Vulnerability Analysis of Electric Power Communication Network. Yucong Wu

Transcription

1 2nd Interntionl Conference on Advnces in Mechnicl Engineering nd Industril Informtics (AMEII 2016 Vulnerbility Anlysis of Electric Power Communiction Network Yucong Wu Deprtment of Telecommunictions Engineering, chool of Electricl nd Electronic Engineering, North Chin Electric Power University, Being, , Chin Keywords: Electric Power Communiction Network; Vulnerbility; Mesure of the Frgility; Chrcteristics Index Evlution Method; Business Reltive Importnt Mtrix ABTRACT. As support network of the smrt grid, the relibility of electric power communiction network hs become the prerequisites of the smrt grid to become intelligent nd economic, nd operte sfely. This pper minly studies the vulnerbility of the electric power communiction network, so s to provide strong gurntee nd support for electric power production. Vulnerbility, s n effective mesure of network relibility, cn mesure the performnce of the network under ttck or equipment filure. Here we put forwrd n nlysis method bout the vulnerbility of the electric power communiction network business lyer, bsed on the importnce of electric power business: in view of the uncertinty produced during expert evlution link in importnce evlution of trditionl electric power business, we put forwrd n objective stndrds insted of experts subjective rting business importnce evlution method, nmely chrcteristic index evlution method. Introduction With the booming of electric power technology, electric system higher the requirements on communiction security. The vulnerbilities in electric power communiction system led to incidents. In the trditionl nlysis, we use relibility index to nlyze the electric power communiction system. The relibility index only relies on the mount of known incident type, which is unble to reflect the defect of the system nd it is not conducive to improve the system. However, the evlution bsed on the concept of vulnerbility synthesize the sfety index, reflect the system security level in generl. The network vulnerbility, s n effective mesure to the system relibility, reflects decline degree of network performnce on different network unit nd point out the wek link in the network, which supports network plnning nd risk mngement. In this pper, we first stte the concept of electric power telecommuniction network nd its min business. econd, we elborte the development sttus of electric power communiction network. Then we discuss the bsic concept of the vulnerbility nd its chrcteristics. After tht we confirm the mesurement index of the vulnerbility. At lst, we put forwrd n electric power communiction network business lyer model of its vulnerbility. In this model, n electric power business importnce evlution method is proposed, in which the expert subjective rting is replced by objective indictors. It elimintes the subjective uncertinty of evlution results. Then we use business importnce s prmeters. We build the electric power communiction network model on the business lyer nd nlyze the vulnerbility of electric power communiction network in vrious link filure model. At lst, we djust the wek link in the network ccording to the results to improve the network performnce The uthors - Published by Atlntis Press 185

2 The concept of electric power communiction network Power Line Communiction, whose full nme is Power Line Crrier Communiction, is specil communiction method using high voltge power lines, medium voltge power line nd low voltge power line s informtion trnsmission medium for voice or dt trnsmission. Network vulnerbility s n effective mesure of network relibility mesures the network performnce when network is ttcked or equipment nturlly fils. It reflects vrious decline degree when different network unit fils nd point out the wek link in the network to support the network progrmming nd risk mngement. Electric power communiction business is divided to production business nd mngement business. There re lrge mount of indexes to describe network vulnerbility, such s integrity, expnsivity nd so on. In the trditionl network vulnerbility nlysis, we consider rther less on ctegories nd chrcteristics of network trnsmission business, which hs its limittion. Development of electric power communiction network Public network is lck of communiction cpcity nd develops slowly. There re vrious types of business in the public communiction network. The business with huge spn mkes it difficult to refine the network performnce index to the business lyer. As the electric communiction network specil for electric system, the demnd of improving communiction cpbility nd stisfy to meet the specil request of the electric system rises. Becuse of the specificity of the electric system, power genertion, trnsmission, substtion, power distribution is conducted t the sme time nd distribution re is very extensive. In order to resonble economic power genertion, distribution of electricity nd timely find nd del with the fults of power system, we hve to set up n electric power system for unified mngement nd need sfegurd of electric power communiction system to supervise the whole process of electric power system nd detection. These dys, electric power communiction network in Chin hs mde gret progress with the development of the power system. After yers of development, communiction institutions nd tem should hve certin scle nd to crete good cdemic tmosphere. Even so, there re still some defects in our country contrst to the big trend in the development of the globl telecommunictions nd direction of the development of electric power communiction round the world electric power communiction network t present. The network structure is wek. The min electric power communiction network structure is complex, minly tree or str structure, difficult to form roundbout circuit. Hence, it is difficult to resonble shre through the detour once the fult hppens. Communiction system is reltively bckwrd nd min circuit over term service. Mny circuits operte for ges, over the term of scrp. It is difficult to complete the integrted digitl business. Network ccess nd network mngement is wek. The current user ccess is telephone lines in generl or the nlog signl interfce. Difficult s the network mngement informtion is collected, it is hrd to form comprehensive network mngement system. The bsic concept of vulnerbility In system sfety point of view, vulnerbility refers to exist in wekness or defect in the system, system for specific thret ttck or the sensitivity of risk events nd the possibility of the thret of ttck effect. The index of vulnerbility nd other indexes hve fundmentl difference. 186

