• Journal of Korea Multimedia Society
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• v.18 no.8
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• pp.915-924
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• 2015

With growing popularity of cloud computing services, users can more easily manage massive amount of data by outsourcing them to the cloud, or more efficiently analyse large amount of data by leveraging IT infrastructure provided by the cloud. This, however, brings the security concerns of sensitive data. To provide data security, it is essential to encrypt sensitive data before uploading it to cloud computing services. Although data encryption helps provide data security, it negatively affects the performance of massive data analytics because it forbids the use of index and mathematical operation on encrypted data. Thus, in this paper, we propose a novel algorithm which enables to efficiently process a large amount of encrypted data. In particular, we propose a novel top-k processing algorithm on the massive amount of encrypted data in the cloud computing environments, and verify the performance of the proposed approach with real data experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5153-5170
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• 2016

The benefit of the scalability and flexibility inherent in cloud computing motivates clients to upload data and computation to public cloud servers. Because data is placed on public clouds, which are very likely to reside outside of the trusted domain of clients, this strategy introduces concerns regarding the security of sensitive client data. Thus, to provide sufficient security for the data stored in the cloud, it is essential to encrypt sensitive data before the data are uploaded onto cloud servers. Although data encryption is considered the most effective solution for protecting sensitive data from unauthorized users, it imposes a significant amount of overhead during the query processing phase, due to the limitations of directly executing operations against encrypted data. Recently, substantial research work that addresses the execution of SQL queries against encrypted data has been conducted. However, there has been little research on top-k join query processing over encrypted data within the cloud computing environments. In this paper, we develop an efficient algorithm that processes a top-k join query against encrypted cloud data. The proposed top-k join processing algorithm is, at an early phase, able to prune unpromising data sets which are guaranteed not to produce top-k highest scores. The experiment results show that the proposed approach provides significant performance gains over the naive solution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.307-316
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• 2016

Reversible data hiding is a technique to hide any data without affecting the original image. Zhang proposed the encryption of original image and a data hiding scheme in encrypted image. First, the encrypted image is decrypted and uses the fluctuation function which exploits the spatial correlation property of decrypted image to extract hidden data. In this paper, the new fluctuation function is proposed to reduce errors which arise from the process extracting hidden data and the performance is verified by simulation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1301-1313
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• 2012

The importance of protecting personal information is increasing day by day due to invasion of privacy, and data encryption is the most effective way to eliminate it. However, current data encryption methods tend to having problems for applying in practical fields because of critical issues such as low performances and frequent changes of applications. In order to find proper solutions for data security, this paper reviews data encryption technologies and experiments on performance of encrypted data in Oracle Database. On top of that, this paper analyses a data encryption technique not only efficiency of performance but also minimization of application changes.

• Journal of KIISE
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• v.43 no.2
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• pp.143-151
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• 2016

Data deduplication is an important technique for cloud storage savings. These techniques are especially important for encrypted data because data deduplication over plaintext is basically vulnerable for data confidentiality. We examined encrypted data deduplication with the aid of a key issuing server and compared Convergent Encryption with a technique created by M.Bellare et al. In addition, we implemented this technique over not only Dropbox but also an open cloud storage service, Openstack Swift. We measured the performance for this technique over Dropbox and Openstack Swift. According to our results, we verified that the encrypted data deduplication technique with the aid of a key issuing server is a feasible and versatile method.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.243-253
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• 2005

Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of query-aware decryption for efficient processing of queries against encrypted XML data. Query-aware decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to 6 times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.

• Current Optics and Photonics
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• v.3 no.5
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• pp.390-400
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• 2019

Encrypted images obtained through double random phase-encoding (DRPE) occupy considerable storage space. We propose efficient compression schemes to reduce the size of the encrypted data. In the proposed schemes, two state-of-art compression methods of JPEG and JP2K are applied to the quantized encrypted phase images obtained by combining the DRPE algorithm with the virtual photon counting imaging technique. We compute the nonlinear cross-correlation between the registered reference images and the compressed input images to verify the performance of the compression of double random phase-encoded images. We show quantitatively through experiments that considerable compression of the encrypted image data can be achieved while security and authentication factors are completely preserved.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.413-426
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• 2017

In this paper, we propose an adder that can be applied to data encrypted with a fully homomorphic encryption scheme and an addition method with improved performance that can be applied when adding multiple data. The proposed arithmetic adder is based on the Kogge-Stone Adder method with the optimal circuit level among the existing hardware-based arithmetic adders and suitable to apply the cryptographic SIMD (Single Instruction for Multiple Data) function on encrypted data. The proposed multiple addition method does not add a large number of data by repeatedly using Kogge-Stone Adder which guarantees perfect addition result. Instead, when three or more numbers are to be added, three numbers are added to C (Carry-out) and S (Sum) using the full-adder circuit implementation. Adding with Kogge-Stone Adder is only when two numbers are finally left to be added. The performance of the proposed method improves dramatically as the number of data increases.

• Journal of KIISE
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• v.43 no.12
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• pp.1437-1457
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• 2016

In outsourced databases, the cloud provides an authorized user with querying services on the outsourced database. However, sensitive data, such as financial or medical records, should be encrypted before being outsourced to the cloud. Meanwhile, k-Nearest Neighbor (kNN) query is the typical query type which is widely used in many fields and the result of the kNN query is closely related to the interest and preference of the user. Therefore, studies on secure kNN query processing algorithms that preserve both the data privacy and the query privacy have been proposed. However, existing algorithms either suffer from high computation cost or leak data access patterns because retrieved index nodes and query results are disclosed. To solve these problems, in this paper we propose a new kNN query processing algorithm on the encrypted database. Our algorithm preserves both data privacy and query privacy. It also hides data access patterns while supporting efficient query processing. To achieve this, we devise an encrypted index search scheme which can perform data filtering without revealing data access patterns. Through the performance analysis, we verify that our proposed algorithm shows better performance than the existing algorithms in terms of query processing times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.331-337
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• 2017

In this work, we propose an improved form of Zhang's reversible data hiding technique in encrypted image. In the original work, average value of neighboring pixels is used for fluctuation calculation which fails to give good performance. In proposed scheme, to reduce the bit error rate a new function is calculated by summing difference from four neighboring pixels for measuring fluctuation. Moreover, modified calculation of fluctuation function is also proposed where border pixels are considered. The simulation results show that the performance of proposed method outperforms Zhang's and Hong's work. From the results, more information can be sent by using proposed system