Researches on Grid Security Authentication Algorithm in Cloud Computing

Transcription

1 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE eseaches o Gd Secuty Authetcato Algothm Cloud Computg Keshou Wu * Depatmet of Compute Scece ad Techology, Xame Uvesty of Techology, Xame 36005, Cha Emal: kollzok@yahoo.com.c Lzhao Lu Depatmet of Compute Scece ad Techology, Xame Uvesty of Techology, Xame 36005, Cha Emal: @qq.com Ja Lu College of Ifomato Sceces ad Techology, The Pesylvaa State Uvesty, PA, USA Emal: @qq.com Wefeg L, Gag Xe, Xaoa Tog ad Yu L KOLLZOK Itellget Techology Co., Ltd, Xame, 36024, Cha Emal: kollzok@yahoo.com Abstact Focusg o mult-mache dstbuted computg secuty poblems cloud computg, the pape has poposed a gd dstbuted paallel authetcato model based o tusted computg, whch ca ealze smultaeous vefcato of gd authetcato ad gd behavo o uppe laye of SSL ad TLS potocols. Adaptve gd authetcato method s establshed applyg adaptve steam cphe famewok a adaptve steam cphe heustc code geeato ad k-meas heustc behavo tust quey fucto s poposed ad acted as authetcato keel. Though compaso of the test esults of TLS ad SSL authetcato potocol ad the ew gd authetcato method, the effectveess of the ew gd authetcato method has bee eplaed. Ide Tems dstbuted computg tusted computg cloud computg gd behavo gd authetcato TLS SSL I. INTODUCTION Taspot Laye Secuty (TLS) ad ts pedecesso, Secue Sockets Laye (SSL), ae cyptogaphc potocols that povde commucatos secuty ove the Iteet[][2]. TLS ad SSL ecypt the segmets of etwok coectos above the Taspot Laye, usg symmetc cyptogaphy fo pvacy ad a keyed message authetcato code fo message elablty. Seveal vesos of the potocols ae wdespead use applcatos such as web bowsg, electoc mal[3][4], Iteet fag, stat messagg ad voce-ove-ip (VoIP).TLS s a IETF stadads tack potocol, last updated FC 5246 ad s based o the eale SSL specfcatos developed by Netscape *the coespodg autho. The wok s suppoted by: The atoal atual scece Foudato ( ) Copoato[5][6][7]. The TLS potocol allows clet/seve applcatos to commucate acoss a etwok a way desged to pevet eavesdoppg ad tampeg.a TLS clet ad seve egotate a stateful coecto by usg a hadshakg pocedue. Dug ths hadshake, the clet ad seve agee o vaous paametes used to establsh the coecto's secuty[8][9][0]. Cloud computg efes to the povso of computatoal esouces o demad va a compute etwok. I the tadtoal model of computg, both data ad softwae ae fully cotaed o the use's compute cloud computg, the use's compute may cota almost o softwae o data (pehaps a mmal opeatg system ad web bowse oly), sevg as lttle moe tha a dsplay temal fo pocesses occug o a etwok of computes fa away[][2]. A commo shothad fo a povde's cloud computg sevce (o eve a aggegato of all estg cloud sevces) s "The Cloud". The most commo aalogy to epla cloud computg s that of publc utltes such as electcty, gas, ad wate. Just as cetalzed ad stadadzed utltes fee dvduals fom the vagaes of geeatg the ow electcty o pumpg the ow wate, cloud computg fees the use fom havg to deal wth the physcal, hadwae aspects of a compute o the moe mudae softwae mateace tasks of possessg a physcal compute the home o offce. Istead they use a shae of a vast etwok of computes, eapg ecoomes of scale [3][4]. Gd computg s a tem efeg to the combato of compute esouces fom multple admstatve domas to each a commo goal. The gd ca be thought of as a dstbuted system wth o-teactve wokloads that volve a lage umbe of fles. What 20 ACADEMY PUBLISHE do:0.4304/jw