3 Generlly, system security mesures hve effectiveness, relibility clcultion nd nti-destroying bility clcultion. The relibility refers to the system's bility to fully relize some function in certin time. Vlidity refers to the system is enbled t ny time in efficient working condition. Anti-destroying bility is in view of the network topology structure relibility ssessment. Anti-destroying bility of the network node communiction is minly pointing to the sfety degree of the system under destruction. Thus, the frgility of the description ngle nd the form re different to the bove two cses. It focus on vulnerble prt of the network fter ttck, brought bout by the decline in overll performnce. Mesure of the frgility Nowdys, there is no unified definition of Frgility. Frgility which we used in the pper is the performnce decline of some nodes in the network fter ttck. Currently, the bsic prmeters of mesuring the network in the complex network theory chrcteristics re the shortest pth, clustering coefficient, degree, degree distribution nd so on. These prmeters show the chrcteristics of the network performnce from different spects. Averge distnce L. In network, the distnce between ny two nodes is defined s the shortest distnce between the two notes. We get the verge distnce from the node distnce. It reflects the verge length of informtion trnsmission between nodes in the network, 1 L= nn ( 1 Clustering coefficient C. The clustering coefficient in the network is the importnt prmeters used to evlute network node cluster. The quntity of clustering coefficient shows the degree of collectiviztion in the network, j 1 n Ci n i = 1 C = d Node degree distribution. Degree distribution effects gretly on the network trnsmission performnce of the informtion. We use P(k to indicte the percentge of number of nodes with k degree nd the ccumulte probbility of notes degree is P ( (k' cum k = P Node betweenness distribution k' k. In the network, node betweenness is the frequency if pssing the note in the shortest distnce. We use P( to indicte the percentge of number of nodes with betweenness nd the ccumulte probbility of notes betweenness is Pcum ( = P(' Generlly we use these prmeters to indicte network structure chrcteristics. However it is unble to describe the network performnce comprehensively. Currently, the index we use to evlute the network performnce is efficiency function. The efficiency index of the network G is defined s ' 187

4 1 1 1 EG ( = ε = nn ( 1 nn ( 1 d i, j Gi, j i, j Gi, j We use to indicte the communiction efficiency between two notes nd it is, inversely with the shortest distnce between the two notes. When, tht is, when there re no pth between the two notes,. The function of the communiction system is different from the electric system. Hence the nlytic ngle is not the sme. In this pper, we consider the communiction network business impct from two spects: the business trnsmission bndwidth nd connectivity. The originl efficiency function only indictes the business trnsmission bndwidth nd it doesn t involve the connectivity. Hence we will modify the efficiency function. The result is s follows: The method of clculting the shortest pth doesn t chnge. Then we clculte the totl efficiency E of the system. We get the totl business volume from the business mtrix nd clculte the shortest distnce mtrix. Of those, is the shortest distnce between note i nd j. We wipe off one dots every time we do the simultion nd count the business which loses link. Then we represent the efficiency function by E' = j, 0 In the eqution, E is the efficiency function clculted by the originl method. j, 0 E j j is the percentge of the trnsporting business, which is regrded s business connected efficiency. The efficiency fter modified not only considers the business connectivity, but lso the effect of business distribution to network trnsmission chrcteristics. When the note with more business connection fils, the vlue of j, 0 j E E nd E is smll. Chrcteristics index evlution method Business reltive importnt mtrix. Expert evlution in the trditionl electric power business importnce evlution hs strong subjectivity. Different experts grding results vry, which my led to inconsistent evlution nd ffect ll sorts of network performnce nlysis bsed on the business importnt degree. In order to eliminte the effect, we need to find objective fctors replcement for the expert subjective fctors to describe the importnt degree of ech other between the business. Different electric power business hve different requirements on the sme technicl indictors. ome indictors cnnot directly reflect the importnce of business, such s communiction bndwidth. However, some index reflects the importnt degree of business chrcteristics, such s time dely. We define the index tht cn reflect the business importnt degree s chrcteristic index, nd use it s n objective evlution fctors insted of the expert subjective fctors. Then we evlute electric power business importnce through the nlysis of the different requirements of business on the chrcteristic indexes. We select the collection of chrcteristic indexes nd for business collection mp vrious requirements of the indexes to integer field forming importnt vlue sequence,. represents the importnce vlue of business under the chrcteristic vlue. For the business requires highest on chrcteristic 188

