• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.87-91
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• 2019

In the IoT(Internet of Things) environment, various devices are utilized and applied for different sites. But attackers can access easy to IoT systems, and try to operate DDoS(Distributed Denial-of-Service) attacks. In this paper, Sensor nodes, Cluster heads, and Gateways operates lightweight mutual authentication each others. Since authenticated sensor nodes and cluster heads only send transactions to Gateways, proposed techniques prevent DDoS attacks. In addition, the blockchain system contains secure keys to decrypt data from sensor nodes. Therefore, attackers can not decrypt the data even if the data is eavesdropped.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.98-101
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• 2019

In this paper, we propose the power-based pipelined-forwarding MAC protocol which can select relay nodes according to the residual power and energy harvesting rate in EH-WSN (energy-harvesting wireless sensor networks). The proposed MAC follows a pipelined-forwarding scheme in which nodes repeatedly sleep and wake up in an EH-WSN environment and data is continuously transmitted from a high-level node to a low-level node. The sleep interval is adaptively controlled so that nodes with low energy harvesting rate can be charged sufficiently, thereby minimizing the transmission delay and increasing the network lifetime. Simulation shows that the proposed MAC protocol improves the balance of residual power and network lifetime.

• Journal of KIISE:Information Networking
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• v.36 no.6
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• pp.514-527
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• 2009

Wireless sensor networks (WSNs) can be used in various applications for military or environmental purpose. Recently, there are lots of on-going researches for detecting and tracking the spread of continuous objects or phenomena such as poisonous gas, wildfires, earthquakes, and so on. Some previous work has proposed techniques to detect edge nodes of such a continuous object based on the information of all the 1-hop neighbor nodes. In those techniques, however, a number of nodes are redundantly selected as edge nodes, and thus, the boundary of the continuous object cannot be presented accurately. In this paper, we propose a new edge detection method in which edge nodes of the continuous object are detected based on the information of the neighbor nodes obtained via the Localized Delaunay Triangulation so that a minimum number of nodes are selected as edge nodes. We also define the sensor behavior rule for tracking continuous objects energy-efficiently. Our simulation results show that the proposed edge detection method provides enhanced performance compared with previous 1-hop neighbor node based methods. On the average, the accuracy is improved by 29.95% while the number of edge nodes, the amount of communication messages and energy consumption are reduced by 54.43%, 79.36% and 72.34%, respectively. Moreover, the number of edge nodes decreases by 48.38% on the average in our field test with MICAz motes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.9
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• pp.1-7
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• 2008

The efficient node energy utilization in wireless sensor networks has been studied because sensor nodes operate with limited power based on battery. Since a large number of sensor nodes are densely deployed and collect data by cooperation in wireless sensor network, keeping more sensor nodes alive as possible is important to extend the lifetime of the sensor network. Energy efficiency is an important factor of researches that efficient routing algorithm is needed in wireless sensor network. In this research, I consider some methods to utilize more efficiently the limited power resource of wireless sensor networks. The proposed algorithm is the sink first divides the network into several areas with hop counts and data transmission based on cluster ID. The performance of the proposed algorithm has been examined and evaluated with NS-2 simulator in terms of lifetime, amount of data and overhead.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.113-118
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• 2011

In this paper, we develop a speaker gender classification technique using collaborative sensor fusion for use in a wireless sensor network. The distributed sensor nodes remove the unwanted input data using the BER(Band Energy Ration) based voice activity detection, process only the relevant data, and transmit the hard labeled decisions to the fusion center where a global decision fusion is carried out. This takes advantages of power consumption and network resource management. The Bayesian sensor fusion and the global weighting decision fusion methods are proposed to achieve the gender classification. As the number of the sensor nodes varies, the Bayesian sensor fusion yields the best classification accuracy using the optimal operating points of the ROC(Receiver Operating Characteristic) curves_ For the weights used in the global decision fusion, the BER and MCL(Mutual Confidence Level) are employed to effectively combined at the fusion center. The simulation results show that as the number of the sensor nodes increases, the classification accuracy was even more improved in the low SNR(Signal to Noise Ration) condition.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.51-58
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• 2010

