• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1182-1188
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• 2014

Recently, the research on database outsourcing has been actively done with the popularity of cloud computing. However, because users' data may contain sensitive personal information, such as health, financial and location information, the data encryption methods have attracted much interest. Existing data encryption schemes process a query without decrypting the encrypted databases in order to support user privacy protection. On the other hand, to efficiently handle the large amount of data in cloud computing, it is necessary to study the distributed index structure. However, existing index structure and query processing algorithms have a limitation that they only consider single-column query processing. In this paper, we propose a grid-based multi column indexing scheme and an encrypted query processing algorithm. In order to support multi-column query processing, the multi-dimensional index keys are generated by using a space decomposition method, i.e. grid index. To support encrypted query processing over encrypted data, we adopt the Hilbert curve when generating a index key. Finally, we prove that the proposed scheme is more efficient than existing scheme for processing the exact and range query.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.85-92
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• 2005

Recently, query processing techniques for the multi-dimensional data like images have been widely used to perform content-based retrieval of the data . Range query and Nearest neighbor query are widely used multi dimensional queries . This paper Proposes the efficient pruning strategies for k-nearest neighbor query in R-tree variants indexing structures. Pruning strategy is important for the multi-dimensional indexing query processing so that search space can be reduced. We analyzed the Pruning strategies and perform experiments to show overhead and the profit of the strategies. Finally, we propose best use of the strategies.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.521-531
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• 2003

Multi-level geographic data can be mainpulated by a window query such as a zoom operation. In order to handle multi-level geographic data efficiently, a spatial indexing method supporting a window query is needed. However, the conventional spatial indexing methods are not efficient to access multi-level geographic data quickly. To solve it, other a few spatial indexing methods for multi-level geographic data are known. However these methods do not support all types of multi-level geographic data. This paper presents a new efficient spatial indexing method, the MLR-tree for window query of multi-level geographic data. The MLR-tree offers both high search performance and no data redundancy. Experiments show them. Moreover, the MLR-tree supports all types of multi-level geographic data.

• The Journal of Korean Association of Computer Education
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• v.7 no.4
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• pp.43-50
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• 2004

Multi-lingual query answering system is the system which answers on the queries with several languages. LASSO[l] is the system that aims to answer the multi-lingual query. In this paper, we design and implement a Korean analysis system for LASSO. The Korean analysis system for query answering needs processing techniques of dialogue style. And the system must be practical and general so as to use on various domains. This system uses not dialogue processing techniques with high cost and low utility but heuristic rules with low cost and high utility. It is designed and implemented as a Korean interface of multi-lingual query answering system. The techniques of this system highly contribute to information retrieval and Korean analysis researches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1286-1306
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• 2022

Searchable symmetric encryption (SSE) provides a safe and effective solution for retrieving encrypted data on cloud servers. However, the existing SSE schemes mainly focus on single keyword search in single client, which is inefficient for multiple keywords and cannot meet the needs for multiple clients. Considering the above drawbacks, we propose a scheme enabling dynamic multi-client and Boolean query in searchable symmetric encryption for cloud storage system (DMC-SSE). DMC-SSE realizes the fine-grained access control of multi-client in SSE by attribute-based encryption (ABE) and novel access control list (ACL), and supports Boolean query of multiple keywords. In addition, DMC-SSE realizes the full dynamic update of client and file. Compared with the existing multi-client schemes, our scheme has the following advantages: 1) Dynamic. DMC-SSE not only supports the dynamic addition or deletion of multiple clients, but also realizes the dynamic update of files. 2) Non-interactivity. After being authorized, the client can query keywords without the help of the data owner and the data owner can dynamically update client's permissions without requiring the client to stay online. At last, the security analysis and experiments results demonstrate that our scheme is safe and efficient.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1995.11a
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• pp.79-88
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• 1995

Most works done so far have concentrated on developing data modeling techniques such as multi-level relation for data protection. These techniques, however, cannot be applied to practical area. This is because they require new queries or new architectures. In this paper, we propose a query processing technique for multi-level databases using horizontal partitioning and views, which does not need any change in database architecture and query language.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.294-297
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• 2000

Among the multi-dimensional query types, ranking query is needed if we want the object one by one until we satisfy for the result. In multi-dimensional indexing structures like R-tree or its variants, not many methods are introduced in this area. In this paper, we introduce new ranking query processing algorithm which use the filtering mechanism in the R-tree variants.

• ETRI Journal
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• v.38 no.6
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• pp.1197-1206
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• 2016

Performing continuous skyline queries of dynamic data sets is now more challenging as the sizes of data sets increase and as they become more volatile due to the increase in dynamic updates. Although previous work proposed support for such queries, their efficiency was restricted to small data sets or uniformly distributed data sets. In a production database with many concurrent queries, the execution of continuous skyline queries impacts query performance due to update requirements to acquire exclusive locks, possibly blocking other query threads. Thus, the computational costs increase. In order to minimize computational requirements, we propose a method based on a multi-layer grid structure. First, relational data object, elements of an initial data set, are processed to obtain the corresponding multi-layer grid structure and the skyline influence regions over the data. Then, the dynamic data are processed only when they are identified within the skyline influence regions. Therefore, a large amount of computation can be pruned by adopting the proposed multi-layer grid structure. Using a variety of datasets, the performance evaluation confirms the efficiency of the proposed method.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.673-682
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• 2005

Distance browsing queries, namely k-nearest neighbor queries, are the most important queries in spatial database applications, e.g., Geographic Information Systems(GISs). Recently, GIS applications trends to extend themselves toward wide multi-user environments such as the Web. Since many techniques for such queries, where Hjaltason and Samet's algorithm is the most efficient one, were optimized for only one query, we need to complement them suitable for multi-user environments. It can be a good approach that we store many individual query results in a cache, i.e., query result caching and reuse them in evaluating incoming queries, j.e., query result matching. In this paper, we propose a complementary Hjaltason and Samet's algerian capable of reusing previous query results in a cache for answering distance browsing queries in multi-user GIS environments. Our experimental results conform the efficiency of our approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3937-3954
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• 2014

With the increasing electricity consumption and the wide application of renewable energy sources, energy auction attracts a lot of attention due to its economic benefits. Many schemes have been proposed to support energy auction in smart grid. However, few of them can achieve range query, ranked search and personalized search. In this paper, we propose an efficient multi-keyword range query (EMRQ) scheme, which can support range query, ranked search and personalized search simultaneously. Based on the homomorphic Paillier cryptosystem, we use two super-increasing sequences to aggregate multidimensional keywords. The first one is used to aggregate one buyer's or seller's multidimensional keywords to an aggregated number. The second one is used to create a summary number by aggregating the aggregated numbers of all sellers. As a result, the comparison between the keywords of all sellers and those of one buyer can be achieved with only one calculation. Security analysis demonstrates that EMRQ can achieve confidentiality of keywords, authentication, data integrity and query privacy. Extensive experiments show that EMRQ is more efficient compared with the scheme in [3] in terms of computation and communication overhead.