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

• The KIPS Transactions:PartC
• /
• v.14C no.5
• /
• pp.439-452
• /
• 2007

We study on the privacy preserving data mining, PPDM for short, by using randomization. The theoretical PPDM based on the secure multi-party computation techniques is not practical for its computational inefficiency. So we concentrate on a practical PPDM, especially randomization technique. We survey various privacy measures and study on the privacy preserving mining of association rules by using randomization. We propose a new randomization operator, binomial selector, for privacy preserving technique of association rule mining. A binomial selector is a special case of a select-a-size operator by Evfimievski et al.[3]. Moreover we present some simulation results of detecting an appropriate parameter for a binomial selector. The randomization by a so-called cut-and-paste method in [3] is not efficient and has high variances on recovered support values for large item-sets. Our randomization by a binomial selector make up for this defects of cut-and-paste method.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.16 no.4
• /
• pp.13-26
• /
• 2006

RFID technology is evaluated as one of core technologies for ubiquitous environment, because of its various characteristics which barcode systems don't have. However, RFID systems have consumer's privacy infringement problems, such like information leakage and location tracing. We need RFID privacy protection protocols, that satisfy three essential security requirements; confidentiality, indistinguishability and forward security, in order to protect consumer's privacy perfectly. The most secure protocol, that satisfies all of the three essential security requirements, among existing protocols, is the hash-chain based protocol that Ohkubo proposed. Unfortunately this protocol has a big disadvantage that it takes very long time to identify a tag in the back-end server. In this paper, we propose a scheme to keep security just as it is and to reduce computation time for identifying a tag in back-end server. The proposed scheme shows the results that the identification time in back-end server is reduced considerably compared to the original scheme of Ohkubo protocol.

• Knowledge Management Research
• /
• v.25 no.2
• /
• pp.49-68
• /
• 2024

Increasing concerns regarding personal data privacy have complicated the acquisition of customer data through online marketing. This study investigates factors influencing customers' willingness to disclose information via a generative AI-based chatbot. Drawing on privacy calculus theory and regulatory focus theory, we explore how customer regulatory focus and familiarity with the generative AI-based chatbot shape disclosure intentions. Our study, involving 473 participants, reveals that low familiarity with the chatbot leads individuals with a prevention focus to perceive higher privacy risks and lower perceived usefulness compared to those with a promotion focus. However, with high familiarity, these differences diminish. Moreover, individuals with a promotion focus show a greater inclination to disclose information when familiarity with the generative AI-based chatbot is low, whereas this regulatory focus does not significantly impact disclosure intentions when familiarity is high. Perceived privacy risks mediate these relationships, underscoring the importance of understanding familiarity with the generative AI-based chatbot in facilitating personal information disclosure.

• The Journal of Society for e-Business Studies
• /
• v.22 no.1
• /
• pp.89-106
• /
• 2017

In advanced mobile devices environment, the market share of mobile application has been increased. Among various mobile services, Location-based Service (LBS) is an important feature to increase user motivation related to purchase intention on mobile. However, individual privacy has also increased as an important problem for invasion of privacy and information leakage while too many LBS based applications (App) rapidly launched in the App market. In this study, we focused on perceived values of LBS App users who use Apps related to recommending best restaurants in China and South Korea. The purpose of this study is to identify important factors for perceived value when users provide personal information for LBS service provider. The result of this study is follows: perceived value can increase while LBS customers can more control self-information and information useability. Also information ability of users affected perceived values for LBS Apps. Also users' app user ability and perceived value were effects on privacy revenue. In addtion, perceived weakness of users and perceived value increased privacy threat.