2 640 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE 20 dstgushes gd computg fom covetoal hgh pefomace computg systems such as cluste computg s that gds ted to be moe loosely coupled, heteogeeous, ad geogaphcally dspesed. Although a gd ca be dedcated to a specalzed applcato, t s moe commo that a sgle gd wll be used fo a vaety of dffeet puposes. Gds ae ofte costucted wth the ad of geeal-pupose gd softwae lbaes kow as mddle wae[5][6]. Tusted Computg (TC) s a techology developed ad pomoted by the Tusted Computg Goup.The tem s take fom the feld of tusted systems ad has a specalzed meag. Wth Tusted Computg, the compute wll cosstetly behave epected ways, ad those behavos wll be efoced by hadwae ad softwae. I pactce, Tusted Computg uses cyptogaphy to help efoce a selected behavo. The ma fuctoalty of TC s to allow someoe else to vefy that oly authozed code us o a system. Ths authozato coves tal bootg ad keel ad may also cove applcatos ad vaous scpts. Just by tself TC does ot potect agast attacks that eplot secuty vuleabltes toduced by pogammg bugs[7][8]. Fgue. Gd dstbuted paallel authetcato model II. GID DISTIBUTED PAALLEL AUTHENTICATION MODEL If the gd etty A wat to tact wth gd etty B a cloud,the gd etty A wll fst go to gd ettes heustc tusted quey, ths pocess eed to calculate tusted value gd doma ad out of gd doma at the othe had t eed to compute the gd etty adaptve authetcato. If the vefy behavo each ts gate value the fomato wll be set to the decso module besdes the fomato of gd etty adaptve authetcato, the the decso module wll gve the compehesve fomato of the tusted value of gd B fo A. Dug the pocess gd B wll teact wth gd etty adaptve authetcato module to gve suffcet fomato o else t wll be ejected. III. ADAPTIVE GID AUTHENTICATION VEIFY FAME Adaptve gd authetcato vefes ca ealze sgal self- detecto ad self-adjustg. [9] The adaptve geeato talzato wth the poducto of cotuous o temttet output wth automatc ecogto ad adjustmet fucto of the geeate sgal, though the desg of efeece models o selftug cotolle module ca be acheved o the output o eceved sgal eal-tme adjustmet ad dyamc match. Adaptve ecypto cotol pcple s as Fgue 2.Fst tatve the clock module ad the clock stmulus module as a self-efeece model, sce the self-efeece model wll ecostuct whe the detectve sgal eceved fom the self-detecto module does ot match, ad the ecostucted efeece model s ot depedet o eteal stmulato, whch depeds oly o the tal algothmts. Ths meas that as log as both ecypto ad decypto have the same efeece model, afte the same talzato, they ca always get sychoous cotol sgal. Fo eample, the use of the two CMOS 8 k 0 / S ut ca keep output sychosm at.take the output sgal fom the self-efeece model as the fst stage paamete of chaos cascade module, the output sgal of the fst stage of chaotc module as the put 20 ACADEMY PUBLISHE

3 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE sgal of self-tug module ad at the same tme, as the put sgal of the secod stage Logstc geeato the output sgal of the secod stage Logstc geeato as the put sgal of the thd stage o put sgal of key geeato the output sgal of the thd stage ad key k togethe as the tal key of key geeato.the selfdetecto module cossts of two detectos, whch ae esposble fo addg state value w to the platet ad testg ecypted state value w c ad chael feedback state value w. Whe the