Study on prediction of network security situation based on fuzzy neutral network

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1 Avalable ole Joural of Chemcal ad Pharmaceutcal Research, 04, 6(6):00-06 Research Artcle ISS : CODE(USA) : JCPRC5 Study o predcto of etwork securty stuato based o fuzzy eutral etwork Wag Yog ad Hu Ytao Iformato Maagemet Departmet, Xuzhou College of Idustral echology, Xuzhou, Cha ag Agrcultural Uversty Lbrary, ag, Cha ABSRAC etwork securty problem has bee cocered recet years, the predcto of etwork securty stuato ca esure the safety of etwork, ad therefore the applcato of fuzzy eutral etwork o t s studed depth. Frst, the frame of predctg system of etwork securty stuato s desged; Secod, the basc theory of fuzzy eutral etwork s aalyzed; the predcto model of etwork securty stuato are establshed. Fally, the smulato s carred out, ad results show that the fuzzy eutral ca predct the etwork securty stuato correctly. Key words: Predcto; etwork securty stuato; fuzzy eutral etwork Opeess, sharg ad tercoecto degree of etwork s wdeg, ad all kds of etwork securty evets are plg up, ad etwork securty has become creasgly mportat, whch focuses more ad more atteto. he tradtoal, sgle defese equpmet or detecto equpmet has bee ot sutable for the demad of esurg the safe operato of etwork system. It s ecessary to evaluate ad predct the etwork securty stuato accurately ad obectvely, the predcto of etwork securty has become the research focus etwork securty feld. he predcto of etwork securty stuato ca make etwork securty maagemet trasform from passvty to tatve. he etwork maager ca udge the tred of state of etwork safety, the the state of etwork ad attack for etwork ca be uderstad. he etwork maager ca take effectve defesve measures to esure the safety of etwork before the etwork s attacked ad suffered to loss []. he safety stuato of etwork s affected by several factors, such as attacks, vruses, vulerabltes ad troa horse, the tradtoal predctg method oly reflect partal formato ad ca ot obta the correct predctg results, the chages of etwork securty stuato has tme varato, probablty ad olearty, therefore the effectve predctg method should be put forward. I recet years, the artfcal tellgece has developed wdely, ad there are may ways for predctg the etwork safety stuato such as support vector mache, Markov cha, ad the good predctg effect s obtaed. However, the curret predctg methods have lmts, for support vector mache, the parametrc selecto lacks approprate theoretcal gudace, the parameters obtaed are so subectve ad bld, whe the sample s too much, the trag speed wll decrease. Markov cha has dffculty costructg precse predctg model, whch eed to draw up the mathematcal formulae largely, t s very complex. I order to overcome the dsadvatages of the curret predctg methods, the fuzzy eutral etwork s appled the predcto of etwork securty stuato. he fuzzy eutral etwork has the advatage of quck trackg speed, whch ca obta hgher predctg precso, ad t ca be used to deal wth the olear problems. he the predcto algorthm of etwork securty stuato based o fuzzy eutral etwork s establshed [,3]. Frame of predctg system of etwork securty stuato he predcto of etwork securty stuato s to use the relatoshp amog tme seres to predct the value of etwork securty stuato. he calculato of value ad the evaluato of etwork securty stuato makes up of the 00

2 Wag Yog ad Hu Ytao J. Chem. Pharm. Res., 04, 6(6):00-06 whole etwork securty stuato techque. he value of etwork securty stuato ca produce the threat formato for the etwork maager, ad the maager ca refer the evaluato results of etwork securty stuato, ad cofrm the possble threat, fally the maager ca fd a proper method to deal wth the threat [4]. he evaluato of etwork securty stuato s the qualtatve aalyss based o evaluatg the workg state of etwork. he am of the evaluato s to help the decder to percept the securty stuato quckly ad correctly. he evaluato of securty stuato cocludes three stages: stuato percepto, stuato uderstadg ad stuato predcto. he frame of predcto of etwork securty stuato based o fuzzy eutral etwork s show fgure. Uderlyg data fuso results Stuato percepto ad uderstadg Calculato of stuato value Stuato predcto Fuzzy eutral etwork Fgure predcto frame of etwork securty stuato based o fuzzy eutral etwork he value of etwork securty stuato s a set of or several sets of values merged by huge etwork securty formato based o a seres of mathematcal methods [5,6]. he value ca reflect the rug character of etwork. he value ca chage wth the chages of frequeces, umber of etwork securty evets. he value of etwork securty stuato ca be calculated based o fgure. Defg ad calculatg weght value Coutg the frequeces of evets Weghted average Value of etwork securty stuato Fgure Calculato method of etwork securty stuato value Basc theory of fuzzy eutral etwork here are fve layers for fuzzy eutral etwork, whch are puttg layer, fuzzy layer, fuzzy assocato layer, assocato layer after fuzzy, ad outputtg layer, the correspodg dagram s show fgure 3 [7]. 0

