥러닝 기법을 적용하여, 교통량을 예측한다. 또한, 본 논문에서 제안한 기법의 우수성을 입증하기 위해, 실데이터를 이용한 성능 평가를 진행한다. 성능 평가 결과는 본 논문에서 제안한 기법이 사용자의 프라이버시를 보호하면서 수집된 데이터를 이용하여 효과적으로 교통량을 예측할 수 있음을 입증한다.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.399-408
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• 2021

Information security reports four types of basic attacks on information. One of the attacks is named as fabrication. Even though mobile devices and applications are showing its maturity in terms of performance, security and ubiquity, location-based applications still faces challenges of quality of service, privacy, integrity, authentication among mobile devices and hence mobile users associated with the devices. There is always a continued fear as how location information of users or IoT appliances is used by third party LB Service providers. Even adversary or malicious attackers get hold of location information in transit or fraudulently hold this information. In this paper, location information fabrication scenarios are presented after knowing basic model of information attacks. Peer-to-Peer broadcast model of location privacy is proposed. This document contains introduction to fabrication, solutions to such threats, management of fabrication mitigation in collaborative or peer to peer location privacy and its cost analysis. There are various infrastructure components in Location Based Services such as Governance Server, Point of interest POI repository, POI service, End users, Intruders etc. Various algorithms are presented and analyzed for fabrication management, integrity, and authentication. Moreover, anti-fabrication mechanism is devised in the presence of trust. Over cost analysis is done for anti-fabrication management due to nature of various cryptographic combinations.

• International Journal of Contents
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• 제13권1호
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• pp.22-30
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• 2017

The diffusion of advanced mobile technology has introduced new types of personal information or 'location data'. These new data mean new opportunities for businesses, such as location-based services (LBS), but have resulted in new consumer anxieties regarding disclosure of personal information. This study examines the effects of the consumers' perceived control over "time-andplace" information in location-aware services on their perceived privacy risk. A total of 270 respondents participated in this study. Conditions of perceived privacy control were operationalized over time-and-place information, in a $2{\times}2$ factorial design. Results indicate that the perceived control over time-and-place personal information is a significant predictor of perceived risk, and control assurances over time-and-place information enhances the perception of control, thus alleviating the perceived risk. In addition, the effect is much more significant when time and place were combined.

• 한국정보시스템학회지:정보시스템연구
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• 제21권4호
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• pp.55-79
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• 2012

LBS(Location-Based Service) is one of the smartphone application services which has been receiving great attention recently. Various applications of smartphone use LBS to provide innovative services. However, use of LBS raises privacy concerns because the location information of users is constantly exposed. Privacy calculus perspective attempts to understand the characteristics of the user's privacy. It is based on the risk-benefit analysis in the economics' perspective. That is, when the benefit expected through personal information disclosure is higher than risk, we are willing to provide personal information. This research suggested a research model based on the privacy calculus perspective to clarify the effect of information disclosure intention of smartphone LBS application users. Based on the main factors of privacy calculus, perception of privacy risk and privacy benefit, the relationship of the perceived value and the information disclosure intention was empirically analyzed by utilizing structural equation modeling(SEM) methodology. According to the results of the empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between privacy concern and information disclosure intention. This study showed a strong evidence of antecedent factors based on privacy calculus of personal information disclosure in smartphone LBS applications.

• 한국컴퓨터정보학회논문지
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• 제18권3호
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• pp.47-57
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• 2013

최근 스마트폰의 발전에 따라서 많은 위치 기반 서비스가 활용되고 있으며, 위치 정보 노출로 인한 문제점이 사회적 이슈로 대두되고 있다. 기존의 잘 알려진 위치 정보 보호를 위한 공간 클로킹 기법은 사용자가 요청한 지역에서 위치 정보를 흐릿하게 처리하였다. 하지만 계속적으로 움직이는 이동 객체의 모든 지역을 클로킹하기에는 범위공간이 무수히 넓어지는 문제를 가진다. 따라서, 본 논문에서는 이동 객체 정보 보호를 위한 그리드 기반 시멘틱 클로킹 기법을 제안한다. 제안 기법은 시멘틱 클로킹을 위하여 EMD 갱신 스키마를 확장하고 이동 객체를 위한 대표 보호지역의 클로킹을 정의하였다. 성능 평가에서는 제안 기법이 기존 기법에 비해 처리 시간과 공간 범위에서 안전성과 효율성을 높였다. 이를 통해, 성공적으로 다양한 적으로부터 지속적으로 움직이는 객체의 위치 개인 정보를 보호하여 기존의 방법을 능가하는 성능을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권5호
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• pp.1717-1732
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• 2015

The widespread use of location-based services (LBSs), which allows untrusted service provider to collect large number of user request records, leads to serious privacy concerns. In response to these issues, a number of LBS privacy protection mechanisms (LPPMs) have been recently proposed. However, the evaluation of these LPPMs usually disregards the background knowledge that the adversary may possess about users' contextual information, which runs the risk of wrongly evaluating users' query privacy. In this paper, we address these issues by proposing a generic formal quantification framework,which comprehensively contemplate the various elements that influence the query privacy of users and explicitly states the knowledge that an adversary might have in the context of query privacy. Moreover, a way to model the adversary's attack on query privacy is proposed, which allows us to show the insufficiency of the existing query privacy metrics, e.g., k-anonymity. Thus we propose two new metrics: entropy anonymity and mutual information anonymity. Lastly, we run a set of experiments on datasets generated by network based generator of moving objects proposed by Thomas Brinkhoff. The results show the effectiveness and efficient of our framework to measure the LPPM.