• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.906-909
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• 2013

The Semantic Web is leading us to a world of information sharing by enabling distributed knowledge aggregation and creation. RDF is the foundations of the Semantic Web. For secure Semantic web we need to secure RDF as well. Unauthorized access to an RDF document can change or damage its semantics or manipulate the relations between resources. This article includes the study of RDF security issues and analysis of the existing solutions. After finding limitations of existing solution, a hybrid approach has been proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1599-1618
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• 2024

Access control has always been one of the effective methods to protect data security. However, in new computing environments such as big data, data resources have the characteristics of distributed cross-domain sharing, massive and dynamic. Traditional access control mechanisms are difficult to meet the security needs. This paper proposes CACM-MMSR to solve distributed cross-domain access control problem for massive resources. The method uses blockchain and smart contracts as a link between different security domains. A permission decision model migration method based on access control logs is designed. It can realize the migration of historical policy to solve the problems of access control heterogeneity among different security domains and the updating of the old and new policies in the same security domain. Meanwhile, a semantic reasoning-based permission decision method for unstructured text data is designed. It can achieve a flexible permission decision by similarity thresholding. Experimental results show that the proposed method can reduce the decision time cost of distributed access control to less than 28.7% of a single node. The permission decision model migration method has a high decision accuracy of 97.4%. The semantic reasoning-based permission decision method is optimal to other reference methods in vectorization and index time cost.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.595-602
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• 2015

One of the challenges of the digital forensics is how to handle certain amounts of data efficiently. Although reliable and various approximate matching algorithms have been presented to quickly identify similarities between digital objects, its practical effectiveness to identify the semantic similarity is low because of frequent false positives. To solve this problem, we suggest adding a pre-processing of the approximate matching target dataset to increase matching accuracy while maintaining the reliability of the approximate matching algorithm. To verify the effectiveness, we experimented with two datasets of eml and hwp using sdhash in order to identify the semantic similarity.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1752-1761
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• 2007

Location-based services are a recent concept that integrates a mobile device's location with other information in order to provide added value to a user. Although Location-based Services provide users with comfortable information, it is a complex task to manage and share heterogeneous and numerous data in decentralized environments. In this paper, we propose the Semantic LBS Model as one of the solution to resolve the problem. The Semantic LBS Model is a LBS middleware model that includes an ontology-based data model for LBS POI information and its processing mechanism based on Semantic Web technologies. Our model enables POI information to be described and retrieved over various domain-specific ontologies based on our proposed POIDL ontology. This mechanism provide rich expressiveness, interoperability, flexibility in describing and using information about POls, and it can enhance POI retrieval services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.223-234
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• 2011

For advanced database security, various researches and challenges are being done to keep pace with new information technologies. We suggests new extended access control that make it possible to conform security policies even with uncertain context and purpose. There may be a discrepancy between the syntactic phrase in security policies and that in queries, called semantic gap problem. New access control derive semantic implications from context and purpose hierarchy tree and control the exceed privileges using semantic gap factor calculating the degree of the discrepancy. And then, We illustrate prototype system architecture and show performance comparison with existing access control methods.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.894-901
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• 2013

This study is aim to research trend of private security and to suggest direction of improvement to sector of private security. This study has been to analyzed to be useful social network analysis(particularly Degree Centrality and Clossness Centrality) for using typical research method about trend of academic subject. As a result of Degree Centrality and Clossness Centrality, Individual factors such as Job Stress and Job satisfaction of private security are more keyword than institutional factors and policy factors such as Security Services Industry Act and training for Private Security guards. It means that research trend of private security are to study Individual factors rather than institutional factors and policy factors. But, this study is a limit as follows; First, An object of study is only to searching article in National Assembly Liberary. A follow-up studies are need to expand the range of an object of study for private security.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.712-718
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• 2021

Virtual communities are studied to analyze their characteristic features, types, and tole to modern society. The article is aimed at creating a classification of virtual communities according to specific characteristics, which can be used to model the interaction, and necessity of components that are important for the community. The classification of virtual communities will contribute to their better performance and satisfy the users' needs in information. The study reveals the value structure of virtual communities, educational and communicative influence, and the possible threats these communities may bring to society and security.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.1-14
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• 2015

To conform to new emerging computing paradigm, various researches and challenges are being done. New information technologies make easy to access and acquire information in various ways. In other side, however, it also makes illegal access more powerful and various threat to system security. In this paper, we suggest a new extended access control method that make it possible to conform to security policies enforcement even with discrepancy between policy based constraints rules and query based constraints rules, based on their semantic information. New method is to derive security policy rules using context tree structure and to control the exceed granting of privileges through the degree of the semantic discrepancy. In addition, we illustrate prototype system architecture and make performance comparison with existing access control methods.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.317-322
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• 2021

The modern technological era has brought about the Semantic Web. Ontologies are essential to achieve the vision of the Semantic Web. Ontologies enable machines to understand data. The Arabic Language currently does not have a significant presence on the Web. To achieve a comparable level of Arabic access to other important languages, further work is needed to build Arabic ontologies. A goal is to design and create a robust Arabic ontology that represents the concepts from a large and significant subset of Arabic. We use a source of Hadiths (prophet saying and deeds) from Riyadh As-Saliheen. Preliminary results are very promising.