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Enabling Dynamic Multi-Client and Boolean Query in Searchable Symmetric Encryption Scheme for Cloud Storage System

  • Xu, Wanshan;Zhang, Jianbiao;Yuan, Yilin
    • 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.

Applying Keyword Analysis to Predicting Agriculture Product Price Index: The Case of the Chinese Farming Market

  • Wang, Zhi-yuan;Kwon, Ohbyung;Liu, Fan
    • Asia Pacific Journal of Business Review
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    • v.1 no.1
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    • pp.1-22
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    • 2016
  • The prediction of prices of agricultural products in the agriculture IT sector plays a significant role in the economic life of consumers and anyone engaged in agricultural business, and as these prices fluctuate more often than do other prices, the prediction of these prices holds a great deal of research promise. For this reason, academic literature has provided studies on the factors influencing the prices of agricultural products and the price index. However, as these factors vary, they are difficult to predict, resulting in the challenge of acquiring quantitative data. China is one example of a country without a reliable prediction system for prices of agricultural products. Fortunately, disclosed heterogeneous data can be found on the Internet, which allows for the effective collection of factors related to the prediction of these product prices through the use of text mining. The data provided online is valuable in that they reflect the opinions of the general public in real-time. Accordingly, this study aims to use heterogeneous data from the Internet and suggest a model predicting the prices of agricultural products before functional analyses. Toward this end, data analyses were conducted on the Chinese agricultural products market, one of the largest markets in the world.

k-Interest Places Search Algorithm for Location Search Map Service (위치 검색 지도 서비스를 위한 k관심지역 검색 기법)

  • Cho, Sunghwan;Lee, Gyoungju;Yu, Kiyun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.4
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    • pp.259-267
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    • 2013
  • GIS-based web map service is all the more accessible to the public. Among others, location query services are most frequently utilized, which are currently restricted to only one keyword search. Although there increases the demand for the service for querying multiple keywords corresponding to sequential activities(banking, having lunch, watching movie, and other activities) in various locations POI, such service is yet to be provided. The objective of the paper is to develop the k-IPS algorithm for quickly and accurately querying multiple POIs that internet users input and locating the search outcomes on a web map. The algorithm is developed by utilizing hierarchical tree structure of $R^*$-tree indexing technique to produce overlapped geometric regions. By using recursive $R^*$-tree index based spatial join process, the performance of the current spatial join operation was improved. The performance of the algorithm is tested by applying 2, 3, and 4 multiple POIs for spatial query selected from 159 keyword set. About 90% of the test outcomes are produced within 0.1 second. The algorithm proposed in this paper is expected to be utilized for providing a variety of location-based query services, of which demand increases to conveniently support for citizens' daily activities.

A Scalable Index for Content-based Retrieval of Large Scale Multimedia Data (대용량 멀티미디어 데이터의 내용 기반 검색을 위한 고확장 지원 색인 기법)

  • Choi, Hyun-HWa;Lee, Mi-Young;Lee, Kyu-Chul
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.726-730
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    • 2009
  • The proliferation of the web and digital photography has drastically increased multimedia data and has resulted in the need of the high quality internet service based on the moving picture like user generated contents(UGC). The keyword-based search on large scale images and video collections is too expensive and requires much manual intervention. Therefore the web search engine may provide the content-based retrieval on the multimedia data for search accuracy and customer satisfaction. In this paper, we propose a novel distributed index structure based on multiple length signature files according to data distribution. In addition, we describe how our scalable index technique can be used to find the nearest neighbors in the cluster environments.

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A study on automation of AV(Atomic Vulnerability) ID assignment (단위 취약점 식별자 부여 자동화에 대한 연구)

  • Kim, Hyung-Jong
    • Journal of Internet Computing and Services
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    • v.9 no.6
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    • pp.49-62
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    • 2008
  • AV (Atomic Vulnerability) is a conceptual definition representing a vulnerability in a systematic way, AVs are defined with respect to its type, location, and result. It is important information for meaning based vulnerability analysis method. Therefore the existing vulnerability can be expressed using multiple AVs, CVE (common vulnerability exposures) which is the most well-known vulnerability information describes the vulnerability exploiting mechanism using natural language. Therefore, for the AV-based analysis, it is necessary to search specific keyword from CVE's description and classify it using keyword and determination method. This paper introduces software design and implementation result, which can be used for atomic vulnerability analysis. The contribution of this work is in design and implementation of software which converts informal vulnerability description into formal AV based vulnerability definition.

