• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1077-1086
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• 2023

The searchable encryption model allows to selectively search for encrypted data stored on a remote server. In a real-world scenarios, the model must be able to support multiple search keywords, multiple data owners/users. In this paper, these models are referred to as Multi Ranked Searchable Encryption model. However, at the time this paper was written, the proposed models use fully-trusted trapdoor centers, some of which assume that the connection between the user and the trapdoor center is secure, which is unlikely that such assumptions will be kept in real life. In order to improve the practicality and security of these searchable encryption models, this paper proposes a new Multi Ranked Searchable Encryption model which uses random keywords to protect search words requested by the data downloader from an honest-but-curious trapdoor center with an external attacker without the assumptions. The attacker cannot distinguish whether two different search requests contain the same search keywords. In addition, experiments demonstrate that the proposed model achieves reasonable performance, even considering the overhead caused by adding this protection process.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.3-14
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• 2011

In recent days, people used to store and share the data with other users through the web storage services. It is more convenient for using the data, but it raise problems such as access control of stored data and privacy exposure to untrusted server. Searchable encryption is used to share the data securely in multi-user setting. Especially in the multi-user setting, the revoked users should not be able to search the data and access the stored data. That is, it should be considered the security from revoked users. However in the existing schemes, the revoked users can decrypt the shared data by passive attack. Proposed scheme is the secure searchable encryption that resolves the problem and guarantees the security for revoked users.

• The KIPS Transactions:PartC
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• v.18C no.4
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• pp.199-206
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• 2011

Removable Storage provides the excellent portability with light weight and small size which fits in one's hand, many users have recently turned attention to the high-capacity products. However, due to the easy of portability for Removable Storage, Removable Storage are frequently lost and stolen and then many problems have been occurred such as the leaking of private information to the public. The advent of remote storage services where data is stored throughout the network, has allowed an increasing number of users to access data. The main data of many users is stored together on remote storage, but this has the problem of disclosure by an unethical administrator or attacker. To solve this problem, the encryption of data stored on the server has become necessary, and a searchable encryption system is needed for efficient retrieval of encrypted data. However, the existing searchable encryption system has the problem of low efficiency of document insert/delete operations and multi-keyword search. In this paper, an efficient searchable encryption system is proposed.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.802-816
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• 2021

Purpose: In this paper, we propose a direction of future research and development to be carried out in the passive tracking field by deriving a white space with enhanced search formula of patent analysis. Method: In this paper, we derive a white space by identifying the direction and the flow of technology change and by matrixing the object and solution through extensive patent search with enhanced search formula and analysis in the field of passive tracking technology. Result: By the proposed scheme, 'multi-target positioning and tracking' and '3D positioning technology' using artificial intelligence, adaptive/hybrid positioning technology, and radar/antenna were derived as white space technologies and confirmed with absence of any services or products. Conclusion: The derived white space technologies from this paper are the areas where patent applications are not active and there are not many prior patents, thus it is necessary to secure the rights through more active R&D and patent application activities.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.569-580
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• 2008

Web services are the current most promising technology for service oriented architecture(SOA) implementations. However, in spite of the large scale acceptance of web services, they have been relegated to internal integration projects, and the grand vision of virtual enterprises where partners can be integrated on demand is yet to be realized. The main reason is that the current standards of web services are not very suitable for the dynamic web service discovery and integration. In this paper, we present a novel SemanticBPEL solution that merges the benefit of WS-BPEL, with the advantage of OWL-S for building a semi-automatic web service composition system. In particular, this work proposes a multi-phase search method for solving dynamic discovery and integration problems of web services. The proposed method is compared with the existing keyword based retrieval method. These comparisons show that our approach outperforms the existing method.