3 Wag Yog ad Hu Ytao J. Chem. Pharm. Res., 04, 6(6):00-06 Fgure 3 Dagram of fuzzy eutral etwork Iputtg layer: the fucto of puttg layer s to troduce the puttg varable to fuzzy layer, ad the correspodg puttg varable vector s expressed as follows:: X = x, x,, ] [ L x () he membershp model of puttg vector ca be expressed as follows [8]: x c σ x c κ ( x) = φ = e, =,, L, σ () = where, c s the ceter of membershp model, puttg vector. σ s the wdth of membershp, s the dmeso of th Fuzzy layer: dfferet ot of fuzzy layer ca be deoted by a laguage varable, whch ca calculate the membershp degree of puttg vector, ad the calculatg formula of membershp degree s expressed as follows: x c = σ m = e, =,, L, (3) Fuzzy assocato layer: the fuzzy sum s carred out for the puttg varable fuzzy layer, ad the fuzzy assocato vector ca be obtaed, the correspodg mathematcal model s expressed as follows: = m{ m, m, m λ k, A },, =, k =,, (4) where, = =. 0

4 Wag Yog ad Hu Ytao J. Chem. Pharm. Res., 04, 6(6):00-06 Assocato layer after fuzzy:the assocato layer after fuzzy s to calculate the ormalzed results of assocato vector, ad the calculatg formula ca be expressed as follows [9]: β λ =, =,, A β = = λ = (5) (6) Outputtg layer: the outputtg layer s to carry out lear weghted sum of assocato stregth ormalzed, ad the correspodg mathematcal model s lsted as follows: Y = = ω α = ω Φ (7) where elemets, ω deotes the assocato weght betwee two elemets, ω deotes assocato vector betwee two ω =, [ ω, ω, ω ] Φ =. [ α, α, α ] 3 heory model of etwork securty stuato Defe the tme seres of etwork securty stuato as X { x( t) t =,, } be expressed as follows: =, ad the sample space S ca { X ( t), Y ( t)} = {[ x( t τ ), x( t τ ), L x( t dτ )],[ x( t)]} (8) t =, τ, τ, L,( d + ) τ, τ s tme lag, d s embeddg dmeso, (t) (t ( d ) τ. where X s puttg sample of predctg model, Y ) s the obect value of predctg model, ad the umber of sample sample space s he predcto value s affected by the adacet tme seres pot durg the processo of predctg the etwork securty stuato. he the proper trag samples that s close to predctg pots chose ca mprove the predctg precso. Assume that there are l samples the space S, the legth of sample wdow s defed by w, the whe Y (t) s predcted, the w samples before t are chose to costruct the predctg model f : R d R, the the predctg model s used to predct Y (t) Y ˆ( t ad predctg model s expressed as follows: value ), the mappg relatoshp betwee the predctg Yˆ ( t) = f ( x( t τ ), x( t τ ), L x( t dτ )) (9) 4 Predcto algorthm of etwork securty stuato Predctg the etwork securty stuato based o fuzzy eutral etwork should solve the followg problems: f the fuzzy segmetato of mputg vector s gve advace, the lkg weght value ω betwee two elemets, the membershp degree model parameter c ad σ should be traed. I order to reduce the trag tme of fuzzy eutral etwork, ad mprove the calculatg effcecy, the tellget algorthm s appled to trag the parameters metoed above, the geetc algorthm s used ths research, the ma reaso s that the geetc algorthm s a advaced optmum algorthm, whch s put forward based o evoluto rules of lvg thgs, t ca reflect the optmum dea of atural selecto ad survval of the fttest, whch ca calculate the lkg weght betwee two elemets ad relevat parameters of membershp model, the the best predcto results of etwork securty stuato ca be obtaed, the aalyzg procedure of predcto of etwork securty stuato based o fuzzy eutral etwork s lsted as follows: 03