• Information Systems Review
• /
• v.15 no.1
• /
• pp.105-122
• /
• 2013

Given the proliferation of social network services, it has become important to understand its user's continued use behavior. As users' privacy concerns in SNS have been identified as a critical barrier against forming this continued intention, many studies have focused on inducing continued intention by mitigating privacy concerns. However, this paper suggests to approach users' continued intention not only from the perspective of mitigating privacy concerns but also from the perspective of increasing potential benefits. Under the theoretical framework of privacy calculus model, we conducted cross sectional survey on 150 Facebook and 150 KakaoTalk users. The result suggests that trust mediates the relationships between privacy concerns and continued intention and between network externality and continued intention, and the influence of support for network formation on continued intention. The effect of network externality on continued intention, however, is not significant among Facebook users while it is significant among KakaoTalk users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.245-248
• /
• 2008

최근 RFID 시스템의 채택이 다양한 분야에서 빠르게 진행되고 있다. 그러나 RFID 시스템의 대중화를 위해서는 RFID 태그의 정보를 무단으로 획득함으로써 발생할 수 있는 프라이버시 침해 문제를 해결해야 한다. 이 문제를 해결하기 위해서 기존 연구들 중에서 가장 안전한 M. Ohkubo 등의 Hash-Chain 기법이 있다. 그러나 이 기법은 태그를 판별할 때 엄청난 태그 수의 증가로 인해 막대한 계산 능력을 요구하는 문제점이 있다. 따라서 본 논문에서는 프라이버시 보호를 유지하면서 태그판별시간 절감을 위해서 그리드 환경으로의 이식과 노드별로 m/k개의 SP를 분할하는 균등분할 알고리즘을 적용한 태그 판별 처리 모델을 제안한다. 제안 모델을 그리드 환경에서 동시에 수행할 수 있다면 이상적인 경우 태그를 판별하는 시간은 1/k로 감소한다.

• Convergence Security Journal
• /
• v.6 no.1
• /
• pp.83-90
• /
• 2006

Recently, the security for RFID/USN environment is divided into network security and RFID security. The authentication protocol design for RFID security is studied to protect user privacy in RFID system. However, the study of efficient authentication protocol for RFID system is not satisfy a security for low-cost RFID tag and user privacy. Therefore, this paper proposes a secure matrix-based RFID authentication protocol that decrease communication overhead and computation. In result, the Matrix-based RFID authentication protocol is an effective authentication protocol compare with HB and $HB^+$ in traffic analysis attack and trace location attack.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.06c
• /
• pp.319-321
• /
• 2006

최근 유비쿼터스 환경의 실현을 위한 핵심기술로서 RFID 시스템에 대한 연구가 활발히 진행되고 있다. 그러나 RFID 시스템이 가지고 있는 특성으로 인하여 사용자 프라이버시 침해 문제가 대두되고 있으며 이를 해결하기 위한 방법들이 개발되고 있다. 기존의 해시 체인 기법은 프라이버시를 침해하는 공격들에 대해서 가장 안전한 기법이다. 그러나 태그를 식별하기 위해서 백엔드 시스템에서의 계산량이 많다는 문제점이 있다. 따라서 본 논문에서는 이러한 확장성 문제를 해결하기 위해 해시 체인 기법 기반으로 Heilman's method를 적용하여 병행 가능한 부분을 추출한 후 각 노드별로 분할하여 적용함으로써 노드별로 수행하는 방법을 설계한다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.5 no.5
• /
• pp.547-554
• /
• 2010

RFID is core technology to lead ubiquitous computing, and attract the notice of the world. It also improves social transparency, creates employment, and invigorates the allied industries. However, The technical characteristic with RFID has some problems with security and privacy. The commercialization of RFID is delayed due to these problems. This paper introduces the technical method to find solutions about an invasion of privacy to be due to introduce RFID system. First, this method applies Hash-Chain proposed by M. Ohkubo and some other researchers. The more tags increase, the more it demands lots of computation time. We divide SPs equally to solve these problems. And then, We'll suggest solutions to shorten the identification time of tag by implementing SPs with multi nodes of Grid environment at the same time. This makes it possible to keep the privacy protection of RFID tag, and process RFID tag in real time at the same time.