• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3182-3203
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• 2023

With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.912-924
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• 2003

Design restructuring improves software quality by reorganizing design elements and reduces maintenance cost. Object-oriented metrics can help to detect design flaws and find transformations to reorganize design elements. Basically, the transformations must preserve the behavior of an initial system. This paper describes a metric based restructuring technique preserving the behavior of object-oriented designs, founded on set theory, and gives its validity by applying the technique to applications written in Java. This paper also compares the technique with a technique using simulated annealing algorithm to show its effectiveness.

• ETRI Journal
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• v.34 no.1
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• pp.66-75
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• 2012

This paper proposes a privacy-preserving database encryption scheme that provides access pattern hiding against a service provider. The proposed scheme uses a session key to permute indices of database records each time they are accessed. The proposed scheme can achieve access pattern hiding in situations in which an adversary cannot access the inside of the database directly, by separating the entity with an index table and data table and permuting both the index and position where the data are stored. Moreover, it is very efficient since only O(1) server computation and communication cost are required in terms of the number of the data stored. It can be applied to cloud computing, where the intermediate entities such as cloud computing service provider can violate the privacy of users or patients.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.50-59
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• 1997

This paper is on the generalized singular perturbation approximation (GSPA) preserving the discrete positive real property. We transform the discrete positive real(PR) system into a stochastically banlanced system and get the reduced order discrete system from the GSPA of the full order stochastically balanced system. eSPECIALLY, WHEN THE FREE PARAMETER OF THE gspa IS .+-.1, we show that the reduced order discrete system retains stability, minimality, and positive real and stochstically balancing properties. And we derived the .inf.-norm error bound with the reduced order discrete strictly positive real(SPR) system by the proposed method. Finally, we give an example to ascertain the properties of the proposed reduced order discrete system and to compare with the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.166-173
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• 2005

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.81-95
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• 2006

The usual arithmetic operations on real numbers can be extended to arithmetical operations on fuzzy intervals by means of Zadeh's extension principle based on a t-norm T. A t-norm is called consistent with respect to a class of fuzzy intervals for some arithmetic operation if this arithmetic operation is closed for this class. It is important to know which t-norms are consistent with a particular type of fuzzy intervals. Recently Dombi and Gyorbiro proved that addition is closed if the Dombi t-norm is used with two bell-shaped fuzzy intervals. A result proved by Mesiar on a strict t-norm based shape preserving additions of LR-fuzzy intervals with unbounded support is recalled. As applications, we define a broader class of bell-shaped fuzzy intervals. Then we study t-norms which are consistent with these particular types of fuzzy intervals. Dombi and Gyorbiro's results are special cases of the results described in this paper.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.35-44
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• 2009

To protect sensitive personal information, data will be stored in encrypted form. However in order to retrieve these encrypted data without decryption, there need efficient search methods to enable the retrieval of the encrypted data. Until now, a number of searchable encryption schemes have been proposed but these schemes are not suitable when dynamic users who have the permission to access the data share the encrypted data. Since, in previous searchable encryption schemes, only specific user who is the data owner in symmetric key settings or has the secret key corresponding to the public key for the encrypted data in asymmetric key settings can access to the encrypted data. To solve this problem, Stephen S. Yau et al. firstly proposed the controlled privacy preserving keyword search scheme which can control the search capabilities of users according to access policies of the data provider. However, this scheme has the problem that the privacy of the data retrievers can be breached. In this paper, we firstly analyze the weakness of Stephen S. Yau et al.'s scheme and propose privacy preserving keyword search with access control. Our proposed scheme preserves the privacy of data retrievers.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.160-161
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• 2010

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.3-6
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• 2003

A nonlinear iterative filtering based on local statistics and anisotropic diffusion is introduced. Local statistics determines the diffusion coefficient at each iteration step. Anisotropic diffusion can be seen as estimates a piecewise smooth image from the noisy input image in the experimental section, our results are shown to suppress noise with preserving the edges. Therefore, it enhances the image and improves performance.