• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.389-403
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• 2011

The objective of this study is to find out how strategic human resource management(SHRM) of a facility security firm affects its organizational culture and behaviors of its members. This study was executed in June 2010 with facility security officers(FSO) in four private security firms by using a judgment sampling technique. A total of 343 FSOs were used in final analysis. Coefficient of reliability(Cronbach's coefficient alpha) of the survey was 0.691. The conclusion was as follows: First, SHRM of facility security firms exert its influence on organizational culture. That is, promotion of education/training, compensation, making avid followers, and career development may facilitate settlement of hierarchical, development-oriented, agreement -based and rationality-oriented culture. Second, SHRM of security firms would affect organizational citizenship behaviors(OCB), i.e., the promotion of education/training, compensation, making avid followers, and career development would tend to enhance consideration for others and altruistic, participatory, conscientious and gentlemanly behaviors. On the other hand, if proper compensation is not made, above-mentioned behaviors would decrease. Third, organizational culture of security firms tends to affect OCB. That is, when hierarchical, development-oriented, agreement-based and rationality-oriented culture is settled, consideration for others, altruistic, participatory, conscientious and gentlemanly behaviors tends to be enhanced.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.65-73
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• 2014

An overall responding security-centered framework is necessary required for infringement accidents, failures, and cyber threats. On the other hand, the correspondence structures of existing administrative, technical, physical security have weakness in a system responding to complex attacks because each step is performed independently. This study will recognize all internal and external users as a potentially threatening element. To perform connectivity analysis regarding an action, an intelligent convergence security framework and road map is suggested. A suggested convergence security framework was constructed to be independent of an automatic framework, such as the conventional single solution for the priority defense system of APT of the latest attack type, which makes continuous reputational attacks to achieve its goals. This study suggested the next generation convergence security framework to have preemptive responses, possibly against an APT attack, consisting of the following five hierarchical layers: domain security, domain connection, action visibility, action control, and convergence correspondence. In the domain, the connection layer suggests a security instruction and direction in the domains of administrative, physical and technical security. The domain security layer has consistency of status information among the security domain. A visibility layer of an intelligent attack action consists of data gathering, comparison and decision cycle. The action control layer is a layer that controls the visibility action. Finally, the convergence corresponding layer suggests a corresponding system of before and after an APT attack. The administrative security domain had a security design based on organization, rule, process, and paper information. The physical security domain is designed to separate into a control layer and facility according to the threats of the control impossible and control possible. Each domain action executes visible and control steps, and is designed to have flexibility regarding security environmental changes. In this study, the framework to address an APT attack and load map will be used as an infrastructure corresponding to the next generation security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2550-2572
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• 2023

Epidemiological survey is an important means for the prevention and control of infectious diseases. Due to the particularity of the epidemic survey, 1) epidemiological survey in epidemic prevention and control has a wide range of people involved, a large number of data collected, strong requirements for information disclosure and high timeliness of data processing; 2) the epidemiological survey data need to be disclosed at different institutions and the use of data has different permission requirements. As a result, it easily causes personal privacy disclosure. Therefore, traditional access control technologies are unsuitable for the privacy protection of epidemiological survey data. In view of these situations, we propose a black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. Firstly, a black box-assisted multi-attribute authority management mechanism without a trusted center is established to avoid authority deception. Meanwhile, the establishment of a master key-free system not only reduces the storage load but also prevents the risk of master key disclosure. Secondly, a sensitivity classification method is proposed according to the confidentiality degree of the institution to which the data belong and the importance of the data properties to set fine-grained access permission. Thirdly, a hierarchical authorization algorithm combined with data sensitivity and hierarchical attribute-based encryption (ABE) technology is proposed to achieve hierarchical access control of epidemiological survey data. Efficiency analysis and experiments show that the scheme meets the security requirements of privacy protection and key management in epidemiological survey.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.165-170
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• 2014

In this paper, a hierarchical authentication protocol is proposed to minimize authentication delay in proxy mobile IPv6 networks. The authentication function of the AAA server is distributed to the LMAs and the MAGs. If the LMAs or the MAGs have authentication information of the MNs, they authenticate the MN on behalf of the AAA servers. Therefore, the authentication delay is reduced. The AAA server is vulnerable to denial-of-service attack. If the AAA server is down, MNs cannot access the proxy mobile IPv6 network until they are authenticated. The proposed scheme reduces the load on the AAA server by distributing the authentication function to the LMAs and the MAGs.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.120-128
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• 2023