In data collection using a mobile sink, the time that sensor nodes are included in its communication radius is not uniform. The data collection schedule in non-uniform time is needed between a mobile sink and sensor nodes for efficient data collection. The existing data collection schemes using a mobile sink considered staying time in its communication range and data collected by the mobile sink. However, they did not consider the characteristics of data collected in sensor networks. In this paper, we propose a TDMA based schedule scheme that consists of the data collection period by each sensor nodes and the data collection period between a mobile sink and sensor nodes. Moreover, we propose a data collection scheme considering the variability of data in sensor networks. The proposed data collection scheme collects only data that changed larger than the threshold set by the user. In order to show the superiority of the proposed scheme, we compare it with DWEDF that aims to collect data uniformly. As a result, our experimental results show that the proposed scheme reduces about 23% energy consumption and the data collection failure of sensor nodes over the DWEDF.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.83-97
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• 2021

Wireless sensors that make up the Wireless Sensor Network generally have extremely limited power and resources. The wireless sensor enters the sleep state at a certain interval to conserve power. The Sleep deflation attack is a deadly attack that consumes power by preventing wireless sensors from entering the sleep state, but there is no clear countermeasure. Thus, in this paper, using clustering-based binary search tree structure, the Sleep deprivation attack detection model is proposed. The model proposed in this paper utilizes one of the characteristics of both attack sensor nodes and normal sensor nodes which were classified using machine learning. The characteristics used for detection were determined using Long Short-Term Memory, Decision Tree, Support Vector Machine, and K-Nearest Neighbor. Thresholds for judging attack sensor nodes were then learned by applying the SVM. The determined features were used in the proposed algorithm to calculate the values for attack detection, and the threshold for determining the calculated values was derived by applying SVM.Through experiments, the detection model proposed showed a detection rate of 94% when 35% of the total sensor nodes were attack sensor nodes and improvement of up to 26% in power retention.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.27-36
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• 2011

The sensor nodes of sensor network system are capable of wireless communication with sink nodes. They also acquire and transmit sensor data in broad region where people cannot access easily. However, the transmission of redundant data from sensor nodes reduces the lifetime of the entire system and substantial amount of resulted data needs to be resorted before implementing them to the specific applications. In this paper, the mobile agent middleware to eliminate the redundant sensor data is designed and implemented. In the proposed system, the mobile agent visits the destination sensor nodes according to the migration list offered by the meta table in the name space of the naming agent, eliminates the redundant sensor data corresponding to user condition, and acquires and transmits sensor data according to the purpose and needs. Thus, the excess transmission of the sensor data is avoided and the lifetime of the entire system can be extended. Moreover, the experiments using the mobile agent middleware with the conditions and limitations that are possible in real situation ore done to verify the successful elimination of the redundant sensor data and the efficiency of the data acquisition. Also, we show the potential applicability of the mobile agent middleware in various active sensor networks through the active rule based mobile agent middleware or the interaction with the active rule system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4883-4901
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• 2016

Energy efficiency in Wireless Sensor Networks (WSNs) is very appealing research area due to serious constrains on resources like storage, processing, and communication power of the sensor nodes. Due to limited capabilities of sensing nodes, such networks are composed of a large number of nodes. The higher number of nodes increases the overall performance in data collection from environment and transmission of packets among nodes. In such networks the nodes sense data and ultimately forward the information to a Base Station (BS). The main issues in WSNs revolve around energy consumption and delay in relaying of data. A lot of research work has been published in this area of achieving energy efficiency in the network. Various techniques have been proposed to divide such networks; like grid division of network, group based division, clustering, making logical layers of network, variable size clusters or groups and so on. In this paper a new technique of group based WSNs is proposed by using some features from recent published protocols i.e. "Energy-Efficient Multi-level and Distance Aware Clustering (EEMDC)" and "Energy-Efficient Multi-level and Distance Aware Clustering (EEUC)". The proposed work is not only energy-efficient but also minimizes the delay in relaying of data from the sensor nodes to BS. Simulation results show, that it outperforms LEACH protocol by 38%, EEMDC by 10% and EEUC by 13%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.850-857
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• 2005

Sensor networks consist of sensor nodes with small size, low cost, lowpower consumption, and multi-functions to sense, to process and to communicate. The main issue in sensor networks has been focused on minimizing power consumption of sensors to maximize network life time. In some critical applications, however, the most important issue is to transmitsensing information to the end user (the sink node) with reliability. Reliable information forwarding using multiple paths in sensor networks (ReinForM) has been proposed to achieve desired reliability in the error-prone channel, but it needs increasing transmission riverhead as the channel error rate becomes high and the number of hops between the source node and the sink node increases. In this paper, we propose a reliable transmission rnechanissmusing intermediate source nodes in sensor networks (ReTrust) to reduce packet overhead while keeping the desired reliability. ReTrust has beenshown to provide desired reliability and reduced overhead via simulationsand analysis.