• 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.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.592-595
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• 2013

Advent of Wireless Sensor Networks (WSN) has provided potentials to a variety of construction applications. It is well appreciated that WSNs have advantages over traditional wired system, such as ease of installation and maintenance with increased cost savings and efficiencies. However, the obstruction of wireless signal from physical objects in the heterogeneous construction environment often brings challenges to WSN measurement system. This paper analyzed the obstruction characteristic of construction environment where construction materials, equipment, and built structures obstruct the wireless signal yielding negative effect of measurement system. By adopting evaluation criteria, such as packet reception rate, field experiments have been implemented to quantitatively identify the interference of wireless signal from penetration, reflection, and network traffic under the construction environment. The results show that reliable performance of wireless sensor in construction environment depends on the optimal separation distance between a receiver and a transmitter, obstruction types, obstruction thickness, and transmission interval. In addition, the methodology and experimental results of this paper could be used in the practical design of network topology when hundreds of sensor nodes form a mesh network in the large scale construction applications.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.339-343
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• 2012

Security and monitoring system has many applications and commonly used for detection, warning, alarm, etc. As the networking technology advances, user requirements are getting higher. An intelligent and cooperative surveillance system is proposed to meet current user demands and improve the performance. This paper focuses on the implementation issue for the embedded intelligent surveillance system. To cover wide area cooperative function is implemented and connected by wireless sensor network technology. Also to improve the performance lots of sensors are employed into the surveillance system to reduce the error but improve the detection probability. The proposed surveillance system is composed of vision sensor (camera), mic array sensor, PIR sensor, etc. Between the sensors, data is transferred by IEEE 802.11s or Zigbee protocol. We deployed a private network for the sensors and multiple gateways for better data throughput. The developed system is targeted to the traffic accident detection and alarm. However, its application can be easily changed to others by just changing software algorithm in a DSP chip.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2172-2178
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• 2007

In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1031-1034
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• 2005

This paper introduces a novel sensor network protocol, R-WSLP(Realtime Wireless Sensor Line Protocol), which has extremely low latency characteristic in large-scale WSN. R-WSLP is proposed to implement realtime forest fire monitoring system. We propose Distributed TDMA method for the multiple channel access and Time Synchronized Forwarding Mechanism instead of routing technique to achieve low latency network. Also, R-WSLP provides extremely low power operation which we accomplished by reducing idle listening. In our experimentation, we get successful results at the forest fire monitoring system with our protocol.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.209-217
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• 2012

In the present, Wireless Sensor Network(WSN) has been used for the purpose of the military operation with surveillance systems and for collecting useful information from the natural environment. Basically, low-power, easy deployment and low cost are the most important factors to be deployed for WSNs. Lots of researches have been studied to meet those requirements, especially on the node capacity and battery lifetime improvements. Recently, the study of wireless mesh networks applied into the surveillance systems has been proceeded as a solution of easy deployment. In this paper, we proposed large-scale intelligent multi-layer surveillance systems based on QoS assuring Wireless Mesh Networks and implemented them in the real testbed environment. The proposed system explains functions and operations for each subsystem as well as S/W and H/W architectures. Experimental results are shown for the implemented subsystems and the performance is satisfactory for the surveillance system. We can identify the possibility of the implemented multi-layer surveillance system to be used in practice.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.3
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• pp.102-106
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• 2010

Recently process industries from oil and gas procedures and mining companies to manufactures of chemicals, foods, and beverages has been exploring the USN (Ubiquitous Sensor Networks) technology to improve safety of production processes. However, to apply the USN technology in the large-scale plant industry, reliability and security issues are not fully addressed yet, and the absence of the industrial sensor networking standard causes a compatibility problem with legacy equipment and systems. Although this situation, process industry such as energy plants are looking for the secure wireless plant solution to provide detailed, accurate safety monitoring from previously hard-reach, unaccordable area. In this paper, SPSF (Smart Plant Safety Framework based on Reliable-Secure USN) is suggested to fulfill the requirements of high-risk industrial environments for highly secure, reliable data collection and plant monitoring that is resistant to interference. The SPSF consists of three main layers: 1) Smart Safety Sensing Layer, 2) Smart Safety Network Layers, 3) Plant Network System Layer.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.136-141
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• 2021

Research on wireless sensor networks has focused on the monitoring and characterization of large-scale physical environments and the tracking of various environmental or physical conditions, such as temperature, pressure, and wind speed. We propose a stochastic mobility model that can be applied to a MANET (Mobile Ad-hoc NETwork). environment, and apply this mobility model to a newly proposed clustering-based routing protocol. To verify its stability and durability, we compared the proposed stochastic mobility model with a random model in terms of energy efficiency. The FND (First Node Dead) was measured and compared to verify the performance of the newly designed protocol. In this paper, we describe the proposed mobility model, quantify the changes to the mobile environment, and detail the selection of cluster heads and clusters formed using a fuzzy inference system. After the clusters are configured, the collected data are sent to a base station. Studies on clustering-based routing protocols and stochastic mobility models for MANET applications have shown that these strategies improve the energy efficiency of a network.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6B
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• pp.233-248
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• 2008

Advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks (WSNs). There are numerous applications for wireless sensor networks, and security is vital for many of them. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the lack of infrastructure, all of which impose unique security challenges and make innovative approaches desirable. In this paper, we present a survey on security issues in wireless sensor networks. We address several network models for security protocols in WSNs, and explore the state of the art in research on the key distribution and management schemes, typical attacks and corresponding countermeasures, entity and message authentication protocols, security data aggregation, and privacy. In addition, we discuss some directions of future work.