• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.421-429
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• 2006

Recently, DHT-based Structured P2P System have a attention to scalability and providing efficient lookup by routing. Retrieving content of DHT-based P2P require knowledge of the exact identifier of sharing file. But user may wish to search for sharing file using descriptive keyword or content. To resolve the problem, this paper propose Extended-CAN mechanism to support keyword search. We defined content-based keyword and identifier of sharing file, and PLS extended to KID and CKD for keyword, common keyword processing. As a result, Extended-CAN mechanism provide efficient keyword search for DHT-based Structured P2P System.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1328-1342
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• 2013

Searchable encryption is a cryptographic protocol for searching a document in encrypted databases. A simple searchable encryption protocol, which is capable of using only one keyword at one time, is very limited and cannot satisfy demands of various applications. Thus, designing a searchable encryption with useful additional functions, for example, conjunctive keyword search, is one of the most important goals. There have been many attempts to construct a searchable encryption with conjunctive keyword search. However, most of the previously proposed protocols are based on public-key cryptosystems which require a large amount of computational cost. Moreover, the amount of computation in search procedure depends on the number of documents stored in the database. These previously proposed protocols are not suitable for extremely large data sets. In this paper, we propose a new searchable encryption protocol with a conjunctive keyword search based on a linked tree structure instead of public-key based techniques. The protocol requires a remarkably small computational cost, particularly when applied to extremely large databases. Actually, the amount of computation in search procedure depends on the number of documents matched to the query, instead of the size of the entire database.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.257-267
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• 2012

Many advertisers utilize sponsored search in search engines since customers want to find relevant information on their purchases from the search engines. Many factors have influences on price per click of the sponsored search. These influences are different based on the types of keywords such as search/experience or prominent/specific. However, differences of the influences have not been studied well. Thus, this study wants to identify the differences of the influences according the type of keywords. One month data of keyword advertising were collected from Naver. The influences of search number, click through rate, and competition on price per click were different according to the keyword types.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5671-5693
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• 2017

With the rapid development of cloud computing, more and more data owners are motivated to outsource their data to cloud for various benefits. Due to serious privacy concerns, sensitive data should be encrypted before being outsourced to the cloud. However, this results that effective data utilization becomes a very challenging task, such as keyword search over ciphertexts. Although many searchable encryption methods have been proposed, they only support exact keyword search. Thus, misspelled keywords in the query will result in wrong or no matching. Very recently, a few methods extends the search capability to fuzzy keyword search. Some of them may result in inaccurate search results. The other methods need very large indexes which inevitably lead to low search efficiency. Additionally, the above fuzzy keyword search methods do not support access control. In our paper, we propose a searchable encryption method which achieves fuzzy search and access control through algorithm design and Ciphertext-Policy Attribute-based Encryption (CP-ABE). In our method, the index is small and the search results are accurate. We present word pattern which can be used to balance the search efficiency and privacy. Finally, we conduct extensive experiments and analyze the security of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.97-104
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• 2017

In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.59-72
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• 2013

In this paper, we propose a keyword query processing technique based on semantic relationships for OWL data. The proposed keyword query processing technique can improve user's search satisfaction by performing two types of associative search. The first associative search uses information inferred by the relationships between classes or properties during keyword query processing. And it supports to search all information resources that are either directly or indirectly related with query keywords by semantic relationships between information resources. The second associative search returns not only information resources related with query keywords but also values of properties of them. We design a storage schema and index structures to support the proposed technique. And we propose evaluation functions to rank retrieved information resources according to three criteria. Finally, we evaluate the validity and accuracy of the proposed technique through experiments. The proposed technique can be utilized in a variety of fields, such as paper retrieval and multimedia retrieval.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.246-251
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• 2016

Recently, the influence of SNS and online media is rapidly growing with a consequent increase in the interest of marketing using these tools. Blog marketing can increase the ripple effect and information delivery in marketing at low cost by prioritizing keyword search results of influential portal sites. However, because of the tough competition to gain top ranking of search results of specific keywords, long-term and proactive efforts are needed. Therefore, we propose a new method that recommends associated keyword groups with the possibility of higher exposure of the blog. The proposed method first collects the documents of blog including search results of target keyword, and extracts and filters keyword with higher association considering the frequency and location information of the word. Next, each associated keyword is compared to target keyword, and then associated keyword group with the possibility of higher exposure is recommended considering the information such as their association, search amount of associated keyword per month, the number of blogs including in search result, and average writhing date of blogs. The experiment result shows that the proposed method recommends keyword group with higher association.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.3-15
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• 2008

In 2000, Song. et. al. firstly proposed the Searchable Keyword Encryption System that treated a problem to search keywords on encrypted data. Since then, various Searchable Keyword Encryption Systems based on symmetric and asymmetric methods have been proposed. However, the Searchable Keyword Encryption Systems based on public key system has a problem that the index size for searching keywords on encrypted data increases linearly according to the number of keyword. In this paper, we propose the method that reduces the index size of Searchable Keyword Encryption based on public key system using Bloom Filter, apply the proposed method to PEKS(Public key Encryption with Keyword Search) that was proposed by Boneh. et. al., and analyze efficiency for the aspect of storage.