An Optimized FPN Network Attack Model Based on. Improved Ant Colony Algorithm

Transcription

1 3rd Ieraoal Coferece o Mecharocs ad Idusral Iformacs (ICMII 5) A Omzed FPN Newor Aac Model Based o Imroved A Coloy Algorhm Hul Wu,a, Weua Wu,b* Hebe Academy of Sceces Isue of Aled Mahemacs, Shazhuag 58 Cha School of Iformao, Rem Uversy of Cha, Beg, 87 Cha a wuhul@heb-mah.org, bwuw@ruc.edu.c Keywords: Fuzzy Per e; e aac model; a coloy algorhm; BP algorhm Absrac: FPN aac model ca be wdely aled o a varey of large ad comlex ewor evromes. I hs aer, we rese a omzed FPN ewor aac model based o he mroved a coloy algorhm. Frs, We aly he a coloy algorhm o he FPN ewor aac model o omze he rag rocedure of wegh arameers. Secod, we roduce hybrdzg ad aberrace gee o he algorhm o mrove he covergg rae ad global search caably. Exermes show ha our algorhm acheves hgher accuracy ad faser coverge rae. Iroduco Per e-based ewor aac model was frsly roosed by Mc Demo. I's suable o descrbe ad aalyss he asychroous, cocurre, resource comeo ad oher ssues he large ad comlex sysems. As he ewor aac has he characerscs of uceray ad cocurre, he Per e s exeded o fuzzy Per e (FPN). However, he arameers of FPN, such as wegh, ceray ad hreshold facors deeds o he exerece of exers a a large exe, so s hard o oba accurae resuls. To solve hs roblem, he research resuls o arameer omzao he arfcal ellgece doma s worh learg. For examle, Huag roose a PID corol mehod, whch ulze he roery of he BP eural ewor algorhm ha ca aroxmae ay couous bouded olear fuco[4]. The PID corol mehod ca ada o he dyamc aure of ucera sysems. Peg mrove he mehod ad reses a mehod of omzed PID arameer self-adaed a coloy algorhm wh hybrdzg ad aberrace gee, based o a coloy algorhm[5]. Ths mehod overcomes ordary a coloy algorhm's defecs of slow covergece seed, easy o ge sagae, ad low ably of full search, ad ca realze he omzao of PI D corol arameer erfecly. Currely, some researchers aem o roduce he eural ewor algorhm o he arameer omzao roblem of FPN ewor aac model. However, he resuls are o good. There are reasos. Because of he secal srucure characer of FPN ewor aac model, he orgal eural ewor algorhms ca' ada o he model erfecly. I addo, hese algorhms' ow arameer omzao sraeges have defecs. Amg hese roblems, hs aer we rese a omzed FPN ewor aac model based o he mroved a coloy algorhm. Frs, we aalyss he ferece algorhm of FPN horoughly, ad aly he a coloy algorhm o FPN. Secod, gvg full cosderao o he dsgushg characerscs of FPN aac model, we roduce hybrdzg ad aberrace gee o he algorhm o mrove he covergg rae ad global search caably. 5. The auhors - Publshed by Alas Press 4

2 The res of he aer s orgazed as follows. Chaer roduce he aac model. I Chaer 3, we descrbe he deals of he mehod. The resuls of exermes are show Chaer 4 ad hs sudy s cocluded Chaer 5. Aac Model Fuzzy Per e(fpn) [] s a lbrary ad wo ds of odes chages bdrecoal dreced grah. FPN srucure s defed as a 9-o Eleme: FPN ( P, T, D, I, O, F,, W, ) Where, PN P, T, D, I, O s a basc Per e. F dag (,,, m) s he cofdece marx, s a fuzzy umber bewee [,] erval, ad rereses he cofdece of fuzzy rule dag (,, ), [,], s he al hreshold of ;, m ; s he al sae of he rooso Deedably, ( d,, d) T, s he al logc sae of Prooso d d, [,] d, d of showg he rue exe of he rooso; W { w }, w [,], Rereseao from he lbrary o he chages coeco arc gve arorae wegh. Tha s, dffere morace of dffere chages rgger. w, (,], g g () Each raso FPN corresods o a rule, whle he u lace ad ouu lace of a raso s he recodo ad cocluso resecvely. A raso occurrece meas a corresodg rule maches successfully. The geeral form of fuzzy roduco rules are as follows: Rule : If ad ad ad formally descrbed as Fg.. The (CF ),, w,,, w w. I ca be w w w w w w a) Chage Trgger before b) Chages rggered Fg. ferece rule of FIG. 5