ecypted value ad the c chael feedback state values ae abomal, feedback should be doe to the efeece model, the the selfefeece model wll update wth a ew efeece model accodg to the cuet state value of tal algothm, thus to update all the output sgals of chaotc module, key geeatos wll also update ew key steam wthout chagg of key k.the eceve uses the decode to etu w c to the sede fst to cofm the acceptace of the c cphe, at the same tme offes w evaluato to the sede fo the chael safety de testg thus to deteme whethe thee s eed to esed the cphe o eew the efeece model. Fgue 2. Adaptve gd authetcato method IV. HEUISTIC CODE GENEATO AND HEUISTIC BEHAVIO TUST QUEY FUNCTION A. Stuctue of heustc code geeato Supposed that the gd etty have some shape volume ad weght[20], the legth of gd etty s L, the wdth W ad the heght H, the decto of the layes vay fom each othe due to dffeet posto of gd etty, ad the, y, z metoed above coespodgly epesets dffeet value[2]. If the gd etty s located behd of gd doma, the equals to W, y equals to H, ad z equals to L, whch meas the decto of the laye s alog wth the legth of etty. If the gd etty s located the sde of compatmet, the equals to L, y equals to H, z equals to W, ad the decto of the laye s alog wth the wdth of compatmet. If thee ae two ettess set espectvely behd ad sde of the gd, the equals to W, y equals to L, z equals to H, ad the decto of the laye s alog wth the heght of gd. Call the best laye loadg pogam ad the plae optmal layout pogam to solve these ad the specfc steps ae as follows: () ete the gd etty sze L, W, H, the gdgo bo sze s, s 2, ad s 3 (make s s 2 s 3 ). Assg, y, z wth L, W, H accodg to the posto of the gd etty (2) call the best laye loadg pogam to compute a, b, c (3) Calculate the optmal layout of each laye: If a 0, make sm = s2, s = s3, call the plae optmal layout pogam geeato ( s2, s 3) 2 If b 0, make sm = s, s = s3, call the plae optmal layout pogam geeato ( s, s 3) 3 If c 0, make sm = s, s = s2, call the plae optmal layout pogam geeato ( s, s 2) (4) Calculate the total umbe of the loadg cotae Sum= a*geeato ( s2, s 3) + b*geeato ( s, s 3) + c*geeato( s, s 2) (5) Output Sum, a, b, c, ad the coespodg values of the paametes of the layout. Gve a gd gd ettyset C, C={,2,,}, the set C 0 ={0} deotes the gd d s the tusted value betwee 20 ACADEMY PUBLISHE

4 642 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE 20 abtay two odes, j C ad C 0 q ( =,, ) s the demad of the gd w s the mamum of the tusted capablty of, s the umbe of the gd etty that eeds to fsh the vetty, whch s = q / w, = () s the ouded up fucto, such as 6.2 = 7 (=,,, ad j=0,,, ad whee ot equals to j) s the decso vaables, oly f the oute pass the ac(, j), othewse = f ad =0 y ((=,,, =,, ) s the demad of the gd whch meets by the oute S deotes the gd set seved by the oute, S deotes the umbe of gd cluded S. Thee ae some assumptos of the model: () the tusted values betwee two odes s symmetc, d = d j (2) the tusted values of the odes satsfy the tagula d + d > d equalty, whch s k kj (3) all the gd etty stat fom the gd ad back to gd afte each delvey (4) evey gd s eeds must be satsfed ad ca be doe by oe o moe gd etty. The objectve of ths poblem s to aage the oute to mmze the cost of delvey. The cost s epeseted by the total tavellg tusted value. As the descpto above, the poblem ca be modeled as: m (2) d = = 0 j = 0 k kj = 0 j= 0 = k = 0,, =,, = = 0 = s j s = j = 0,, y = q =,, { } = S =,, S C 0 y w =,, q y =,, =,, j = 0 (8) {0,}, j =,, =,, (9) q y 0 =,, =,, (0) The costat (2) s to mmze the total tavellg tusted value costat (3) meas the flow cosevato, that s, the umbe of gd etty s equal betwee eteg ad etg of a ode Costat (4) ad (5) esue that each ode s vsted at least oe tme ad the equemet s satsfed (6) shows that the edges betwee seved gd s equals to the umbe of seved gd s mus (3) (4) (5) (6) (7) each oute, (7) shows thetuseted capablty of gd (8) shows that the gd s seved oly the gd pass. Compute : put, y, s m, s Compute 2: deteme whethe the gd A ad B ca be tusted ts doma, etu 0 f ot. Compute 3: fo ( y = y/2 s y y/ s y++ ) { fo ( = /2 sm / sm ++ ) {talze 5 5 0, usg = = 0 j = 0 k = 0 j= 0 = s = y = ad compute 2 y 4 d ad = kj k = 0,, =,, If ( sy / y/ sm sm ) { y 2 = y/ s m 3 = y3 = 0 Compute 4 y = q =,, } else { y 2 = sy / sm Compute y 3 usg = S =,, S C { 0} j s usg If ( s / /2 2 sm s 2 sm > sm ) { compute usg q y 0 =,, =,,.} 3, 4 = j = 0 Else { compute 3, 4 usg y w =,, y = q =,, ad = If( sm3 s4 > s){ compute 5, y 5 usg q y =,, =,, ad {0,}, j =,, =,, } } } Compute the total umbe of y + y + y + y + y. geeato= Compae ad ecod the geeato umbe ad the ageemet method. } } Compute 4:Output the optmzed esult. We ca also have 5 = ( sm 3 s 4 )/ s y5 = ( y smy2)/ sm. The objectve fucto s y + y + y + y + y. Whe s / /2 2 sm s 2 sm > sm, geeato= ACADEMY PUBLISHE

5 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE / 3 = s2 sm + 4 = ( sm3)/ s, The objectve fucto s geeato= y + 2 y y y 4. So such vefy model, the paametes ca be solved as log as ad y ae kow. The age of, y ae 0 s / m ad 0 y y/ s, whch becomes to /2 sm / sm ad y/2 s y y/ s o cosdeg the symmety of vefy model 4. The objectve optmzato value ca be foud afte the tavesal of all the combatos of, y. B. k-meas heustc behavo tust quey fucto I may pactcal applcatos, the k-meas clusteg algothm (k-meas algothm) whch s based o patto clusteg has bee pove to be effectve ad geeate good esults[22][23]. The steps of a geeal k- meas algothm ae: Select k couples of tal cluste cete Assg sample whch eed to be classfed to some cluste cete oe by oe accodg to the mmum tusted value pcple Calculate ew value of evey cluste cete. Geeally the ew cluste cete s the mea vecto of the sample cotaed the cluste feld. The mea vecto of the sample k couples of cluste eed to be calculated espectvely. eclassfy the sample ad epeat teato. The algothm coveges whe evey cluste cete o loge moves, the calculato fshes. The pcple of k-meas algothm s to fd k couples of patto wth a least squae eo ad make the geeated esult as compact ad sepaate as possble. The k-mea algothm s elatvely scalable ad effcet dealg wth lage data sets ad the complety s O( kt ), whch meas the umbe of objects, k s the umbe of cluste, ad t s the umbe of teatos. The case maly dscussed ths pape s that the demad of gd may be geate tha the mamum tusted capacty of gd etty. Hece, t s po to meet each gd wholly, ad the mege the emag pat to othe gd to meet. Net the pcple dscussed s used to cluste the gd ettes ad deteme the gd s seved by the same gd. Howeve, the SDVP s a costat clusteg poblem, the calculato may ot covege, so the umbe of teatos N eeds to be set to temate focbly ad set the clusteg evaluato ctea to select bette clusteg esults. The clusteg evaluato fucto used ths pape s: M( sumd) = d, j= Cj C j epesets cluste j. The fomula above calculates the sum of