• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1643-1660
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• 2016

Connectivity and trust in social networks have been exploited to propose applications on top of these networks, including routing, Sybil defenses, and anonymous communication systems. In these networks, and for such applications, connectivity ensures good performance of applications while trust is assumed to always hold, so as collaboration and good behavior are always guaranteed. In this paper, we study the impact of differential behavior of users on performance in typical social network-enabled routing applications. We classify users into either collaborative or rational (probabilistically collaborative) and study the impact of this classification and the associated behavior of users on the performance of such applications, including random walk-based routing, shortest path based routing, breadth-first-search based routing, and Dijkstra routing. By experimenting with real-world social network traces, we make several interesting observations. First, we show that some of the existing social graphs have high routing costs, demonstrating poor structure that prevents their use in such applications. Second, we study the factors that make probabilistically collaborative nodes important for the performance of the routing protocol within the entire network and demonstrate that the importance of these nodes stems from their topological features rather than their percentage of all the nodes within the network.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.83-95
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• 2019

It is becoming more and more difficult to cope with new knowledge and technology required by society by the efforts of one person or organization according to the development of science and technology. As a method to overcome this, collaborative research is becoming important. This tendency is increasing in the government R&D projects as well, and the 'A' test research institute, which is the subject of this paper, is also increasing a collaborative research. The purpose of this study is to analyze the network characteristics among the participating researchers in the government R&D project conducted by the institution A, and to ascertain how the network characters of the researchers actually affect the financial performance of the team. The results of the analysis show that 'closeness centrality' and 'degree of centrality' contribute positively to the financial performance of the team. On the other hand, 'betweenness centrality' and 'eigenvector centrality' have a negative effect on the financial performance of the team because they are not directly related to financial performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1330-1347
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• 2018

Mobile Ad hoc Network (MANET) is a collection of nodes or communication devices that wish to communicate without any fixed infrastructure and predetermined organization of available links. The effort has been made by proposing a scheme to overcome the critical security issue in MANET. The insufficiency of security considerations in the design of Ad hoc On-Demand Distance Vector protocol makes it vulnerable to the threats of collaborative black hole attacks, where hacker nodes attack the data packets and drop them instead of forwarding. To secure mobile ad hoc networks from collaborative black hole attacks, we implement our scheme and considered sensor's energy as a key feature with a better packet delivery ratio, less delay time and high throughput. The proposed scheme has offered an improved solution to diminish collaborative black hole attacks with high performance and benchmark results as compared to the existing schemes EDRIAODV and DRIAODV respectively. This paper has shown that throughput and packet delivery ratio increase while the end to end delay decreases as compared to existing schemes. It also reduces the overall energy consumption and network traffic by maintaining accuracy and high detection rate which is more safe and reliable for future work.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.1-21
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• 2015

This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.

• Educational Technology International
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• v.16 no.1
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• pp.1-30
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• 2015

The purpose of this research is to propose a novel social LMS developed for group collaborative learning with a think-aloud tool integrated for sharing cognitive processes in order to improve group collaborative learning performance. In this developmental research, the system was designed with three critical elements: the think-aloud element supports learners through shared cognition, the social network element improves the quality of collaborative learning by forming a structured social environment, and the learning management element provides a understructure for collaborative learning for student groups. Moreover, the three critical elements were combined in an educational context and applied in three directions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.135-141
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• 2016

Recently, the needs for the development and application of marine robots are increasing as marine accidents occur frequently. However, it is very difficult to acquire the information by utilizing marine robots in the marine environment. Therefore, the needs for the researches of sensor networks which are composed of underwater, surface and aerial robots are increasing in order to acquire the information effectively as the information from heterogeneous robots has less limitation in terms of coverage and connectivity. Although various researches of the sensor network which is based on marine robots have been executed, all of the underwater, surface and aerial robots have not yet been considered in the sensor network. To solve this problem, a collaborative control method based on the acoustic information and image by the sonars of the underwater robot, the acoustic information by the sonar of the surface robot and the optical image by the camera of the static-floating aerial robot is proposed. To verify the performance of the proposed method, the collaborative control of a MUR(Micro Underwater Robot) with an OAS(Obstacle Avoidance Sonar) and a SSS(Side Scan Sonar), a MSR(Micro Surface Robot) with an OAS and a BMAR(Balloon-based Micro Aerial Robot) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.56-78
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• 2018

Security issue in mobile ad hoc network (MANET) is a promising research. In 2011, we had accomplished a survey of black hole attacks in MANETs. However network technology is changing with each passing day, a vast number of novel schemes and papers have been proposed and published in recent years. In this paper, we survey the literature on malicious attacks in MANETs published during past 5 years, especially the black hole attack. Black hole attacks are classified into non-cooperative and collaborative black hole attacks. Except black hole attacks, other attacks in MANET are also studied, e.g., wormhole and flooding attacks. In addition, we conceive the open issues and future trends of black hole detection and prevention in MANETs based on the survey results of this paper. We summarize these detection schemes with three systematic comparison tables of non-cooperative black hole, collaborative black hole and other attacks, respectively, for a comprehensive survey of attacks in MANETs.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.427-449
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• 2015

Network governance can be defined as collaborative process to develop a new socio-political order through civil society centered networking with government and market, and the term 'collaborative governance' can be used in a sense that the basis of governance is collaborative process. In particular, it can be stressed that collaborative governance between regions need double collaborative processes, that is, collaboration between local governments and collaboration between local government and local civil society within a region. Yet, the collaboration as a core element of collaborative governance should not be seen as a pure normativity presupposing confidence and reciprocity, but as a strategy based on competition and antagonism. The normativity implied in the concept of collaborative governance may not realized in actual process, and tends to be mobilized as a rationale for justifying neoliberal strategies. In order to overcome such limits of collaborative governance, the concept of collaborative governance should be reconstructed. This paper suggests that collaborative governance can be seen as hegemonic governing process in a Gramcian sense operating in the government plus civil society, and that, radicalizing Ostrom's concept, it also can be seen as a governing process producing polycentricity by self-regulating subjects. Finally, collaborative governance between regions needs expansion of material basis for economic complementarity and construction of infrastructure as well as a discursive process in order to enhance connectivity between them.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.375-390
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• 2024

Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

• Korean Institute of Interior Design Journal
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• v.21 no.5
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• pp.200-207
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• 2012

This paper is analyzed the successful fundamentals of collaborative design management strategy from case of corporates such as, Louis Vuitton, H&M, MINI, Black Berry, Chanel, and Prada. Collaborative design management contributes creating cultural life and concurrently achieving corporate purpose through new vision and value creations which is a combination of rationality and originality as interacting design area and management area.In addition, collaborative design management has been emerged in order to create new business model in the rapidly changing modern society. It should be horizontal intercourse in order to increase social value and positive effects of each others to collaborative design management and play an important role in the new partner to build an effective business model. These case studies established the successful design strategy which is well structuring the systematic design network and efficiently managing the brand image from analyzing the user's needs and their life styles as an element of collaborative design management. This research is presented the mean of collaborative design management as a managing element to build a successful business model and proposed an appropriate application plan through the case studies.