The intrusion detection, tracking and information collection in mobile sensor networks

2010 ◽  
Author(s):  
Yik Keung
Keyword(s):  
Sensor Networks ◽  
Intrusion Detection ◽  
Mobile Sensor Networks ◽  
Information Collection ◽  
Mobile Sensor

scholarly journals LKM: A LDA-BasedK-Means Clustering Algorithm for Data Analysis of Intrusion Detection in Mobile Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yuhua Zhang ◽  
Kun Wang ◽  
Min Gao ◽  
Zhiyou Ouyang ◽  
Siguang Chen
Keyword(s):  
Data Analysis ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
High Dimension ◽  
Clustering Analysis ◽  
Clustering Algorithm ◽  
Mobile Sensor Networks ◽  
Mobile Sensor ◽  
Data Set ◽  
High Dimension Data

Mobile sensor networks (MSNs), consisting of mobile nodes, are sensitive to network attacks. Intrusion detection system (IDS) is a kind of active network security technology to protect network from attacks. In the data gathering phase of IDS, due to the high-dimension data collected in multidimension space, great pressure has been put on the subsequent data analysis and response phase. Therefore, traditional methods for intrusion detection can no longer be applicable in MSNs. To improve the performance of data analysis, we applyK-means algorithm to high-dimension data clustering analysis. Thus, an improvedK-means clustering algorithm based on linear discriminant analysis (LDA) is proposed, called LKM algorithm. In this algorithm, we firstly apply the dimension reduction of LDA to divide the high-dimension data set into 2-dimension data set; then we useK-means algorithm for clustering analysis of the dimension-reduced data. Simulation results show that LKM algorithm shortens the sample feature extraction time and improves the accuracy ofK-means clustering algorithm, both of which prove that LKM algorithm enhances the performance of high-dimension data analysis and the abnormal detection rate of IDS in MSNs.

scholarly journals Intrusion Detection Based on $k$ -Coverage in Mobile Sensor Networks With Empowered Intruders

2018 ◽  
Vol 67 (12) ◽  
pp. 12109-12123 ◽  
Author(s):  
Haiping Huang ◽  
Tianhe Gong ◽  
Rong Zhang ◽  
Lie-Liang Yang ◽  
Jiancong Zhang ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Intrusion Detection ◽  
Mobile Sensor Networks ◽  
Mobile Sensor

Relative Distance-Aware Data Delivery Scheme for Delay Tolerant Mobile Sensor Networks

2010 ◽  
Vol 21 (3) ◽  
pp. 490-504 ◽  
Author(s):  
Fu-Long XU ◽  
Ming LIU ◽  
Hai-Gang GONG ◽  
Gui-Hai CHEN ◽  
Jian-Ping LI ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Relative Distance ◽  
Data Delivery ◽  
Mobile Sensor ◽  
Delay Tolerant

Group Mobility Adaptive Event Delivery Scheme for Delay Tolerant Mobile Sensor Networks

2012 ◽  
Vol 23 (3) ◽  
pp. 629-647 ◽  
Author(s):  
Lei WU ◽  
Xiao-Min WANG ◽  
Ming LIU ◽  
Gui-Hai CHEN ◽  
Hai-Gang GONG
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Mobile Sensor ◽  
Group Mobility ◽  
Delay Tolerant

Tips on Stochastic Optimal Feedback Control and Bayesian Spatiotemporal Models: Applications to Robotics

2014 ◽  
Vol 137 (3) ◽  
Author(s):  
Jongeun Choi ◽  
Dejan Milutinović
Keyword(s):  
Sensor Networks ◽  
Feedback Control ◽  
Control Theory ◽  
Mobile Sensor Networks ◽  
Optimal Feedback Control ◽  
Mobile Sensor ◽  
Optimal Feedback ◽  
Spatiotemporal Models ◽  
Feedback Control Theory

This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.

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