tusted value betwee evey gd etty ad the cete the cluste. Select the mmum sum as the best clusteg esult. The cocete steps ae below: Step : Fd the gd etty whose demad s geate tha o equal to the tusted capacty of gd. Splt the s c demad q to two pats q ad q, ad s q = w q / w c q = q w q / w meas to oud dow, fo eample 6.6 = 6. s The demad of q s dvdually met ad the emaed c demad q ad the othe etty ae meged to some othe ccut to meet. Modfy the demad of the gd to be q c Step 2: adomly select couples of tal cluste cete,, fom the gd set C =, 2,,, ad mak as set P =,,. Italze evey cluste set C = Φ ( =,, ), ad set the value of the mamum umbe of teatos N Step 3: Cluste the gd s. Calculate the tusted value d betwee evey gd etty ad evey cluste cete, ad fd the eaest cluste cete of evey gd etty. The eae the tusted value s, the hghe poty the gd etty has to jo the cete. If the cluste wated to jo s full loaded, the choose the secod eaest. Whe thee s stll emag demad the cluste, ad f the addg of the demad make the total demad of cluste C j eceed W ( QC j > W ), compute the umet demad of gd, whch s deoted by S, ad tasmt the umet demad to othe gd of C j. The tasmsso pcple s: fstly fd the gd etty (clude gd ) whose demad s ot less tha S cluste C j, the fd the cluste whose esdual demad SuQz = W QCz S( z P j). Compute the tusted value betwee these gd ettys ad these clustes ad choose the gd etty wth smallest tusted value to splt. Guess the gd etty k ad ts coespodg cluste cete p, add k to cluste C p ad the umet demad S s met by ths oute. If the esdual demad of all clustes SuQz < S, the select the cluste wth lagest esdual demad to jo utl S s fully met. epeat ths step utl all the gd s demads ae met. Step 4: Calculate the sum of the tusted value betwee evey clusteg gd etty ad ts cluste cete SumD Step 5: Use the followg way to adjust the cluste cete ad get the ew 2 2. The coodate posto of the cluste cete,, 2 j ( j =,, ) s =, y = y, 2 2 j j C y C Whee s the umbe of gd etty C Step 6: epeat Step 3-5 utl each the mamum teato umbe N. Output the clusteg esults coespodg to the mmum value of sumd Step 7: Optmze the esult of step 6 by smulated aealg algothm. The cool way 20 ACADEMY PUBLISHE

6 644 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE 20 s Tt ( + ) = k Tt ( ). I the fomula k s a postve costat slghtly less tha.00 ad t s the tmes of coolg. I step, the stuato that the gd demad s geate tha the tusted capacty of gd s cosdeed. I step 2 to 6, cluste the gd s eed to, ad fd the optmal clusteg soluto. I step 7, the oute optmzato s doe fo solvg TSP poblem. The clusteg pocess s: () adom deteme (obtaed fom fomula ()) couples of cluste cete (2) Calculate the tusted value betwee evey gd etty ad evey cluste cete d ( =,, j =,, ). Sot d ( j =,, ) fom small to lage ad fd the smallest tusted value fom evey gd etty to the cluste cete. (3) If the smallest tusted value d kp s foud, the the coespodg gd k s added to cluste p, ad add the gd coespodg to the secod smallest value to the coespodg cluste, compute the esdual demad SuQ (that s, the capacty of gdage mus the amout of gd mouted) of the cluste ad tu dow. Whe the esdual demad of cluste s less tha the demad the gd s wat to add, the splt ettes ae selected to splt cluste. The pcple of splt etty selecto wll be dscussed late. (4) Whe the total demad of the cluste that the gd s wat to jo has eached the mamumtuseted capacty of gd etty, the secod eaest cluste