• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.152-155
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• 2010

실시간 데이터 마이닝 기법은 다양한 종류의 센서에서 수집된 다차원 스트림 데이터들 사이에 존재하는 의미있는 정보를 탐사할 수 있다. 전통적인 데이터베이스 시스템에서의 마이닝 기법은 정적인 데이터베이스에 기초하므로 실시간으로 수집되는 스트림 데이터는 시간 속성을 갖는 인터벌 이벤트로 요약되어야 한다. 이 논문은 다차원 스트림 데이터 환경에서 스트림 데이터를 요약하고 이들 사이에 존재하는 인과 관계를 탐사하는 실시간 데이터 마이닝 기법을 제안한다. 제안 기법은 센서에서 수집되는 데이터의 대부분이 객체의 정상적인 상태 데이터임을 고려하여 의미있는 이상 이벤트를 선별하여 전송한다. 그리고 스트림 데이터의 연속성을 고려하며 스트림 데이터를 세 가지 상태의 이벤트로 요약하고 인과 관계 규칙을 탐사한다. 인과 관계 규칙은 시간에 따라 이벤트 발생에 영향력을 미치는 원인 이벤트를 발견함으로써 이벤트의 발생을 미리 예측할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.688-696
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• 2013

In wireless sensor networks, real-time applications have to ensure the timely delivery of real-time data. Recently, OMLRP (On-demand Multi-hop Look-ahead Routing Protocol) has been proposed to improve the timeliness of wireless sensor networks. The protocol needs initialization time to establish multi-hop information based routing path because it performs incremental look-ahead of the information. Consequently, the protocol deteriorates DDSR (Deadline Delivery Success Ratio) as an event moves because it takes little consideration of event mobility. In this paper, we proposed a Real-time Routing for Events Mobility (RREM) which exploits a data redirection in order to improve the DDSR of moving events. Instead of recollecting muti-hop look-ahead information, the RREM redirects the data to a sensor node holding the information collected in a previous round. We verify the timeliness and energy efficiency of RREM using various MatLab simulations.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.69-70
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• 2015

본 논문에서는 운행중인 차량이 수집한 위치별 교통 이벤트 (지체, 정체, 사고, 노면상태 등)를 다른 운행 차량과 실시간으로 공유하여 안전운행 서비스를 제공하기 위한 방법을 제안한다. 운행중인 차량은 차량내의 스마트 기기나 전용 기기를 이용해 수집한 교통이벤트를 실시간으로 서버로 전송하고 서버는 전송된 교통이벤트를 위치별, 시간별로 색인하고 중복된 교통이벤트를 분류하여 저장한다. 이런 모든 과정은 처리 속도 향상을 위해 Spark의 RDD를 이용해서 인-메모리에서 처리된다.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.324-332
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• 2010

The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings from heterogeneous sensors and subsequently detect complex events of interest in real-time fashion need further research. We are developing real-time event detection approaches which allow light-weight data fusion and do not require significant computing resources. Underlying the event detection framework is a collection of real-time monitoring and fusion mechanisms that are invoked upon the arrival of sensor data. The combination of these mechanisms and the framework has the potential to significantly improve the timeliness and reduce the resource requirements of embedded sensor networks. In addition to that, we discuss about a privacy that is foundation technique for trusted embedded sensor network system and explain anonymization technique to ensure privacy.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.271-273
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• 2005

많은 글로벌 기업들이 비용절감 및 효율성 증대를 위하여 RFID 시스템을 도입하거나 도입을 적극 검토 중에 있다. RFID 시스템으로부터 획득된 수많은 정보들이 기업의 업무효율을 증대시킬 수 있도록 하기 위해서는 상위 응용 서비스에서 RFID 데이터를 효율적으로 사용할 수 있도록 리더와 응용 서비스 간의 중계 역할을 할 수 있는 RFID 미들웨어의 역할이 매우 중요하다. 이러한 요구사항에 맞춰 최근 EPCglobal에서는 RFID 미들웨어인 ALE(Application Level Event)를 제시하고 있다. ALE는 RFID 리더에 의해 읽혀진 EPC 이벤트 데이터를 실시간으로 수집하여 원본 데이터의 오류를 보정한 후에 사용자와 응용 서비스의 요구에 따라 특정 이벤트 데이터를 필터링하여 보고하는 역할을 한다. 본 논문에서는 ALE의 실시간 EPC 이벤트 데이터 처리를 위한 EMS(Event Management System) 컴포넌트를 제시하며 EMS에 대한 요구사항을 분석하고 설계하였다. EMS 컴포넌트는 RFID 리더를 통해서 끊임없이 들어오는 스트링 형태의 EPC 이벤트 데이터를 블록킹 없이 수집하는 역할을 한다. 또한, RFID 리더에서 수집한 데이터의 보정 및 필요 데이터 추출을 위한 다양한 필터링 기능을 제공함으로써 수집된 데이터의 정확성을 높이며 신속한 데이터 제공을 가능하게 한다.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.599-608
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• 2008

Advanced wireless network and sensor technologies are capable of collecting information such as temperature, humidity, weight, and location about objects at real time in logistics area. Besides, users want to be notified of contextual information about interest of objects whenever they want it and wherever they want it. To satisfy these requirements, applications should collect and analyze contextual information at real time, and must support a service that can notify it to wanted users. Event-based service is one of the way to satisfy these requirement of users. In this paper, we design an event notification system focused on location- and RFID-based logistics area. To do this, we present XML-based event expression model, ECA-based profile definition model, and an algorithm that has high scalability by distinguishing event filtering in two steps. Based on these designs, our implemented system can apply to not only logistics area but also intelligent traffic control system based on RFID or GPS devices.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.31-43
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• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.39-49
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• 2014

Cyber threats on the Internet are tremendously increasing and their techniques are also evolving constantly. Intrusion Detection System (IDS) is one of the powerful solutions for detecting and analyzing the cyber attacks in realtime. Most organizations deploy it into their networks and operate it for security monitoring and response service. However, IDS has a fatal problem in that it raises a large number of alerts and most of them are false positives. In order to cope with this problem, many approaches have been proposed for the purpose of automatically identifying whether the IDS alerts are caused by real attacks or not. In this paper, we present an alert verification method based on correlation analysis between vulnerability inspection results for real systems that should be protected and the IDS alerts. In addition, we carry out practical experiments to demonstrate the effectiveness of the proposed verification method using two types of real data, i.e., the IDS alerts and the vulnerability inspection results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.970-972
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• 2010

ERP is an integrated information system to manage all human and material resources in offices. Therefore, the business competitiveness is reinforced. The best requirement of ERP is the real time data collection and analysis in ubiquitous environment. Passive information collection is a problem in existing ERP system. To solve that problem, active system is proposed using RFID Tag and Reader. From the simulation results, we confirm that resource information is acquired and event message is occurred after fixed time. In this paper, the real time management system of industry resource with RFID collects resource information actively instead of passive information collection and supports the event according to the schedule.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.