Situation element extraction of network security based on Logistic Regression and Improved Particle Swarm Optimization - Details

author：

Li, Dongyin (Li, Dongyin.) ^[1] | Liu, Zhanghui (Liu, Zhanghui.) ^[2] (Scholars：刘漳辉)

Indexed by：

EI Scopus

Abstract：

Situation　element　extraction　of　network　security　situation　awareness　can　be　transformed　into　the　vast　amounts　of　data　recognition　and　classification.　Due　to　the　difficulty　of　situation　element　extraction　of　network　security　situation　awareness,　a　mechanism　for　situation　extraction　based　on　Logistic　Regression　(LR)　and　Improved　Particle　Swarm　Optimization　(LR-IPSO)　model　is　proposed.　In　order　to　improve　local　and　global　search　capability　of　Particle　Swarm　Optimization(PSO),　this　paper　takes　the　nonlinear　decreasing　random　strategy　for　weight　value　to　improve　PSO,　because　of　the　inherent　implicit　parallelism　and　good　global　optimization　ability　of　IPSO,　it　is　used　to　estimate　parameters　and　optimize　the　learning　ability　of　the　LR　model.　Experiment　results　show　that　this　model　is　an　effective　extraction　technology　of　situation　element.　©　2013　IEEE.

Keyword：

Extraction Global optimization Network security Particle swarm optimization (PSO) Reactive power Regression analysis

Community：

[ 1 ] [Li, Dongyin]College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou 350108, China
[ 2 ] [Liu, Zhanghui]College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou 350108, China

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