• Journal of Korean Library and Information Science Society
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• v.30 no.2
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• pp.123-153
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• 1999

This article aims at finding the ways, on the basis of the studies about the behaviors to search the existing CD-ROM databases, so that the searchers who retrieve the on-line MEDLINE used in the medical libraries can use the data more efficiently than now. We gave the questionnaires to the librarians in 60 medical libraries and searched the literatures and realities on the behaviors of the data uses to examine the search behaviors of the MEDLINE in the medical libraries. The result is as follows: 1) The medical data system rate for single users was $53\%$ and the ons for multi users $43\%$. As for the time which users retrieve for a week, under two hours was $75\%$, between 3 and 8 hours $18.3\%$, and eve. 9 hours $6.7\%$. 2) The increasing factors of the search result are (1) an enough discussion and interview between librarians and users, and (2) the use of the correct indexing terms, Thesaurus, and Keyword. In principle users must search directly. However, the librarians searched instead in case that the retrieval result was under two hours a week$(75\%)$. 3) As for the search fee, $91\%$ was free and $9\%$ was charged. Also search effectiveness was enhanced by the means of Inter-Library Loan Service & Information Network. 4) The medical librarians answered the questionnaire that they need the application education of professional knowledge, medical terms(thesaurus) and electronic medium, and also they need the computer education, interview technique and reeducation to give a satisfactory service. 5) As for the satisfactory degree of MEDLINE application, they answered $44.6\%$ for economy, $38.2\%$ for the conveniency of the time required, and $58.9\%$ for the users' search satisfaction answered respectively. 6) The application of MEDLINE system enhanced the medical libraries' image and had an effect on the users' satisfaction of using the data and search, the data activities and the research achievement. 7) In the past MeSH was used but as the time passes CD-ROM MEDLINE search behavior was preferred to On-line one.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.502-510
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• 2012

As defense science and technology are developing, smart weapons are being developed continually. The collection and analysis of the future strategic weapon information from all over the world have become a greater priority because information sharing became active. So, a system to manage and analyze heterogeneous defense intelligence is required. Semantic Web is the next generation knowledge information management technology for integrating, searching and navigating heterogeneous knowledge resource. Recently, Semantic Web is wildly being used in intelligent information management system. Semantic Web supports the analysis with the high reliability because it supports the simple keyword search as well as the semantic based information retrieval. In this paper, we propose the semantic web based multi-dimensional information analysis system on the national defense weapons that constructs ontology for various weapons information such as weapon specifications, nations, manufacturers and technologies and searches and analyses the specific weapon based on ontology. The proposed system supports the semantic search and multi-dimensional information analysis based on the relations between weapon specifications. Also, our system improves the efficiency on acquiring smart weapon information because it is developed with ontology based on military experts' knowledge and various web documents related with various weapons and intelligent search service.

• The Journal of Korean Medicine
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• v.28 no.3 s.71
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• pp.116-125
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• 2007

Objective : To overview the protocols of clinical acupuncture research on cancer in the USA. Methods : Using 'acupuncture' and 'cancer' as keyword search terms in Clinical Trials. gov, 28 clinical studies were found. Three studies by non-American institutions were excluded and 25 studies were analyzed. Analytic parameters were cancer condition, primary outcome, research institution, study design, and acupuncture intervention. Results : Breast cancer was the most frequent single condition in the searched protocols. Pain and quality of life were the primary outcomes in many studies. Memorial Sloan-Kettering Cancer Centerin New York has performed the largest number of acupuncture cancer studies. The majority of studies were randomized controlled trials with active controls or placebo/sham controls. Total enrollment varied between the range of 10 and 700 subjects and ages of these subjects were at least above 18 years old (except one protocol). Most protocols had strict exclusion criteria for acupuncture needling such as bleeding disorders, infection, heart disorder, and central nervous system disorder. Conclusions : Clinical acupuncture studies for cancer patients have focused on pain, quality of life, and side effects induced by anti-cancer therapies. Re-evaluation and cautions for strict exclusion criteria in foreign countries are required to perform multi-national acupuncture trials.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.