• Journal of Advanced Marine Engineering and Technology
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• v.39 no.4
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• pp.483-488
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• 2015

This paper implements a long-term monitoring system (LMS) for ship's engine performance analysis (SEPA) based on the web, for the purpose of the communication speed and engine maintenance. This system is composed of a simulator, monitoring module with a multi channel A/D converter, monitoring computer, network attached storage (NAS), RS485 serial and wireless internet communication system. The existing products monitor the information transmitted from pressure sensors installed in the upper parts of each of engines in the local or web computer, but have a delay in the communication speed and errors in long-term monitoring due to the large volume of sampling pressure data. To improve these problems, the monitoring computer saves the sampling pressure data received from the pressure sensors in NAS, monitors the long-term sampling data generated by the sectional down sampling method on a local computer, and transmits them to the web for long-term monitoring. Because this method has one tenth of the original sampling data, it will use memory with small capacity, save communication cost, monitor the long-term sampling data for 30 days, and as a result, make a great contribution to engine maintenance.

• Smart Media Journal
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• v.4 no.4
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• pp.24-32
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• 2015

Recently, SDN is actively used as datacenter networks and gradually increase its applied areas. Along with this change of networking environment, research of deploying network security systems on SDN becomes highlighted. Especially, systems for detecting network flooding attacks by monitoring every packets through ports of OpenFlow switches have been proposed. However, because of the centralized management of a SDN controller which manage multiple switches, it may be substantial overhead that the attack detection system continuously monitors all the flows. In this paper, a sampling based network flooding attack detection and prevention system is proposed to reduce the overhead of monitoring packets and to achieve reasonable functionality of attack detection and prevention. The proposed system periodically takes sample packets of network flows with the given sampling conditions, analyzes the sampled packets to detect network flooding attacks, and block the attack flows actively by managing the flow entries in OpenFlow switches. As network traffic sampler, sFlow agent is used, and snort, an opensource IDS, is used to detect network flooding attack from the sampled packets. For active prevention of the detected attacks, an OpenDaylight application is developed and applied. The proposed system is evaluated on the local testbed composed with multiple OVSes (Open Virtual Switch), and the performance and overhead of the proposed system under various sampling condition is analyzed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.227-230
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• 2002

The Loose Part Monitoring System(LPMS) has been designed to detect, locate and evaluate detached or loosened parts and foreign objects in the reactor coolant system. In this paper, at first, we presents an application of the back propagation neural network. At the preprocessing step, the moving window average filter is adopted to reject the low frequency background noise components. And then, extracting the acoustic signature such as Starting point of impact signal, Rising time, Half period, and Global time, they are used as the inputs to neural network. Secondly, we applied the neural network algorithm to LPMS in order to estimate the mass of loose parts. We trained the impact test data of YGN3 using the backpropagation method. The input parameter for training is Rising Time, Half Period, Maximum amplitude. The result showed that the neural network would be applied to LPMS. Also, applying the neural network to the Practical false alarm data during startup and impact test signal at nuclear power Plant, the false alarms are reduced effectively. 1.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3946-3965
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• 2018

Network anomaly detection in Software Defined Networking, especially the detection of DDoS attack, has been given great attention in recent years. It is convenient to build the Traffic Matrix from a global view in SDN. However, the monitoring and management of high-volume feature-rich traffic in large networks brings significant challenges. In this paper, we propose a moving window Principal Components Analysis based anomaly detection and mitigation approach to map data onto a low-dimensional subspace and keep monitoring the network state in real-time. Once the anomaly is detected, the controller will install the defense flow table rules onto the corresponding data plane switches to mitigate the attack. Furthermore, we evaluate our approach with experiments. The Receiver Operating Characteristic curves show that our approach performs well in both detection probability and false alarm probability compared with the entropy-based approach. In addition, the mitigation effect is impressive that our approach can prevent most of the attacking traffic. At last, we evaluate the overhead of the system, including the detection delay and utilization of CPU, which is not excessive. Our anomaly detection approach is lightweight and effective.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.854-859
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• 2002

