• Korean Security Journal
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• no.41
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• pp.153-183
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• 2014

Nowadays, proactive intelligence activities are required because of enhanced nation wide threats of terrorism and complexity of multidimensional factors of national security. South Korea not only need to draw up plans of information sharing among agencies for more effective national intelligence activities, but also have to evaluate the structure of Domestic Intelligence Agency and its right direction of activities. In this vein, this paper conducts comparative studies of structures and range of activities of intelligence Agencies by reviewing U.K, U.S.A, and France cases and suggests a potential model of 'domestic information specified agency' that we can adopt and methods to share information among agencies. The focus of this paper is on the reviewing of necessity of establishing new 'domestic information specified agency' which will mainly conduct anti-terrorism and counterintelligence activities, and its appropriate form. After reviewing the cases of U.K, U.S.A. and France, we conclude that overcoming the people's distrust about an invasion of freedom and rights caused by centralized and integrated independent intelligence agency is a prerequisite. Disputable issues of FBI, DHS, and South Korea's intelligence agency cases suggest that plans for restoring trust have to be considered if a new 'domestic information specified agency' is established in NIS. If it is established under government ministries such as MSPA focusing on implementing anti-terrorism and counterintelligence activities, organizations such as NCTC, NIC, that can carry out information sharing and cooperating with agencies concerned have to be established. Additionally, measures to solve structural problems caused by carrying out law enforcement functions by domestic information specified agency should be considered.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.865-889
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• 2019

The need for cyber resilience is increasingly important in our technology-dependent society where computing devices and data have been, and will continue to be, the target of cyber-attackers, particularly advanced persistent threat (APT) and nation-state/sponsored actors. APT and nation-state/sponsored actors tend to be more sophisticated, having access to significantly more resources and time to facilitate their attacks, which in most cases are not financially driven (unlike typical cyber-criminals). For example, such threat actors often utilize a broad range of attack vectors, cyber and/or physical, and constantly evolve their attack tactics. Thus, having up-to-date and detailed information of APT's tactics, techniques, and procedures (TTPs) facilitates the design of effective defense strategies as the focus of this paper. Specifically, we posit the importance of taxonomies in categorizing cyber-attacks. Note, however, that existing information about APT attack campaigns is fragmented across practitioner, government (including intelligence/classified), and academic publications, and existing taxonomies generally have a narrow scope (e.g., to a limited number of APT campaigns). Therefore, in this paper, we leverage the Cyber Kill Chain (CKC) model to "decompose" any complex attack and identify the relevant characteristics of such attacks. We then comprehensively analyze more than 40 APT campaigns disclosed before 2018 to build our taxonomy. Such taxonomy can facilitate incident response and cyber threat hunting by aiding in understanding of the potential attacks to organizations as well as which attacks may surface. In addition, the taxonomy can allow national security and intelligence agencies and businesses to share their analysis of ongoing, sensitive APT campaigns without the need to disclose detailed information about the campaigns. It can also notify future security policies and mitigation strategy formulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.691-708
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• 2014

This paper formalizes a special type of social networking knowledge, which is called "workflow performer-role affiliation networking knowledge." A workflow model specifies execution sequences of the associated activities and their affiliated relationships with roles, performers, invoked-applications, and relevant data. In Particular, these affiliated relationships exhibit a stream of organizational work-sharing knowledge and utilize business process intelligence to explore resources allotting and planning knowledge concealed in the corresponding workflow model. In this paper, we particularly focus on the performer-role affiliation relationships and their implications as organizational and business process intelligence in workflow-driven organizations. We elaborate a series of theoretical formalisms and practical implementation for modeling, discovering, and visualizing workflow performer-role affiliation networking knowledge, and practical details as workflow performer-role affiliation knowledge representation, discovery, and visualization techniques. These theoretical concepts and practical algorithms are based upon information control net methodology for formally describing workflow models, and the affiliated knowledge eventually represents the various degrees of involvements and participations between a group of performers and a group of roles in a corresponding workflow model. Finally, we summarily describe the implications of the proposed affiliation networking knowledge as business process intelligence, and how worthwhile it is in discovering and visualizing the knowledge in workflow-driven organizations and enterprises that produce massively parallel interactions and large-scaled operational data collections through deploying and enacting massively parallel and large-scale workflow models.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.209-214
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• 2024

This is an extended research paper focusing on the applications of Machine Learing and Artificial Intelligence in virtual learning environment. The world is moving at a fast pace having the application of Machine Learning (ML) and Artificial Intelligence (AI) in all the major disciplines and the educational sector is also not untouched by its impact especially in an online learning environment. This paper attempts to elaborate on the benefits of ML and AI in E-Learning (EL) in general and explain how King Khalid University (KKU) EL Deanship is making the best of ML and AI in its practices. Also, researchers have focused on the future of ML and AI in any academic program. This research is descriptive in nature; results are based on qualitative analysis done through tools and techniques of EL applied in KKU as an example but the same modus operandi can be implemented by any institution in its EL platform. KKU is using Learning Management Services (LMS) for providing online learning practices and Blackboard (BB) for sharing online learning resources, therefore these tools are considered by the researchers for explaining the results of ML and AI.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.19-38
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• 2014

