• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.901-923
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• 2017

Efficient key distribution and management mechanisms as well as lightweight ciphers are the main pillar for establishing secure wireless sensor networks (WSN). Several symmetric based key distribution protocols are already proposed, but most of them are not scalable, yet vulnerable to a small number of compromised nodes. In this paper, we propose an efficient and scalable key management and distribution framework, named KMMR, for large scale WSNs. The KMMR contributions are three fold. First, it performs lightweight local processes orchestrated into upward and downward tiers. Second, it limits the impact of compromised nodes to only local links. Third, KMMR performs efficient secure node addition and revocation. The security analysis shows that KMMR withstands several known attacks. We implemented KMMR using the NesC language and experimented on Telosb motes. Performance evaluation using the TOSSIM simulator shows that KMMR is scalable, provides an excellent key connectivity and allows a good resilience, yet it ensures both forward and backward secrecy. For a WSN comprising 961 sensor nodes monitoring a 60 hectares agriculture field, KMMR requires around 2.5 seconds to distribute all necessary keys, and attains a key connectivity above 96% and a resilience approaching 100%. Quantitative comparisons to earlier work show that KMMR is more efficient in terms of computational complexity, required storage space and communication overhead.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.369-376
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• 2018

This paper presents an android-based implementation of real-time remote monitoring system for industrial gas turbines. The use of remote monitoring techniques can be beneficial in terms of not only the reduction of monitoring cost but also the earlier detection of abnormal status. In order to achieve the ability of protecting sensitive information from unauthorized persons, the proposed system supports secure transmissions using the RSA(Rivest Shamir Adleman) algorithm. In the event of abnormal situation on the gas turbine, the remote monitoring system generates an alarm to attract the user's attention by exploiting a push-message technique. The proposed system has been verified through a series of experiments with an experimental setup including a virtual data generator.

• Ocean and Polar Research
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• v.21 no.2
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• pp.117-126
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• 1999

To meet increasing needs for environmentally sustainable management of coastal area, there has been compelling pressure to establish a cost-effective and long-term coastal water quality (CWQ) monitoring system. A remote CWQ monitoring system, STAMP, has been developed and is in operation along the route between Kyema harbor and Anma Island in the southwestern coastal area of Korea. STAMP uses a PCS phone as a telemetry unit to transmit acquired data for monitoring general water quality parameters, and a routinely operating coastal passenger ship or car ferry. STAMP has various merits of low-cost operations; long-term monitoring with secure instrumentation; and stable real-time telemetry of acquired data with-out the loss and noise. It is expected that the system will serve as a very useful tool in the CWQ managing programs of Korea taking the advantage of many coastal passenger ships in various routes including the ships departing from the coastal industrial cities. The acquired data compiled on suspended surface sediment concentrations (SSSC) will be also valuably helpful in understanding the sediment budget across the routes of the vessel.

• The KIPS Transactions:PartC
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• v.18C no.5
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• pp.303-316
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• 2011

Data aggregation is important in wireless sensor networks. However, it also introduces many security problems, one of which is that a compromised node may inject false data or drop a message during data aggregation. Most existing solutions rely on encryption, which however requires high computation and communication cost. But they can only detect the occurrence of an attack without finding the attacking node. This makes sensor nodes waste their energy in sending false data if attacks occur repeatedly. Even an existing work can identify the location of a false data injection attack but it has a limitation that at most 50% of total sensor nodes can participate in data transmission. Therefore, a novel approach is required such that it can identify an attacker and also increase the number of nodes which participate in data transmission. In this paper, we propose a monitoring-based secure data aggregation protocol to prevent against a compromised aggregator which injects false data or drops a message. The proposed protocol consists of aggregation tree construction and secure data aggregation. In secure data aggregation, we use integration of abnormal data detection with monitoring and a minimal cryptographic technique. The simulation results show the proposed protocol increases the number of participating nodes in data transmission to 95% of the total nodes. The proposed protocol also can identify the location of a compromised node which injects false data or drops a message. A communication overhead for tracing back a location of a compromised node is O(n) where n is the total number of nodes and the cost is the same or better than other existing solutions.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.132-132
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• 2000

The reliability of EIC systems in hot rolling mill is indispensable and very important in order to maintain stable production. Signals obtained from sensors and control system should be analyzed to monitor the condition of down coiler in hot rolling mill. We develope a monitoring system of down coiler which is composed of three parts (1) data acquisition and MMI (2) signal processing and analyzing, and (3) automatic data saving. Also it is designed to enable to inform users the abnormal conditions of down coiler. This developed system is expected to make it possible to reduce long downtime, secure high facility precision, and maintain high control levels.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.4
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• pp.48-56
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• 2000

This paper proposes the new concept & design method and implementation of LonWorks network system for telemetry & remote monitoring and control in BAS. In order to apply this open system, the essential components of Lonworks is analyzed and a new concepts of its design method is proposed. In our experiment, Lonworks network system for telemetry & remote monitoring and control of lighting are designed and fabricated. As a result, it is verified that LonWorks is open, interoperable, reliable network system from the experimental results, especially, node development, network configuration & design, secure communication and MMI.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2410-2415
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• 2000

This paper propose the new concept & design method and implementation of LonWorks network system for telemetry & remote monitoring and control in BAS. In order to apply this open system, the essential components of LonWorks is analyzed and a new concepts of its design method is proposed. In our experiment, LonWorks network system for telemetry & remote monitoring and control of lighting are designed and fabricated. As a result, it is verified that LonWorks is open, interoperable, reliable network system from the experimental results, especially, node development, network configuration & design, secure communication and MMI.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.321-327
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• 1998

This paper presented a case study on the application of on-line wear monitoring technique to a high duty air-turbo-compressor system. Main objects monitored were a gear unit and metal bearings, both shown frequent troubles due to the severe operation conditions at heavy dynamic load. The air-turbo-compressor system needs secure condition monitoring because it is one of the main utilities in steel making industry. Temperature and vibration characteristics have been mainly on-line monitored in this system for a predictive maintenance; however, it has been shown that they are not fairly good enough to give an early warning prior to the machine failure. In this work, an on-line Opto Magnetic Detector(OMD) was implemented for an on-line wear monitoring, which quantitatively measured the contamination level of both ferrous and non-ferrous wear particles by detecting the change in optical density of used oil. Results showed that the application of on-line OMD system was satisfactory in diagnosis of the machine system.

• Journal of the Korean Institute of Educational Facilities
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• v.27 no.1
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• pp.3-10
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• 2020

Due to the frequent occurrence of large-scale disasters such as recent earthquakes, the problem of the safety of old school buildings has emerged. The need to secure safety management technology through constant monitoring is increasing in an attempt to supplement old school buildings with weak disaster response capabilities. Traditional research is approaching the development of an existing sensor-based risk precursor information monitoring system. However, unlike this, in this study, we will focus on the development of a data analysis platform as part of the development of a continuous monitoring system that can be prepared for earthquakes, collapses, and fires, based on constantly measured data. For this reason, the development of a safety diagnostic algorithm based on the optimal sensor-attached points and sensor data reflecting the fragile characteristics of old school buildings was derived. Utilizing this, a message and action manual system for each management / use entity of school buildings after retirement was constructed.