• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.27-34
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• 2014

Todays, the rapid technical progress of smart device has been used for various social (wall-fare) services in our lives. Especially, most of these services are based on the Local-based Services (LBS) and this technology is getting popular more and more compared with before. Basically, LBS is able to support various types of geographical services such as vehicles' navigation services, Augmented reality services as using extensional local information such as GPS. However, LBS has serious mathematical vulnerability on the services frequently because of its miscalculated GPS data under interior and ambiguous geographical environment such like shadowed area. So, to overcome this limitation, iBeacon, which would be able to mitigate LBS miscalculation process, has been proposed recently among network experts. Compared with other wireless technologies, iBeacon is able to determine the accurate geographical data of certain local positions easily because it is not only designed based on low-powered data transmitting technology, but also, it can be much easy to be deployed. As users' dependency of smart devices are getting higher and higher and the use of smart device is also getting complex more and more, the users prefer to use various types of smart devices at one time. Therefore, in this paper, we propose the loss prevention system that is able to interwork smart devices networks as using iBeacon technology for users' better conveniences.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.107-115
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• 2014

Recently, increased use of the internet resulted in generation of large and diverse types of data due to increased use of social media, expansion of a convergence of among industries, use of the various smart device. We are facing difficulties to manage and analyze the data using previous data processing techniques since the volume of the data is huge, form of the data varies and evolves rapidly. In other words, we need to study a new approach to solve such problems. Many approaches are being studied on this issue, and we are describing an effective design and development to build indexing engine of big data platform. Our goal is to build a system that could effectively manage for huge data set which exceeds previous data processing range, and that could reduce data analysis time. We used large SNMP log data for an experiment, and tried to reduce data analysis time through the fast indexing and searching approach. Also, we expect our approach could help analyzing the user data through visualization of the analyzed data expression.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.63-72
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• 2013

Business Process Intelligence (BPI) is one of the emerging technologies in the knowledge discovery and analysis area. BPI deals with a series of techniques from discovering knowledge to analyzing the discovered knowledge in BPM-supported organizations. By means of the BPI technology, we are able to provide the full functionality of control, monitoring, prediction, and optimization of process-supported organizational knowledge. Particularly, we focus on the focal organizational knowledge, which is so-called the BPM activity-performer affiliation networking knowledge that represents the affiliated relationships between performers and activities in enacting a specific business process model. That is, in this paper we devise a statistical analysis method to be applied to the BPM activity-performer affiliation networking knowledge, and dubbed it the activity-performer correspondence analysis method. The devised method consists of a series of pipelined phases from the generation of a bipartite matrix to the visualization of the analysis result, and through the method we are eventually able to analyze the degree of correspondences between a group of performers and a group of activities involved in a business process model or a package of business process models. Conclusively, we strongly expect the effectiveness and efficiency of the human resources allotments, and the improvement of the correlational degree between business activities and performers, in planning and designing business process models and packages for the BPM-supported organization, through the activity-performer correspondence analysis method.

• Journal of Science and Technology Studies
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• v.18 no.2
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• pp.7-41
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• 2018

The projects of citizen science which is originated from citizen data collecting action driven by governmental institutes and science associations have been implemented with different form of collaboration with scientists. The themes of citizen science has extended from the ecology to astronomy, distributed computing, and particle physics. Citizen science could contribute to the advancement of science through cost-effective science research based on citizen volunteer data collecting. In addition, citizen science enhance the public understanding of science by increasing knowledge of citizen participants. The community-led citizen science projects could raise public awareness of environmental problems and promote the participation in environmental problem-solving. Citizen science projects based on local tacit knowledge can be of benefit to the local environmental policy decision making and implementation of policy. These social values of citizen science make many countries develop promoting policies of citizen science. The korean government also has introduced some citizen science projects. However there are some obstacles, such as low participation of citizen and scientists in projects which the government has to overcome in order to promote citizen science. It is important that scientists could recognize values of citizen science through the successful government driven citizen science projects and the evaluation tool of scientific career could be modified in order to promote scientist's participation. The project management should be well planned to intensify citizen participation. The government should prepare open data policy which could support a data reliability of the community-led monitoring projects. It is also desirable that a citizen science network could be made with the purpose of sharing best practices of citizen science.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.629-635
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• 2019

In Deep Learning models derivative is implemented by error back-propagation which enables the model to learn the error and update parameters. It can find the global (or local) optimal points of parameters even in the complex models taking advantage of a huge improvement in computing power. However, deliberately generated data points can 'fool' models and degrade the performance such as prediction accuracy. Not only these adversarial examples reduce the performance but also these examples are not easily detectable with human's eyes. In this work, we propose the method to detect adversarial datasets with random noise addition. We exploit the fact that when random noise is added, prediction accuracy of non-adversarial dataset remains almost unchanged, but that of adversarial dataset changes. We set attack methods (FGSM, Saliency Map) and noise level (0-19 with max pixel value 255) as independent variables and difference of prediction accuracy when noise was added as dependent variable in a simulation experiment. We have succeeded in extracting the threshold that separates non-adversarial and adversarial dataset. We detected the adversarial dataset using this threshold.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.708-710
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• 2013

