• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.139-149
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• 2008

The amount of personal information collected by organizations and government agencies is continuously increasing. When a data collector publishes personal information for research and other purposes, individuals' sensitive information should not be revealed. On the other hand, published data is also required to provide accurate statistical information for analysis. k-Anonymity and ${\iota}$-diversity models are popular approaches for privacy preserving data publication. However, they are limited to static data release. After a dataset is updated with insertions and deletions, a data collector cannot safely release up-to-date information. Recently, the m-invariance model has been proposed to support re-publication of dynamic datasets. However, the m-invariant generalization can cause high information loss. In addition, if the adversary already obtained sensitive values of some individuals before accessing released information, the m-invariance leads to severe privacy disclosure. In this paper, we propose a novel technique for safely releasing dynamic datasets. The proposed technique offers a simple and effective method for handling inserted and deleted records without generalization. It also gives equivalent degree of privacy preservation to the m-invariance model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2719-2735
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• 2015

In the cloud environment, users pay more attentions to their data security since all of them are stored in the cloud server. Researchers have proposed many mutual authentication schemes for the access control of the cloud server by using the smart card to protect the sensitive data. However, few of them can resist from the smart card lost problem and provide both of the forward security and the backward security. In this paper, we propose a novel authentication scheme for cloud computing which can address these problems and also provide the anonymity for the user. The trick we use is using the password, the smart card and the public key technique to protect the processes of the user's authentication and key exchange. Under the Elliptic Curve Diffie-Hellman (ECDH) assumption, it is provably secure in the random oracle model. Compared with the existing smart card based authentication schemes in the cloud computing, the proposed scheme can provide better security degree.

• KNOM Review
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• v.21 no.2
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• pp.18-25
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• 2018

Since the development of block-chain technology by Satoshi Nakamoto and Bitcoin pioneered a new cryptocurrency market, a number of scale of cryptocurrency have emerged. There are crimes taking place using the anonymity and vulnerabilities of block-chain technology, and many studies are underway to improve vulnerability and prevent crime. However, they are not enough to detect users who commit crimes. Therefore, it is very important to detect abnormal behavior such as money laundering and stealing cryptocurrency from the network. In this paper, the characteristics of the transactions and user graphs in the Bitcoin network are collected and statistical information is extracted from them and presented as plots on the log scale. Finally, we analyze visualized plots according to the Densification Power Law and Power Law Degree, as a result, present features appropriate for detection of anomalies involving abnormal transactions and abnormal users in the Bitcoin network.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.335-340
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• 2014

Crowd Sourcing-based Social App Manufacturing environment, a small app development project by a team of anonymous virtual performed without the constraints of time and space, and manage it for the app development process need to be automated method. Virtual teams with anonymity is a feature of the Social App Manufacturing, is an important factor that increases the uncertainty of whether the completion of the project or reduction in visibility of the progress of the project. In this study, as one of how to manage the project of Social App Manufacturing environment, the impact of risk that can be used to quantitatively measure the impact of the risk of delay in development has on the project also proposes a measurement model. Effects of risk and type of the impact of risks associated with delays in the work schedule also define the characteristic function, measurement model that has been proposed, suggest the degree of influence measurement equation of risk of the project in accordance with the progressive. The advantage of this model, the project manager is able to ensure the visibility of the progress of the project. In addition, identify the project risk of work delays, and to take precautions.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.81-92
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• 2023

A privacy model is a technique that quantitatively restricts the possibility and degree of privacy breaches through privacy attacks. Representative models include k-anonymity, l-diversity, t-closeness, and differential privacy. While many privacy models have been studied, research on selecting the most suitable model for a given dataset has been relatively limited. In this study, we develop a system for recommending the suitable privacy model to prevent privacy breaches. To achieve this, we analyze the data features that need to be considered when selecting a model, such as data type, distribution, frequency, and range. Based on privacy model background knowledge that includes information about the relationships between data features and models, we recommend the most appropriate model. Finally, we validate the feasibility and usefulness by implementing a recommendation prototype system.

• Information Systems Review
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• v.25 no.4
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• pp.47-65
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• 2023

In this paper, we investigate how the online voting system can be a trust-based system from a technical perspective. Under four principles of voting, we finely evaluate the existing belief that offline voting is safer and more reliable than online voting based on procedural processes, technical principles. Many studies have suggested the ideas for implementing online voting system, but they have not attempted to strictly examine the technologies of online voting system from the perspective of voting requirements, and usually verification has been insufficient in terms of practical acceptance. Therefore, this study aims to analyze how the technologies are utilized to meet the demanding requirements of voting based on the technologies proven in the field. In addition to general data encryption, online voting requires more technologies for preventing data manipulation and verifying voting results. Moreover, high degree of confidentiality is required because voting data should not be exposed not only to outsiders but also to managers or the system itself. To this end, the security techniques such as Blind Signature, Bit Delegation and Key Division are used. In the case of blockchain-based voting, Mixnet and Zero-Knowledge Proof are required to ensure anonymity. In this study, the current status of the online voting system is analyzed based on the field system that actually serves. This study will enhance our understanding on online voting security technologies and contribute to build a more trust-based voting mechanism.