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e-Cohesive Keyword based Arc Ranking Measure for Web Navigation (연관 웹 페이지 검색을 위한 e-아크 랭킹 메저)

  • Lee, Woo-Key;Lee, Byoung-Su
    • Journal of KIISE:Databases
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    • v.36 no.1
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    • pp.22-29
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    • 2009
  • The World Wide Web has emerged as largest media which provides even a single user to market their products and publish desired information; on the other hand the user can access what kind of information abundantly enough as well. As a result web holds large amount of related information distributed over multiple web pages. The current search engines search for all the entered keywords in a single webpage and rank the resulting set of web pages as an answer to the user query. But this approach fails to retrieve the pair of web pages which contains more relevant information for users search. We introduce a new search paradigm which gives different weights to the query keywords according to their order of appearance. We propose a new arc weight measure that assigns more relevance to the pair of web pages with alternate keywords present so that the pair of web pages which contains related but distributed information can be presented to the user. Our measure proved to be effective on the similarity search in which the experimentation represented the e~arc ranking measure outperforming the conventional ones.

Comparison of Research Characteristics in Western, Chinese Traditional Medicine and Korean Medicine on Psoriasis (건선의 동서의학적 연구 특징의 비교)

  • Lee, Sundong;Jung, Seyoung;Lee, Seung eun
    • The Journal of Korean Medicine
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    • v.42 no.2
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    • pp.72-81
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    • 2021
  • Objectives: We compared research characteristics of western medicine, Chinese medicine and Korean medicine on causes, mechanisms, types, treatments and prevention of psoriasis. Methods: For western medicine, "Psoriasis" was used as keyword on Pubmed, for Chinese medicine, "銀屑病" and "中医" on CNKI (China National Knowledge Infrastructure" and for Korean medicine, "건선" on OASIS. Keyword searches were done for papers and books published after 2010. For Chinese medicine, there were more in-depth searches done for "從血論 (血熱, 血瘀, 血燥)" and "陽虛症". Results: Western medicine puts an emphasis on the foci, and approaches it from molecular and genetic levels based on molecular biology; while it views psoriasis as a disease with multiple possible causes, it ultimately sees it as an inflammation that is immunity-mediated. Western medicine seeks to suppress cytokine in order to prevent and eliminate inflammation at each stage of treatment While they are effective short-term, psoriasis recurs shortly after. Chinese and Korean medicines categorize psoriasis as an internal comprehensive systemic diseases that encompasses the patient's physical and mental characteristics, and defines it as a disease that has many causes and mechanisms such as "血熱, 血瘀, 血燥" and "陽虛". They use herbal medicine, acupuncture, and lifestyle interventions to improve the overall health of the patient in addition to treating psoriasis. Treatments are effective, but it takes relatively longer to see results, and can recur. Conclusion: In order for more progress to happen on psoriasis treatment, each branch of medicine must exchange knowledge and information more frequently.

An Analysis for the Student's Needs of non-face-to-face based Software Lecture in General Education using Text Mining (텍스트 마이닝을 이용한 비대면 소프트웨어 교양과목의 요구사항 분석)

  • Jeong, Hwa-Young
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.105-111
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    • 2022
  • Multiple-choice survey types have been mainly performed to analyze students' needs for online classes. However, in order to analyze the exact needs of students, unstructured data analysis by answer for essay question is required. Big data is applied in various fields because it is possible to analyze unstructured data. This study aims to investigate and analyze what students want subjects or topics for software lecture in general education that process on non-face-to-face online teaching methods. As for the experimental method, keyword analysis and association analysis of big data were performed with unstructured data by giving a subjective questionnaire to students. By the result, we are able to know the keyword what the students want for software lecture, so it will be an important data for planning and designing software lecture of liberal arts in the future as students can grasp the topics they want to learn.

The Influence of Factors Related to Preparation by Pre-Service Teachers for Gender Equity Education and Teaching Gender Equity

  • Kwon, Yoo-Jin;Jeon, Se-Kyung
    • International Journal of Human Ecology
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    • v.11 no.1
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    • pp.97-107
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    • 2010
  • Gender equity education is ineffective in a public school system even though gender equity education is a current issue in South Korean education. One of the problems is attributed to teacher education because no better gender equity education can be accomplished without teacher preparation. Therefore, the effectiveness of teachers is a very important keyword in teacher education. This study examines learning experience, gender equity value, teacher preparation for gender equity education of pre-service teachers in Gonju, South Korea, the factors that influence teacher preparation for gender equity education, and the instruction of gender equity. A survey was delivered to pre-service teachers in 2008, and the data of 350 pre-service teachers were analyzed. MANOVA and Multiple Regressions were used for analyzing the data. The results will contribute to the development of effective teacher education for gender equity education and information on a partnership between the family and the public school system that is centered on gender equity education.

User Category-Based Intelligent e-Commerce Meta-Search Engine

  • U, Sang-Hun;Kim, Gyeong-Pil;Kim, Chang-Uk
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.346-355
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    • 2005
  • In this paper, we propose a meta-search engine which provides distributed product information through a unified access to multiple e-commerce. The meta-search engine proposed in this paper performs the following functions: (I) The user is able to create a category-based user query, (2) by using the WordNet, the query is semantical refined fined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user's search intention, by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

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