Web based simulation service is utilized to computationally analyze various phenomena in real world according to the progress of network and computing technology. To provide suitable simulation service, web based simulation service will be improved by analyzing execution data. Especially, an API for data retrieval is designed, because every analyst needs different data. In this paper, we design the retrieval API for a user to analyze the web based simulation execution data, which is used on CFD (Cumputational Fluid Dynamics) and Chemistry. The designed retrieval API provides an simulation execution data depending on an user requirement such as a user type, an execution period, and an affiliation, which is based on the core information such as an user, a simulation program, and a cyberlab. Besides, a developer can provides a suitable information for a user to execute a simulation well such as a simulation statistics, an execution trend, and a frequent error.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.481-492
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• 2011

Recently, various mobile services are provided by the spread of wireless network infrastructures and smart devices. The improvement of cloud computing technologies increases the interests for enterprise mobile cloud services in various IT companies as well. By increasing the interests for enterprise mobile cloud services, it is necessary to evaluate the use of enterprise mobile cloud services. Therefore, the factors which affect the user acceptance of enterprise mobile cloud services are analyzed on the basis of Davis' technology acceptance model in this research. As analysis results, four external variables have significant effects on perceived ease of use of mobile cloud services. Also, these variables indirectly affect attitude toward using cloud services. The results show that the security is the most important factor for attitude toward using enterprise mobile cloud services. The service users also consider the interoperability as an important factor for the user acceptance of cloud services. The perceived ease of use has more contribution than the perceive usefulness on attitude toward using enterprise mobile cloud services. This research has both industrial and academic contributions because it provides the guideline to companies for introducing the enterprise mobile cloud services and apply the technology acceptance model on new IT services.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.459-468
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• 2008

A data stream which is a massive unbounded sequence of data elements continuously generated at a rapid rate. Many recent research activities for emerging applications often need to deal with the data stream. Such applications can be web click monitoring, sensor data processing, network traffic analysis. telephone records and multi-media data. For this. data processing over a data stream are not performed on the stored data but performed the newly updated data with pre-registered queries, and then return a result immediately or periodically. Recently, many studies are focused on dealing with a data stream more than a stored data set. Especially. there are many researches to optimize continuous queries in order to perform them efficiently. This paper proposes a query optimization algorithm to manage continuous query which has multiple join operators(Multi-way join) over data streams. It is called by an Extended Greedy query optimization based on a greedy algorithm. It defines a join cost by a required operation to compute a join and an operation to process a result and then stores all information for computing join cost and join cost in the statistics catalog. To overcome a weak point of greedy algorithm which has poor performance, the algorithm selects the set of operators with a small lay, instead of operator with the smallest cost. The set is influenced the accuracy and execution time of the algorithm and can be controlled adaptively by two user-defined values. Experiment results illustrate the performance of the EGA algorithm in various stream environments.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.47-61
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• 2011

Recently, the importance of digital forensic has been magnified because of the dramatic increase of cyber crimes and the increasing complexity of the investigation of target systems such as PCs, servers, and database systems. Moreover, some systems have to be investigated with live forensic techniques. However, even though live forensic techniques have been improved, they are still vulnerable to anti-forensic activities when the target systems are remotely accessible by criminals or their accomplices. To solve this problem, we first suggest a layer-based model and the anti-forensic scenarios which can actually be applicable to each layer. Our suggested model, the Anti-Forensic Activites layer-based model, has 5 layers - the physical layer, network layer, OS layer, database application layer and data layer. Each layer has possible anti-forensic scenarios with detailed commands. Second, we propose a fuzzy expert system for effectively detecting anti-forensic activities. Some anti-forensic activities are hardly distinguished from normal activities. So, we use fuzzy logic for handling ambiguous data. We make rule sets with extracted commands and their arguments from pre-defined scenarios and the fuzzy expert system learns the rule sets. With this system, we can detect anti-forensic activities in real time when performing live forensic.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.21-28
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• 2011

Recently medical and entertainment applications using conducting textile are suggested, but the data of conducting threads are not characterized, classified and verified. Only the data sheet published by manufacturing companies is available. Thus we need to verify the performances of the threading threads in communication. And we need a guideline if the existing communication protocols can be used for the conducting threads communication or the new specific communication protocols have to be developed for the communication. This paper classifies the characteristics of conducting threads made by domestic and overseas companies. Based on the criteria we classified conducting threads into three classes: class A, class B and class C. Further we carried out experiments to verify the adaptability of existing simple serial communication protocols such as RS232. Six different conducting threads are used in experiments and the length of each thread was 0.5m, 1m, 2m and 3m. The data transmission rate and error rate are collected and analyzed. RS485 is very prone to error due to static electricity from human and environment. So it may not be appropriate as long-distance communication protocol up to 12km which is possible in theory. RS232 shows stable and error-less data transmission ability even though every conducting thread didn’t show transmission capability over RS232. USB protocol shows high data rate transmission but the distance cannot be exceeded over 2m. Additionally, USB requires stable power supply. But if the power is supplied through conducting thread, its function is not.