This study focused on the role of active knowledge seeking (knowledge browsing and knowledge searching) in the context of virtual community of interest. Knowledge seeking is rarely studied as an antecedent in knowledge management (KM) research. Active knowledge seeking is considered as antecedents of sense of virtual community which mediates to knowledge sharing intention and virtual community promotion. Research hypotheses are tested by applying structure equation modeling with survey data from virtual community members in South Korea. Active knowledge seeking behavior was found to be the strong predictor of sense of virtual community, which, in turn, positively affects knowledge sharing intention and virtual community promotion. Implication to practitioners is to understand and accommodate the members' knowledge seeking efforts, who are potential contributors and promoters of the virtual community. Knowledge seeking, knowledge sharing and promoting virtual community are more of human activities than technology and this study extends the understanding of such human activities. By providing a mechanism of how knowledge seeking and sharing could work harmoniously, a virtuous circle with win-win situation could be achieved in virtual communities.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.163-175
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• 2018

The age of the $4^{th}$ Industrial revolution characterized with artificial intelligence leads to increased interest in emotional aspects representing humanity as counterpart competence to the digital literacy, As the educational model to foster emotional intelligence, noticed is 'maker education based on design thinking process,' since it cultivates the spirits of empathy, intuitive thinking, collaboration, communication, sharing, and openness. In this context, this study aimed to examine relationship between the educational model and emotional intelligence. For this purpose, a case study has been conducted with 37 undergraduate students in an University general education class, and the results of data collection and analysis confirmed positive influences of the program in enhancing most components of the emotional intelligence.

• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.23-32
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• 2011

The Internet is appearing a new paradigm called Web 2.0 which 'Participation', 'Sharing', 'Openness', 'Cooperation'. Web 2.0 is expanded by experts and general users and many people's ideas can solve more problems than an expert's idea. The collective intelligence is techniques that express the valuable of Web 2.0. For this reason, the collective intelligence has attracted attention because of its potential as an educational tool. The purpose of this study is to develop a PBL-based programming instruction model using collective intelligence to improve students' problem solving abilities and programming attitudes and verified its effectiveness. As a result, the developed instruction model showed significant differences in the students' problem solving abilities and programming attitudes. According to these results, these have been proved that a PBL-based programming instruction model using collective intelligence has an influence to the students' problem solving abilities and programming attitudes.

• Korean Journal of Childcare and Education
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• v.10 no.5
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• pp.229-248
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• 2014

The purpose of this study is to draw guidelines on how to select traditional games that would efficiently help and develop multiple intelligences in children. Guidelines standard of section inquiries were prepared through a Delphi survey targeting twenty experts in early childhood education and traditional games. As a result, linguistic intelligence questions regarding writing, listening, speaking and vocabulary acquisition were selected. logical-mathematical intelligence questions regarding strategy, counting, patterns, hypothesis, verification, and comparing, contrasting, calculating ability were selected. Spatial intelligence questions regarding drawing, coloring, representation activities, operating and creating were selected, physical performance intelligence questions regarding global muscles, eye-hand coordination, flexibility, accommodation force, balance, agility and muscular strength were selected. Musical intelligence included questions about singing, and playing musical instruments. Interpersonal intelligence included perspective-taking, role-sharing, cooperation and discussion. For intrapersonal intelligence questions regarding personal significance-ties, planning-decision making, emotional expression and problem solving were selected. Finally, in relation to naturalist intelligence, questions regarding living organisms, inanimate objects and seasons were selected. In addition, traditional games were analyzed based on the finalized guidelines, and the results showed that each of the traditional games would not only work with one intelligence at a time but with other different intelligence as well. In the light of that, the study confirmed the validity of the guidelines on how to select traditional games that would develop multiple intelligences in children.

• Asia pacific journal of information systems
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• v.14 no.4
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• pp.49-70
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• 2004

Multi-agent technology is being regarded as one of the promising technologies for today's supply chain management because of its desirable features such as autonomy, intelligence, and collaboration. This paper suggests a multi-agent system architecture with which companies can improve the efficiency of their supply chains by collaborative operation. Reflecting the practical difficulties of collaboration in complex supply chains, the architecture allows agent systems to share information with only neighboring companies for the coordinated operation. The suggested architecture is elaborated with a collaboration model based on Petri-net, conversation models for communication, and internal behavior models of each agent. A simulation experiment was performed for the evaluation of the suggested architecture. The result implies that when the estimation of market demand is higher than a certain level, the suggested architecture can be beneficial.