3 The cofdece of he cocluso of Rule s: ( ) ( ) w, ( ) w Rule :If or or or, he ( CF ), formal descro show Fg.. a) Chage Trgger before b) Chages rggered Fg. ferece rule The cofdece of he cocluso of Rule s: ( ) max( ( ),, ( )), ( ) ; Fuzzy Per e s a good modelg ool o descrbe he fuzzy roduco rules owledge sysems [], a drawbac fuzzy sysem self s oor learg ably. FPN hered grahcal deco ably o rerese owledge, ad he rereseao s smle ad clear; also has he ably for fuzzy reasog [3], commoly used he owledge aalyss, esg, ad decso suor, ec. However, le oher fuzzy sysems, he arameers of FPN, such as wegh, ceray ad hreshold facors deeds o he exerece of exers a a large exe, so s hard o oba accurae resuls. As a resul, brgs large dffculy o he owledge ferece. To solve hs roblem, we mae use of he mroved a coloy algorhm o omze he arameer esmao rocedure of FPN ewor aac model. Imroved a coloy algorhm o omze he use of ewor aac model FPN Imroved A Coloy Algorhm The a coloy algorhm s sred from as foragg behavor. The mechasm s o mmc as foragg rocess, hrough he socal arersh, each a leaves chemcal heromoes, he boo accordg o he cocerao of odor as robablsc seleco foragg ah o acheve global search resuls. A coloy algorhm s a global omzao, arallel osve feedbac heursc algorhm, usg o ra FPN arameers, may have a sroger bdg. Bu here are a coloy algorhm s easy o fall o he radoal search sadsll, he comug me s loger, easy o fall o local omum roblem for large comlex ad o well sued FPN ewor. To solve he above roblem, hs aer rooses he roduco of Crossover ad muao oeraor o ehace a a coloy o fd soluo. Ths mehod ca mae full use of exsg heromoe exchage bewee he as ge formao abou he roue, ad crossover ad muao o shore he search me ad reduce he ossbly o a local omum. Ad whle he 6

4 roduco of add caddae se hg, reduce he scoe of he search, mrove accuracy, so ha ca ada o large-scale cyber aacs FPN comlex models. Algorhm ses Sar Ialzao ah As movg a row Local udae Caddae umber Varorum > Radomly geeraed Varao Cross, Varao Choose, Cross, Varao No Ge he soluo Oe ed Calculae alcable degrees E ah Global Prory udaes of caddae Varorum Caddae se s full Yes Elmao of low-rory se of soluos No Mees he codo No Ed Fg. 3 algorhm flowchar 7

5 The frs se: alze radomly geeraed al soluo, he soluo of each comoe s calculaed ha belogs o he sub-erval (Cy), resulg varous ces of he caddae grou, calculaed o each sde (he coeco bewee wo ces), he fess fuco of formao he amou. Se wo: erave rocess 5 Whle (he umber of omzao s more ha 4 mes or fess value. ){ For(= o 7){ ///7 soluo comoes For(= o ){ //// as Deerme he value of he -h comoe of he falls from o ces ad edge formao based o q roulee mehod(3.) Local Udae o he sde of he heromoe (3.) The grou carred ou he caddae seleco, crossover ad muao o roduce ew value - seleced ces. (3.3) } } For(= o ){ Calculae he fess fuco of each a } Value udae formao accordace wh he fess of each sde of (3.4) Tae hgh fess value udag he cy's caddae se (3.5) } Srucural body (Cy) o coued algorhm fess fuco s a error cos fuco E, he cy's caddae se s a comoe of he soluo ca save value ad he fess value, whle refers o he eghborg cy of abou wrg o behalf of comoe rage seleced dreco. The coued algorhms (3.) Selec he -h comoe accordace wh he followg formula where he erval value (Cy), =,,..., arg max{ }, f q q, oherwse. () Argmax whch rereses he larges cocerao of seleced formao edge. q s a radom umber [,], q s a cosa, s referable.8, order o avod remaure hal. robably rereseed by he followg formula bewee o rereseg he seleced value from o ces, cludg dyamcally. () rereses he me, ad umber of urba edge formao, ( ) ( ) / ( ) (3) 8