In this work, we have presented ATSA, a hierarchical attention deep learning model for Arabic sentiment analysis. ATSA was proposed by addressing several challenges and limitations that arise when applying the classical models to perform opinion mining in Arabic. Arabic-specific challenges including the morphological complexity and language sparsity were addressed by modeling semantic composition at the Arabic morphological analysis after performing tokenization. ATSA proposed to perform phrase-chunks sentiment embedding to provide a broader set of features that cover syntactic, semantic, and sentiment information. We used phrase structure parser to generate syntactic parse trees that are used as a reference for ATSA. This allowed modeling semantic and sentiment composition following the natural order in which words and phrase-chunks are combined in a sentence. The proposed model was evaluated on three Arabic corpora that correspond to different genres (newswire, online comments, and tweets) and different writing styles (MSA and dialectal Arabic). Experiments showed that each of the proposed contributions in ATSA was able to achieve significant improvement. The combination of all contributions, which makes up for the complete ATSA model, was able to improve the classification accuracy by 3% and 2% on Tweets and Hotel reviews datasets, respectively, compared to the existing models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1657-1673
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• 2023

With the advancement of information technology, criminals employ multiple cyberspaces to promote cybercrime. To combat cybercrime and cyber dangers, banks and financial institutions use artificial intelligence (AI). AI technologies assist the banking sector to develop and grow in many ways. Transparency and explanation of AI's ability are required to preserve trust. Deep learning protects client behavior and interest data. Deep learning techniques may anticipate cyber-attack behavior, allowing for secure banking transactions. This proposed approach is based on a user-centric design that safeguards people's private data over banking. Here, initially, the attack data can be generated over banking transactions. Routing is done for the configuration of the nodes. Then, the obtained data can be preprocessed for removing the errors. Followed by hierarchical network feature extraction can be used to identify the abnormal features related to the attack. Finally, the user data can be protected and the malicious attack in the transmission route can be identified by using the Wrapper stepwise ResNet classifier. The proposed work outperforms other techniques in terms of attack detection and accuracy, and the findings are depicted in the graphical format by employing the Python tool.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.119-127
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• 2013

The merits of Smartphone are portability, convenience and especially a lot of information can be stored in the device. Especially in Smartphone, users can install programs that cannot install to normal cell phone and users can use many different services through these Smartphone programs. Also Smartphone can connect to Internet through network, so it can access information anytime, anywhere easily. Security of personal information and variety of information which stored in Smartphone are in risk. In Chapter 2 of thesis, it will discuss the definition and features of the Smartphone and market trends. In Chapter 3 of thesis, it will discuss security vulnerabilities of Smartphone and it will analyze and research security vulnerabilities of Smartphone in Chapter 4. In conclusion, it will check users' identification twice in useful application especially application that relate to finance and mobile payment. By checking users' identification several times, it will help to defend from security threats. Users can use Smartphone safely and convenience by know how to prevent from mobile hacking for personal and private information. the quality of APIs matching by the clustering and hierarchical relationships mechanism.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.2021-2024
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• 2003

Information security is becoming a more important factor in distribution of digital contents. Generally, illegal facsimile of high-quality multimedia products such as DVDs, MP3s and AACs is possible without damaging quality. Thus, the illegal distribution of duplicated contents on the Web is causing digital content providers great economic loss. Therefore, a study of security and efficient distribution of digital contents is required. The most important issues in the design of a digital content distribution system are user convenience, execution speed and security. In this study, we designed a digital contents distribution system that uses web caching technology and encryption/decryption techniques in hierarchical structures. We propose a digital content distribution system that improves user convenience, security and execution speed. The superior performance of the proposed system has been proven in the tests. The results of experiment show that the developed system has improved the security of DC without decreasing process speed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.133-140
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• 2011

Recently, Web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hash techniques are used for the image registration, management and retrieval as the identifier and many researches have been performed to raise the hash performance. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which based on histogram bin population method. So far, many researches have proven that image hashing techniques based on histogram are robust image processing and geometrical attack. We modified existing image hashing method developed by our research team. The main idea is that it makes more fluent hash string if we have histogram bin of specific length as shown in the body of paper. Finally, we can raise the magnitude of hash string within same context or feature and strengthen the robustness of hash.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.281-291
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• 2021

The Islamic jurisprudential legal system represents an essential component of the Islamic religion, that governs many aspects of Muslims' daily lives. This creates many questions that require interpretations by qualified specialists, or Muftis according to the main sources of legislation in Islam. The Islamic jurisprudence is usually classified into branches, according to which the questions can be categorized and classified. Such categorization has many applications in automated question-answering systems, and in manual systems in routing the questions to a specialized Mufti to answer specific topics. In this work we tackle the problem of automatic categorisation of Islamic jurisprudential legal questions using deep learning techniques. In this paper, we build a hierarchical deep learning model that first extracts the question text features at two levels: word and sentence representation, followed by a text classifier that acts upon the question representation. To evaluate our model, we build and release the largest publicly available dataset of Islamic questions and answers, along with their topics, for 52 topic categories. We evaluate different state-of-the art deep learning models, both for word and sentence embeddings, comparing recurrent and transformer-based techniques, and performing extensive ablation studies to show the effect of each model choice. Our hierarchical model is based on pre-trained models, taking advantage of the recent advancement of transfer learning techniques, focused on Arabic language.