Location Based Services, or LBS refers to value-added service by processing information utilizing mobile user location. With the rapidly increasing wireless internet subscribers and world LBS market, the various location based applications are introduced such as buddy finder, proximity and security services. As the killer application of the wireless internet, the LBS has preconsidered technology about location determination technology, LBS middleware server for various application, and diverse contents processing technology. This paper describes the open architecture for LBS platform ensuring interoperability among the wireless networks and various location-based application services and the functional requirements for the LBS platform. The LBS platform in a narrow sense provides a standard interfaces for location management and network management for location services as follows, positioning (location acquisition through network or/and handset), location managing, location based functions, profile management, authentication and security, location based billing, information roaming between carriers and the system monitoring independent to specific network or ISP/CPs(Content Providers).

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.3
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• pp.126-133
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• 2009

There are already many researches providing u-Healthcare service, but they have left problems to be improved. First of all, the transmission range between sensor nodes and the gateway are restricted. Hence, patients feel uncomfortable because of they need to possess or locate closed to a gateway all the time when they aggregates their medical data. Also, the existing systems have not considered life environment that is important to analyze patient's diseases. Moreover, a guardian need to located close to patient or possess a mobile device that monitors a patients' status in real time when they are in outdoor. In this research, we present multi-hop packet transfer algorithm and compilation of life environment which help improve the problem of the existing researches. Likewise, we designed and implemented a medical information database and a real-time web monitoring system that manage patients' personal history and monitor a patients' status in real time. In this paper, we design and implement the u-Healthcare system based on mobile environment and we present a result when we tested our u-Healthcare system in scenario environment.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2281-2293
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• 1999

Many applications such as nuclear power plant monitoring, plant process control, stock market management, and network data management require a database system supporting both temporal data model and active rule processing. There have been some efforts to extend the temporal functionalities of the active database system, but an active database system based on temporal database, especially the one applied to the real application is rare. In this paper, we proposed an active temporal rule model based on bi-temporal database. And a rule language following the proposed rule model was described with its execution semantics. Then, how to apply to the nuclear power plant monitoring system was given as the examples.

• ETRI Journal
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• v.26 no.3
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• pp.203-217
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• 2004

This paper presents a method and architecture to analyze streaming media and multimedia conferencing traffic. Our method is based on detecting the transport protocol and port numbers that are dynamically assigned during the setup between communicating parties. We then apply such information to analyze traffic generated by the most popular streaming media and multimedia conferencing applications, namely, Windows Media, Real Networks, QuickTime, SIP and H.323. We also describe a prototype implementation of a traffic monitoring and analysis system that uses our method and architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.229-232
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• 2008

A Neural network classification of human activity data is presented. The data acquisition system involves a tri-axial accelerometer in wireless sensor network environment. The wireless ad-hoc system has the advantage of small size, convenience for wearability and cost effectiveness. The system can further improve the range of user mobility with the inclusion of ad-hoc environment. The classification is based on the frequencies of the involved activities. The most significant Fast Fourier coefficients, of the acceleration of the body movement, are used for classification of the daily activities like, Rest walk and Run. A supervised learning approach is used. The work presents classification accuracy with the available fast batch training algorithms i.e. Levenberg-Marquardt and Resilient back propagation scheme is used for training and calculation of accuracy.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.33-41
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• 2009

Network industry is complex combined with various fields of industry, such as communication, broadcast, construction, and home appliances. Moreover, it's fairly lucrative since the growth industry makes lots of added values, interacting with the others.The network industry, usually called 'Ubiquitous', connects some home appliances and makes an integrated system that you can use them with whenever and wherever. A demand for network security, however, has skyrocketed due to the relatively low safety. It's been expected that the market of home security is going to be grown up nearly 30 percent every year. Recently, analog surveilance cameras have been replaced with digital ones, and they will be providing stronger security services taking advantage of mutual interaction with related industies. In this paper, a mobile monitoring system for home security is proposed, which makes it possible to supervise all home appliances wherever you're, using the conventional wired/wireless network infra.