6 The coued algorhms (3.) le seleced suberval aral udae of formao o he seleced sub-erval mmedaely reduce he amou of formao as arorae, so ha he robably of oher as he lower sub-erval seleced. Le he -h dvdual of he -h comoe of he -h cy s seleced, ress he edge of he aral udae ye formao, whch by he es ae afer a volale facor.. () ( ) () m{ () } (4) Thus, he amou of formao udaed ad releva formao s he orgal -h comoe of he sub-seco covex combao of he mmum amou of formao. Afer he mos formave sub-erval s reeaedly seleced, he amou of formao o reduce he amou of formao o he average level of sub-seco, so ha he robably of oher as choose subervals crease, ha crease udersadg of dversy, whle effecvely reducg he sagao heomea occur. The coued algorhm (3.3) of he caddae se of geec maulao: ) Radom fuco corresodg o he oerao rad(uer), rd( low, double uer), rd(double low, double uer) ) Whe oerag he caddae seleco grou, wh "roulee wheel" aroach o fess fuco E value selecs wo values, he frs value robably of beg seleced s: E / E, whch rereses he caddae grou E All values fess values. 3) I he crossover oerao, he seg seleced wo value x () ad x (), he corresodg fuco values were E, E, ad E E, we have o cross he robably c oerao. Radomly geeraed [,],f c, crossover oerao s erformed. c value should be dyamc, Because of radomly geeraed al oulao dversy, order o mrove he covergece rae, crossover rae should As he omzao rocess creases, order o avod early covergece, he robably of crossg should be reduced usg he followg formula. N s he curre umber of eraos, M s he oal umber of eraos. e c.5 N/ M (5) I he omzao of he rocess should ae a cross-radom umber r [,], cross he resulg value X c x() r [x() x() ] ; f c, crossover oerao s o erformed, Tae Xc x(). 4) I he hase varao ca be he robably m resul of he oerao of cross- X c muag ge X m. m value should be dyamc, ally be relavely small, wh he rogress of 9

7 he omzao rocess of muao robably creases o esure he dversy of he oulao. m he followg formula: m. N/ M e (6) The -h comoe of he -h erval as: [( ).,. ). Le d max{. X c, Xc ( ). }, geeraes a radom umber [,], he value of X m ae followg formula: x m x d ( ).x d.x xc d oherwse c c c (7) Ths wll esure ha he resuls of geec maulao s sll he sub-erval. The coued algorhm (3.4) he M as oba M soluo, accordg o he followg formula for he amou of formao o each ah for udaes: () () (8) Where umber for all ad are umbers hrough he cy o hs sde of he a heromoe sum. Here he frs a afer a edge s lef Q heromoes, heromoe / f hrough he es o ae he resdual coeffce ρ =.5, w =.8, because he rogram s so volved he floag-o oeraos ae Q =., f fess fuco values. The coued algorhms (3.5) whe as oce ge comlee omzao ad adaao values. The caddae each cy grou fess sored by value, deerme wheher you eed o udae he caddae grou. Ths chaer a coloy ad geec combe he advaages of boh roosed a ew omzao algorhm, ad elaboraed o he secfc mlemeao ses, he ew algorhm erformace aalyss of me ad sace, show ha he ew algorhm s feasble, easy o mleme. Exermes I hs aer, rece years, he dagers of a large Boe aacs, for examle, o verfy he algorhm descrbed above. Fg. 4 Boe aac wh weghs FPN rocess. Where o deoe dffere aac sae. Where, : Hos dagerous oe ors; : hos does o oe he frewall; 3: he hos s coeced (o allow daa exchage); 4: he hos does o sar he ach maageme; 5: sysem has overflow; 6: aacer hoss wh User rvleges; 7: a aacer o ga access o he hos comuer; 8: Hos allows remoe maageme; 9: hoss are mlaed Bo rogram; : Bo rogram ad he hos s he worm feced. o 5 deoe dffere aacs. Where, : elevao of rvlege; : Hos exlos; 3: User ermssos o oher hoss Bo mlaao rocedure; 4: Bo remoe mlaao rocedure; 5: Bo hos dowloads he worm

