Hybrid gene expression programming-based sensor data correlation mining

2017 ◽  
Vol 14 (1) ◽  
pp. 34-49
Author(s):  
Lechan Yang ◽  
Zhihao Qin ◽  
Kun Wang ◽  
Song Deng
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming ◽  
Sensor Data ◽  
Data Correlation ◽  
Hybrid Gene ◽  
Correlation Mining

Intrusion Detection on Hybrid Gene Expression Programming

2011 ◽  
Vol 143-144 ◽  
pp. 526-530 ◽  
Author(s):  
S. Deng ◽  
W.M. Lin ◽  
T. Zhang
Keyword(s):  
Gene Expression ◽  
Intrusion Detection ◽  
Rough Set ◽  
High Dimension ◽  
Detection Efficiency ◽  
Gene Expression Programming ◽  
Detection Algorithm ◽  
Data Sets ◽  
Hybrid Gene ◽  
High Dimension Data

This paper present intrusion detection on hybrid gene expression programming (ID-HGEP), which combined theory of attribution reduction in rough set to improve precision and efficiency on intrusion detection. Through extensive experiments on high dimension data sets, it is shown that ID-HGEP is apparently more advantageous in terms of convergence speed, intrusion detection efficiency and average consumptive time in contrast with traditional intrusion detection algorithm on GEP.

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