wll be cosdeed. Tu dow utl all gd s ae added to a cluste. I ode to esue the load facto ad the least equemet of gd etty, the gd s eed s allowed to splt, so the pcple of gd choce splttg should be cosdeed. If gd s added to a cluste p whch s ot fully loaded, whch makes the total demad of the cluste eceeds the mamum tusted capacty of gd etty, the demad eeds to be splt to meet. If the secod eaest cluste cete s fa away fom the gd, the taffc tusted values cease geatly. The umet demad wll be allowed to tasmt to a etty whose demad s geate tha the umet demad of gd cluste p ad whch s elatvely close to the othe cluste whose esdual demad should be geate tha the umet demad of gd, to make the demad of ths etty splt meet. The demad of gd s totally met by cluste p. If the esdual demad of all clustes s lowe tha the umet demad of gd, the choose the oe wth the mamum esdual demad to jo to avod beg splt too may tmes. V. COMPAISON OF THE TEST ESULTS OF TLS AND SSL AUTHENTICATION POTOCOL AND THE NEW GID AUTHENTICATION METHOD We set the clouds as a pool wth hudeds of computes ad thee ae may gd ettes that caot be tusted o should be lmted fo tact, the we set some etty to sed the equest to othe gds to compute o calculate some fomato togethe, so evey gd the clouds wll go to the TLS\SSL model ad ou ew model usg dstbuted paallel authetcato model based o tusted computg, the we emde the accuacy ad lead tme of all the model. Fom the table ad table2 we ca see that the accuacy ate of SSL&TLS authetcato s lowe tha dstbuted paallel authetcato model, the lead tme of SSL&TLS authetcato s loge tha dstbuted paallel authetcato model. I table3 we wll show the detal compehesve mpovemet fo dffeet clouds ad dffeet teet evomet. TABLE I. ACCUACY ATE OF SSL&TLS AUTHENTICATION AND THE LEAD TIME Epemet Accuacy TLS SSL TIME(ms) de ate(km) TIME(ms) Ave TABLE II. THE ACCUACY ATE AND LEAD TIME FO USING DISTIBUTED PAALLEL AUTHENTICATION MODEL Epemet de Accuacy ate Computato tme(s) Ave Fom the table3 we ca see the compehesve evaluato of dstbuted paallel authetcato model s much bette tha SSL&TLS that the dstbuted paallel authetcato model use less computg opeato ad computg tmes but wth 30 hghe coect accuacy pecet ad 35.7 equal total pecet. 20 ACADEMY PUBLISHE

7 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE Authetcato TABLE III. ACCUACY ATE OF SSL&TLS AUTHENTICATION AND THE LEAD TIME AUTHENTICATION MODEL AND SSL&TLS Compehesve evaluato of ou algothm Compehesve evaluato of SSL&TLS Coect tmes Computato tme(s) Coect tmes Computato tme(s) Impove-met (%) A A A A A A A B B B B B B B C C C C C C C D D D D D D D EQUAL VI. CONCLUSION Fom the above aalyss, take tusted computg as the bass, a cloud computg, gd dstbuted paallel authetcato method whch s ealzed by gd authetcato ad gd behavo smultaeous authetcato, establshed o the uppe laye of SSL ad TLS potocols, by adaptve steam cphe heustc code geeato ad heustc behavo tust quey fucto, plays well authetcato. Howeve, o the tust ssue of gd behavo, futhe stadadzato s eeded o ettes quattatve tust level wth a doma, whle the coe of the heustc algothm eeds to quatfy the gd ettes wth the shape, weght, sze ad othe physcal dcatos as a physcal etty, ths quattatve method stll eeds to be futhe mpoved, so as to pomote adaptve steam cphe authetcato famewok ad mpove the uppe tusted computg platfom. EFEENCES [] [2] The SSL Potocol: Veso 3.0Netscape's fal SSL 3.0 daft (Novembe 8, 