5 Wag Yog ad Hu Ytao J. Chem. Pharm. Res., 04, 6(6):00-06 Step :costruct the structure of fuzzy eutral etwork, ad cofrm the umber of eutral elemets for every layer accordg to the remad of predcto of etwork securty stuato. Step :the value scope of parameter fuzzy eutral etwork chages from 0 to, the the ormalzato calculato s carred out for the trag data fuzzy eutral etwork, ad the correspodg ormalzato formula s expressed as follows: f ( x) = max m m (0) where, x s the orgal data, f (x) s the ormalzato fucto. Step 3:the calculato processo ca be smplfed through drect real umber ecodg;whe codg, the ceter ad wdth of every membershp model ca be sorted by sze. Durg the tersecto, the probablty that the ceter ad wdth of membershp for dfferet dvdual chage at the same tme wll mprove, ad the effcecy of geetc operato ba be mproved. Step 4: Calculate the ftess of dvdual, ad the calculato formula of ftess d ft = = ( d Y ) d ft s expressed as follows: () where, d s the ratoal output, ad y s the output of fuzzy eutral etwork. Step 5:the optmum dvdual obtaed ths calculato before teractg operato ca be trasmtted to ext geerato, the algorthm ca be avod to Fall to the local optmal soluto, the teractg operato ad mutato operato ca be carred out for other dvduals accordg to the teractg probablty ad mutato probablty, the the ew dvdual ca be formed. Step 6:the fuzzy eutral etwork traed ca be appled the predctg the etwork securty stuato 5 Smulato o predcto of etwork securty stuato I order to verfy the effectveess ad ratoalty of fuzzy eutral etwork based o geetc algorthm, the smulato o the predcto of etwork securty stuato s carred out, the data comes from data set of hacker attack collected by Hoeyet group. Ad the smulato program s compled by MALAB software. he parameters of predctg model are lsted as follows: the dmeso of puttg vector s 4, the four days are used as a cycle; the dmeso of output vector s, the stuato value of oe day ca be predcted; the umber of trag samples are chose as 84, whch are data fourtee weeks. I order to avod the bg error, the ormalzato processg s carred out for the stuato value, the correspodg formula s expressed as follows: xˆ = max m m () where x max s the maxmum value of stuato value, m x s the mmum value of stuato value, xˆ s the ormalzato value, x s the curret stuato value. he fal results of stuato value the smulato are show fgure 4. 04

6 Wag Yog ad Hu Ytao J. Chem. Pharm. Res., 04, 6(6): ormalzato stuato value order umber Fgure 4 fal results of stuato value the smulato he maxmum terato tmes are take as 50, the umber of dvduals group s take as 50, ad the teractg probablty s 0.75, ad the mutato probablty s he traed fuzzy eutral s used to predct the stuato value from Ja. 6 to Ja., 04, ad the predctg results are show fgure predctg values measured values ormalzato stuato value order umber Fgure 5 Predctg results of etwork securty stuato value based o fuzzy eutral etwork 05

7 Wag Yog ad Hu Ytao J. Chem. Pharm. Res., 04, 6(6):00-06 As see from fgure 5, the fuzzy eutral etwork has better predctg precso predctg the etwork securty stuato value, the chagg rules of stuato value are show fgure 5, ad the measured value s bascally agreemet wth predcto value. Accordg to the chagg treds of stuato value, the etwork maager ca udge the probablty of attack, the the maager ca take measuremet to avod the attack ad protect the etwork securty. COCLUSIO Accordg to the dsadvatages of curret predctg method of etwork securty stuato, the fuzzy eutral etwork wth geetc algorthm s appled the predctg the securty stuato of etwork. he fuzzy eutral etwork has ablty dealg wth the olear problems. Smulato s carred out, ad results show that the fuzzy eutral etwork ca obta better relable predctg results, whch ca reflect the securty state of etwork. REFERECES [] Yaxg Zhag, Shuyua J, Xag Cu, et al. Commucatos Computer ad Iformato Scece Volume 30, 03, pp [] Boyu Zhag, Zhgag Che, Xa Ya, et al. Lecture otes Computer Scece, Volume 6838, 0, pp [3] Baoq Ca. Lecture otes Electrcal Egeerg, Volume 73, 04, pp [4] J Yag, Cl Wag, Le Yu, et al. Commucatos Computer ad Iformato Scece, Volume 308, 0, pp [5] Zhag Ruru, L ao, Xao X, et al. Commucatos Computer ad Iformato Scece, Volume 34, 0, pp -8 [6] Zeg B, Zhog Pg. Computer Smulato, 0, 9(5): (I Chese). [7] Pe-Cha Chag, Ch-Yua Fa, Jyu-Je L. Iteratoal Joural of Electrcal Power & Eergy Systems, Volume 33, Issue, 0, Pages 7 7 [8] Yüksel Özbay, Rahme Ceyla, Bekr Karlk. Expert Systems wth Applcatos, Volume 38, Issue, 0, Pages [9] Log Xu, Jupg Wag, Quash Che. Eergy Coverso ad Maagemet, Volume 53, Issue, 0, Pages