• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.161-171
• /
• 2010

Sensor Networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes. Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. Ye et al. proposed the Statistical En-route Filtering scheme to overcome this threat. In statistical en-route filtering scheme, all the intermediate nodes perform verification as event reports created by center of stimulus node are forwarded to the base station. This paper applies a probabilistic verification method to the Static Statistical En-route Filtering for energy efficiency. It is expected that the farther from the base station an event source is, the higher energy efficiency is achieved.

• Journal of Sensor Science and Technology
• /
• v.19 no.2
• /
• pp.87-91
• /
• 2010

Hydrogen gas sensors were fabricated using $PdO_x$ loaded with SWNTs. The nanoparticle powders of $SWNT_s-PdO_x$ composite were deposited on Si wafer substrates by a vacuum filtering deposition method. The fabricated sensors were tested against hydrogen gas. The composition ratio that exhibited the highest response to hydrogen gases was SWNTs : $PdO_x$ = 98 : 2 in wt% ratio at operating temperature of about $150^{\circ}C$. The response and recovery times were shorter than 1.0 min. in presence of 1000 ppm hydrogen.

• Journal of Auto-vehicle Safety Association
• /
• v.3 no.2
• /
• pp.28-33
• /
• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.9
• /
• pp.4183-4204
• /
• 2018

The existing en-route filtering schemes only consider some simple false data injection attacks, which results in lower safety performance. In this paper, we propose an efficient geographical information-based en-route filtering scheme (EGEFS), in which each forwarding node verifies not only the message authentication codes (MACs), but also the report identifier and the legitimacy and authenticity of locations carried in a data report. Thus, EGEFS can defend against not only the simple false data injection attacks and the replay attack, but also the collusion attack with forged locations proposed in this paper. In addition, we propose a new method for electing the center-of-stimulus (CoS) node, which can ensure that only one detecting node will be elected as the CoS node to generate one data report for an event. The simulation results show that, compared to the existing en-route filtering schemes, EGEFS has higher safety performance, because it can resist more types of false data injection attacks, and it also has higher filtering efficiency and lower energy expenditure.

• Journal of KIISE:Databases
• /
• v.36 no.4
• /
• pp.280-291
• /
• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.1
• /
• pp.27-31
• /
• 2001

In this paper, we consider the guaranteed cost filtering design method for time-varying delay system with parameter uncertainties by LMI(Linear Matrix Inequality) approach. The objective is to design a stable guaranteed cost filter which minimizes the guaranteed cost fo the closed loop systems in filtering error dynamics. The sufficient conditions for the existence of filter, the guaranteed cost filter design method, and th guaranteed cost upper bound are proposed by LMI technique in terms of all finding variables. Finally, we give an example to check the validity of the proposed method.

• Journal of Communications and Networks
• /
• v.15 no.2
• /
• pp.164-172
• /
• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

• Journal of KIISE:Databases
• /
• v.32 no.4
• /
• pp.372-382
• /
• 2005

Aggregation such as computing an average value of data measured in each sensor commonly occurs in many applications of sensor networks. Since sensor networks consist of low-cost nodes with limited battery power, reducing energy consumption must be considered in order to achieve a long network lifetime. Reducing the amount of messages exchanged is the most important for saving energy. Earlier work has demonstrated the effectiveness of in-network data aggregation and data filtering for minimizing the amount of messages in sensor networks. In this paper, we propose an adaptive error adjustment scheme that is simpler, more effective and efficient than previous work. The proposed scheme is based on self-adjustment in each sensor node. We show through various experiments that our scheme reduces the network traffic significantly, and performs better than existing methods.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.12
• /
• pp.938-942
• /
• 2009

In this paper, we propose a novel filtering method for processing continuous skyline queries on wireless sensor network environments. The existing filtering methods use the filter based on router paths. However, because these filters are applied not to a whole area but to a partial area, these methods send almost data of sensor nodes to transmit to the base station and have no sufficient effect in terms of energy efficiency. Therefore, we propose an efficient method to dramatically reduce the transmission data of sensors through applying a low-cost and effective filter to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.

• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.223-226
• /
• 2003

This paper presents a realization of sensor signal processing(noise filtering) and Fieldbus based communication for condition monitoring of check valve. we first acquired the AE(Acoustic Emission) sensor data at the KAERI check valve test loop, and their frequencies were analyzed to find the informative band. To reject background noises, bandpass filters have been designed. Also, to send the processed data to a remote site, wired communication facility has been realized via DeviceNet.