996) [3] "SSL/TLS Detal". Mcosoft TechNet. Updated July 3, [4] Thomas Y. C. Woo, aghuam Bdgavle, Shaowe Su ad Smo S. Lam, SNP: A teface fo secue etwok pogammg Poceedgs USENIX Summe Techcal Cofeece, Jue 994 [5] Deks, T. ad E. escola. "The Taspot Laye Secuty (TLS) Potocol Veso., FC 4346". [6] Natoal Isttute of Stadads ad Techology. "Implemetato Gudace fo FIPS PUB 40-2 ad the Cyptogaphc Module Valdato Pogam". [7] Ec escola ( ). "Udestadg the TLS eegotato Attack". Educated Guesswok. g_the_tls_eegot.html. [8] McMlla, obet ( ). "Secuty Po Says New SSL Attack Ca Ht May Stes". PC Wold. [9] "SSL_CTX_set_optos SECUE_ENEGOTIATION". OpeSSL Docs [0] Vaous ( ). "IE SSL Vuleablty". Educated Guesswok. [] Sea Mastoa Zh La Subhajyot Badyopadhyaya Juheg Zhaga Aad Ghalsasb. "Cloud computg The busess pespectve". Decso Suppot Systems. [2] M. Ambust A. Fo. Gffth A.D. Joseph.H. Katz A. Kowsk G. Lee D.A. Patteso A. abk 20 ACADEMY PUBLISHE

8 646 JOUNAL OF NETWOKS, VOL. 6, NO., NOVEMBE 20 I. Stoca ad M. Zahaa. "Above the Clouds: A Bekeley Vew of cloud computg". Uvesty of Calfoa at Bekeley. 0 Apl 20. [3] "NIST.gov Compute Secuty Dvso Compute Secuty esouce Cete". Csc.st.gov. [4] "Gate Says Cloud Computg Wll Be As Ifluetal As E-busess". Gate.com [5] a b "What s the Gd? A Thee etty Checklst". [6] Duf.uf.ch. "Pevasve ad Atfcal Itellgece Goup: publcatos [Pevasve ad Atfcal Itellgece eseach Goup]". May 8, [7] Chs Mtchell, Tusted Computg, Isttuto of Electcal Egees, [8] oss Adeso, "Cyptogaphy ad Competto Polcy - Issues wth Tusted Computg ", Ecoomcs of Ifomato Secuty, fom sees Advaces Ifomato Secuty, Vol. 2, Apl, [9] Lu Lzhao, A New Adaptve SSC ad SSSC Steam Cphe Model Desg ad Implemetato [J]. Advaced Mateals eseach Joual: 20, (43), [20] Yag, H., J. Sh.: A Hybd CD/VND Algothm fo theedmesoal b packg [C]. The 2d Iteatoal Cofeece o Compute Modelg ad Smulato. IEEE Pess, Saya(200) [2] Almeda A. d., Fgueedo M.B.: A patcula appoach fo the thee-dmesoal packg poblem wth addtoal costats [J]. Computes & Opeatos eseach. 37(), (200) [22] C. Achett, A. Hetz, M.G. Speaza. A Tabu seach algothm fo the splt delvey vehcle outg poblem[j].taspotato Scece, 40, 64-73(2006) [23] C. Achett, M.W.P. Savelsbegh, M.G. Speaza. A optmzato-based heustc fo the splt delvey vehcle outg poblem [J]. Taspotato Scece, 42, 22-3(2008) Keshou Wu (975.3-), Xame cty, Fuja Povce, Cha, PhD of Huazhog uvesty of scece ad techology, majoed softwae egeeg. eseach feld: System Egeeg, Ifomato System, Data Mg, GIS. Lzhao Lu (983.3-), Xame cty, Fuja povce, Cha. PhD caddate of Xame uvesty, majoed automato, system egeeg, Ifomato Scece ad Techology Depatmet. eseach feld: chaotc modelg ad cotol of umaed aplae vehcle ad fomato system, featue attacto ad detecto, scale space ad multscale techology. He has doe the Cha atoal 985 egeeg pocess of umaed aplae vehcle fo the UAV\UAIS chaotc pheomeo aalyss, UAV\UAIS chaotc modelg ad cotol. He made the pape such as The Chaotc Chaactes ad New Cotol Stategy of Umaed Aplae Ifomato System 2008 ISCID ad Eo! efeece souce ot foud.the Chaotc Dstubace of UAV System's Commucato Ad Copg Stategy 2008 ICCCAS. He also has doe the wok of gd behavo tust model ad has the pape such as The Quattatve Assgmet of The Gd Behavo Tust Model Based o Tusted Computg 200 Wuha uvesty joual.now he s dog the wok of scale space ad multscale techology fo the mage aalyss especally fo the featue descbto defto detecto ad matchg. 20 ACADEMY PUBLISHE