• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.101-108
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• 2015

Location-sharing based service (LSBS) refers to a service that users share their location information with other users with whom friendship. At this time, the location information is shared through service provider, and then their position information is exposed to the service provider. The exposure of this personal position information to the service provider has raised a privacy problem, and thus privacy preserving mechanisms have been proposed to protect them. In this paper, we examine the types and features of the proposed location-sharing based services so far, and survey the research trend of privacy preserving mechanisms for them. Through the analysis on existing privacy preserving mechanisms, we present design factors for a privacy preserving mechanism for the current LSBS services, and suggest future work.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.141-156
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• 2020

Differential privacy, which used to collect and analysis data and preserve data privacy, has been applied widely in data privacy preserving data application. Local differential privacy algorithm which is the local model of differential privacy is used to user who add noise to his data himself with randomized response by self and release his own data. So, user can be preserved his data privacy and data analyst can make a statistical useful data by collected many data. Local differential privacy method has been used by global companies which are Google, Apple and Microsoft to collect and analyze data from users. In this paper, we compare and analyze the local differential privacy methods which used in practically. And then, we study applicability that applying the local differential privacy method in survey or opinion poll scenario in practically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.24-45
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• 2012

In this paper, we present a survey of security and privacy preserving issues in M2M communications in Cyber-Physical Systems. First, we discuss the security challenges in M2M communications in wireless networks of Cyber-Physical Systems and outline the constraints, attack issues, and a set of challenges that need to be addressed for building secure Cyber-Physical Systems. Then, a secure architecture suitable for Cyber-Physical Systems is proposed to cope with these security issues. Eventually, the corresponding countermeasures to the security issues are discussed from four aspects: access control, intrusion detection, authentication and privacy preserving, respectively. Along the way we highlight the advantages and disadvantages of various existing security schemes and further compare and evaluate these schemes from each of these four aspects. We also point out the open research issues in each subarea and conclude with possible future research directions on security in Cyber-Physical Systems. It is believed that once these challenges are surmounted, applications with intrinsic security considerations will become immediately realizable.

• Journal of KIISE
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• v.44 no.2
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• pp.195-207
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• 2017

In recent years, data are actively exploited in various fields. Hence, there is a strong demand for sharing and publishing data. However, sensitive information regarding people can breach the privacy of an individual. To publish data while protecting an individual's privacy with minimal information distortion, the privacy- preserving data publishing(PPDP) has been explored. PPDP assumes various attacker models and has been developed according to privacy models which are principles to protect against privacy breaching attacks. In this paper, we first present the concept of privacy breaching attacks. Subsequently, we classify the privacy models according to the privacy breaching attacks. We further clarify the differences and requirements of each privacy model.

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

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.105-110
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• 2021

Contact between Vehicle-to-vehicle and vehicle-to-infrastructural is becoming increasingly popular in recent years due to their crucial role in the field of intelligent transportation. Vehicular Ad-hoc networks (VANETs) security and privacy are of the highest value since a transparent wireless communication tool allows an intruder to intercept, tamper, reply and erase messages in plain text. The security of a VANET based intelligent transport system may therefore be compromised. There is a strong likelihood. Securing and maintaining message exchange in VANETs is currently the focal point of several security testing teams, as it is reflected in the number of authentication schemes. However, these systems have not fulfilled all aspects of security and privacy criteria. This study is an attempt to provide a detailed history of VANETs and their components; different kinds of attacks and all protection and privacy criteria for VANETs. This paper contributed to the existing literature by systematically analyzes and compares existing authentication and confidentiality systems based on all security needs, the cost of information and communication as well as the level of resistance to different types of attacks. This paper may be used as a guide and reference for any new VANET protection and privacy technologies in the design and development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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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.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1149-1155
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• 2017

In these days, cloud environments such as cloud platforms, cloud services like Amazon AWS, IBM Bluemix are used in the Internet of Things for providing efficient services. These cloud platform environments have various security threats according to increasing of use, so the recent research results on cloud security and privacy protection technologies and related regimes and legislations are written in this paper and we suggest prospect of research on cloud platform environment security and privacy preserving.

• Journal of Research and Publication Ethics
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• v.4 no.1
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• pp.1-7
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• 2023

Purpose: Poor anonymity and confidential strategies by a researcher not only develop unprecedented and precedented harm to participants but also impacts the overall critical appraisal of the research outcomes. Therefore, understanding and applying anonymity and confidentiality in research is key for credible research. As such, this research expansively presents the importance of anonymity and confidentiality for research surveys through critical literature reviews of past works. Research design, data and methodology: This research has selected the literature content approach to obtain proper literature dataset which was proven by high degree of validity and reliability using only books and peer-reviewed research articles. The current authors have conducted screening procedure thoroughly to collect better fitted resources. Results: Research findings consistently mentioned the confidentiality and anonymity principles are preserved and implemented as a means of protecting the privacy of all individuals, establishing trust and rapport between researchers and study participants, as a way of critically upholding research ethical standards, and preserving the integrity of research processes. Conclusions: Confidentiality and anonymity are research ethical principles that help in providing informed consent to participants assuring subjects of the privacy of their personal data. As provided by research bodies and organizations, every research process has to incorporate the principles to meet credibility.