8 feco o he mache. Ad se a deal wegh W = {.4,.3,.3,.5,.35,.4,,.5,.5,}. bach samle daa FPN model ra, where b = 5, he umber of al soluo of a oulaos of, o more ha 4 mes he umber of eraos, he maxmum error of accuracy, corol. 6 or more. Above algorhms are used C ++ rogrammg, algorhms rug he Xeo.7 grahcs worsaos. Through he above daa ad algorhms of rogrammg, he exermeal daa obaed ca be aalyzed ad comared he followg asecs w w w3 w w w w4 w Fg. 4 FPN weghed value rereses Boe aacs of FIG. Comarso of evoluo: he mea square error ad (MSE) hs exerme o verfy he desred ouu value ad ouu value by he recso error bewee afer learg hrough he magude of he error value o rove he effecveess of he learg rocess. BP algorhm rag rocess reflecs he fess of MSE evoluo grah Fg. 5 (a). Fgure fess fuco error accuracy 4. Fg. 5 (b) s mroved a coloy algorhm fess FIG. See from he fgure, he fess fuco value leas ad aroachg he low error, maly because of crossover ad muao facor ca reduce covergece me, ad reves a coloy o a local omum, bu also ca radly aroachg global covergece dreco. Covergece me aalyss: wh cross, ew a coloy algorhm varao facor rescrbed by he as each erao arcag he search, se he aboo able records he rogram ca o ae he ah of he as, hey ca o resrc he same ah he reeaed omzao, o esure ha he omzao effcecy, whle here s also a caddae se of grealy reduced he scoe of he search o esure ha he omzao resuls fas close o he omal soluo a fe umber of mes, effecvely avodg he a coloy o local search sadsll sae, he delay due o geec oeraor geeraed subsaally eglgble, a subsaal crease he effcecy of he rogram. Sce BP algorhm o rogrammg daa srucure volves a large umber of marx oeraos, calculae me-cosumg large. Fg. 6 shows he mes he erave me-cosumg comarso of he wo algorhms.

9 Precso fess Cycles Precso fess Cycles (a)bp algorhm Fg. 5 (b)imroved a coloy algorhm MSE evoluo curve Fg. 6 Comarso of rug seed Cocluso I hs aer, we rese a omzed FPN ewor aac model based o he mroved a coloy algorhm. Fully cosderg he dsgushg aure of FPN, we aly he a coloy algorhm o he FPN ewor aac model. The mehod omze he wegh arameer esmao roblem ad ca beer adave o he comlex ewor aac model. Furhermore, hybrdzg ad aberrace gee are roduced o he algorhm o mrove he covergg rae ad global search caably. The resuls of smulao exermes whch comare o he resul of BP algorhm shows ha our mehod ca beer ada o he comlex FPN ewor aac model, acheves hgher accuracy ad faser coverge rae. Ths aer s suored by he roec of research ad mlemeao of moble healh moorg formao laform, roec umber: 553LR6-4 Referece [] Fay A.A fuzzy owledgebased sysem for ralway raffc corol Egeerg Alcaos of Arfcal Iellgece.3() [] Looey C. G. Fuzzy Per es ad alcao. I : Tzafesas S. G. e al. Fuzzy Reasog Iformao, Decso ad Corol Sysems Norwell,MA: Kluwer Academc Publshers.(994) 5-57.

10 [3] Eugea Mca Dael Racoceau Nouredde Zerhou. Moorg Sysems Modelg ad Aalyss Usg Fuzzy Per Nes[J].Sudes Iformacs ad Corol. () [4] Jya Huag. Sudy PID corol mehod based o BP eural ewor [J]. Mcrocomuer Iformao. (6) [5] Pefu Peg. Adave hybrd a coloy algorhm, he omal PID arameer varao facor [J]. Comuer Egeerg ad Alcaos.6(6)