5 ,. For the business requires lowest on chrcteristic,. is determined by difference degree of business set under the feture index, of which the vlue hs different requirements to index. We get the business reltive importnt mtrix under the chrcteristic index through the clcultion of business importnt vlue sequence, In the eqution, is whether the business importnt under chrcteristic index reltive to the business.1 = importnt, 0 = unimportnt, 0.5 = of the sme importnce s. When i=j, hs no prcticl mening nd it should be vlue tht doesn t ffect the result. According to the lgorithm, we hve in this pper. When, si( k n 1, > 1 sj( kn s ( k = 0.5, = 1 ( si( kn 0, < 1 sj( kn ( kn i n sj kn We sum up ll business reltive importnt mtrix under ll indexes in the collection of chrcteristic index nd get syntheticlly reltive importnt mtrix A, in which, N = n= 1 The evlution of business importnce. In order to void the difference between business importnt degree evlution result is too lrge or too smll. In this pper we use the liner normliztion function nd intervl mpping function to del with syntheticlly reltive importnt mtrix nd get importnt business degrees. First of ll, we sum up the row vector elements of the syntheticlly reltive importnt mtrix nd get the sum of ll the other syntheticlly reltive importnt vlue of focusing business to business, sum i Then, we select the liner normliztion function ( kn I = mx j= 1 z z f( z = z z In the eqution, z is the vrite to be normlized nd, respectively represents the mximum nd the minimum vrible in z domin,. We substitute into eqution nd get normlized importnt vlue: min min ( sum sum sum i i min i' = f( i = sum sum ( i mx ( i min After normliztion, the minimum vlue of is 0, which represents the importnce degree of the business is 0, nmely it cn be discrded, which is not resonble. Therefore, we need to mp through formul 189

6 Q= Q ( ' = '(1 X + X i i i to intervl [X,1], in which 0<X<1 nd get the resonble importnce evlution of business. When the vlue of X is too lrge, the difference of importnce degree between business is too smll nd it is difficult to distinguish vrious business. Hence, in this pper, we hve X=0.1 to define the distnce between the mximum nd minimum of importnce degree s ten times. Reference [1] Zhoxi X,Mnimrn G,Vittl V.An informtion rchitecture for future power systems nd its relibility nlysis[j].ieee Trnsctions on Power ystems,2002,17(3: [2] Brefoot C A,Entringer R,wrt H.Vulnerbility in grphs- comprtive survey [J]. Journl of Combintoril Mthemtics nd Combintoril Computing 1987(1: [3] Dinh T N,Ying Xun,Thi M T,et l.on new pproches of ssessing network vulnerbility: hrdness nd pproximtion[j]. IEEE/ACM Trnsctions on Networking,2012,20(2: [4] Vrdi Y, Zhng Cun Hui. Mesures of network vulnerbility[j]. IEEE ignl Processing Letters, 2007, 14(5: [5] Peng Wei,Li Zimu,Liu Yujing,et l.assessing the vulnerbility of network topologies under lrge-scle regionl filures[j].ieee Journl of Communictions nd Networks,2012,14(4: [6] Wng Xioling,Jing Xiohong,Pttvin A.Assessing network vulnerbility under probbilistic region filure model[c]//ieee 12th Interntionl Conference on High Performnce witching nd Routing (HPR. Crtgen, pin:ieee,2011. [7] ZHAO L, PARK K,nd LAI Y C.Attck vulnerbility of scle-free networks due to cscding brekdown[j],phys.rev.e,2004(70: