Research Article Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network

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1 e Scientific World Journal, Article ID 75257, 6 page Reearch Article Goodne-of-Fit Baed Secure Cooperative Spectrum Sening for Cognitive Radio Network Hiep Vu-Van and Inoo Koo The School of Electrical Engineering, Univerity of Ulan, San 29, Muger 2-dong, Ulan , Republic of Korea Correpondence hould be addreed to Inoo Koo; ikoo@ulan.ac.kr Received 7 March 24; Accepted 25 April 24; Publihed 8 May 24 Academic Editor: Yuxin Mao Copyright 24 H. Vu-Van and I. Koo. Thi i an open acce article ditributed under the Creative Common Attribution Licene, which permit unretricted ue, ditribution, and reproduction in any medium, provided the original work i properly cited. Cognitive radio (CR) i a promiing technology for improving uage of frequency band. Cognitive radio uer () are allowed to ue the band without interference in operation of licened uer. Reliable ening information about tatu of licened band i a prerequirement for CR network. Cooperative pectrum ening (CSS) i able to offer an improved ening reliability compared toindividualening.however,theeningperformanceofcsscanbedetroyedduetotheappearanceofomemaliciouuer. In thi paper, we propoe a goodne-of-fit (GOF) baed cooperative pectrum ening cheme to detect the diimilarity between ening information of normal and that of maliciou uer, and reject their harmful effect to CSS. The empirical CDF will be ued in GOF tet to determine the meaured ditance between ditribution of obervation ample et according to each hypothei of licened uer ignal. Further, the DS theory i ued to combine reult of multi-gof tet. The imulation reult demontrate that the propoed cheme can protect the ening proce againt the attack from maliciou uer.. Introduction Nowaday, more bandwidth and higher bit-rate have been required to meet uage demand due to an exploion in wirele communication technology. According to the Federal Communication Commiion pectrum policy tak force report [], the actual utilization of the licened pectrum varie from 5% to 8%. In ome cae, the utilization i only a mall percentage of the total capacity. Cognitive radio (CR) technology [2] ha been propoed to olve the problem of ineffective utilization of pectrum band. Both unlicened and licened uer, termed the cognitive radio uer () and primary uer (PU), repectively, operate in CRnetwork.InCRnetwork,areallowedtoacce the frequency aigned to PU when it i free. But mut vacatetheoccupiedfrequencywhenthepreenceofpui detected. Therefore, reliable detection of the PU ignal i a requirement of CR network. In order to acertain the preence of a PU, can ue one of everal common detection method, uch a matched filter, feature, and energy detection [2, 3]. Energy detection i the optimal ening method if the ha limited information about PU ignal (e.g., only the local noie power i known) [3]. In energy detection, frequency energy in the ening channel i received in a fixed bandwidth W over an obervation time window T to compare with the energy threhold and determine whether or not the channel i utilized. However, the received ignal power may fluctuate everely due to multipath fading and hadowing effect. Therefore, it i difficult to obtain reliable detection with only one. Better ening performance can be obtained by allowing ome to perform cooperative pectrum ening [4 6]. CSS can ue ome combination method uch a equal gain combination (EGC) and maximum gain combination (MGC) [7] to combine ening information of all in the network and make a global deciion about tatu of PU ignal. Since EGC give the ame weight for all in the network, it i eay to execute but with limited performance. MGC i known a the optimal combination rule. However, it require information about the SNR of the ening channel, which i difficult to obtain in practice. In addition, MGC i enitive to attack by maliciou uer who end fale ening data to the fuion center (FC) [8]. The reearch preented in [8, 9]

2 2 The Scientific World Journal determined that the preence of a few maliciou uer can everely reduce the performance of a CSS cheme. Algorithm ued to identify the maliciou uer have been propoed in the tudie of [8, 9]. In previou reearch, a imple technique (i.e., outlier-detection) i ued to detect le damage maliciou uch a alway No or alway Ye.Inaddition,thetechnique iunabletoprotectthecssintheeventofalargenumberof maliciou uer in the network. In thi paper, we utilize multi-goodne-of-fit (GOF) tet to deign a robut CSS, in which the event detection technique [, ] will be ued to provide the combination of different evidence of each type of GOF tet which are upported by a particular hypothei of PU ignal. The propoed cheme conider two type of GOF tet, Kolmogorov-Smirnov (KS) and Cramer-von Mie (CM) tet. The propoed cheme can ditinguih the ening information of normal and that of maliciou uer and reject the harmful effect of maliciou uer to ening combination proce. Three common type of maliciou uer including alway Ye, alway No, and oppoite are conidered in thi paper. 2. Background 2.. Goodne-of-Fit Tet. The GOF tet ummarize the dicrepancy between the oberved ample with theoretical ditribution or empirical ditribution and the reference ditribution. For the n independent and identical ditributed obervation, the ample i firt arranged in acending order uch that 2 n. The GOF tet i ued to determine whether or not the ample et wa drawn from the ame ditribution with a cumulative ditribution function (CDF) F. The teting hypothei can be formulated a follow: F () =F () :H o, F () =F () :H, where F() i the empirical CDF of the ample. It can be calculated a follow: F () = n n i= () I{ i }, (2) where I{ } i the indicator of event { }. There are many type of GOF tet, for intance, Cramervon Mie (CM), Kolmogorov-Smirnov (KS), AnderonDarling (AD), and Homer-Lemehow (HL) tet. In thi paper, we conider two type of GOF tet, CM and KS tet, which can run well with a low number of ample. () Kolmogorov-Smirnov (KS) tet: the KS tet, which i baedontheempiricalcdfoftheampleetand the reference CDF, can be calculated according to the larget difference of two ditribution a follow: D KS = up { F( i) F ( i ) :i=,...,n}, (3) where up{ } i upremum function, which indicate the greatet element of the et. If the ample come from ditribution F (x),thend KS will converge to. (2) Cramer-von Mie (CM) tet: CM tet i ued for judging the goodne-of-fit of the ample et CDF F() and reference ditribution CDF F (). Thetet tatitic i given by + D CM =n [F () F ()] 2 df () (4) and can be approximated a D CM = n 2n + [ 2i 2 2n F ( i )]. (5) i= If thi value, D CM, i larger than the threhold, the hypothei that the ample data come from the reference ditribution F can be rejected Combination of Evidence in Dempter-Shafer Theory. Dempter-Shafer (DS) theory wa firt introduced by Demperter and wa later extended by Shafer. Thi i a potentially valuable tool for the evaluation of rik and reliability in engineering application when it i not poible to obtain a precie meaurement from experiment or when knowledge i obtained from expert elicitation. An important apect of thi theory i the combination of evidence obtained from multiple ource and the modeling of conflict between them. In DS theory [2], a repreentation of ignorance i provided by aigning a nonzero ma function to hypothei m, alo called the baic probability aignment (BPA), and i defined for every hypothei A uch that the ma value m(a) belong to the interval [, ] and atifie the following condition: m(φ)=, m (A) =, A Ω, where Ω i the frame of dicernment, which i a fixed et of q mutually excluive and exhautive element. By aigning a nonzero ma in a compound hypothei, A Bmean that there exit the option to not make a deciion between A and B but to leave the formulation in the A Bcla. In DS theory, two function, belief (Bel) and plauibility (Pl), are defined to characterize the uncertainty and upport of certain hypothee. Bel meaure the minimum or neceary upport, wherea Pl reflect the maximum or potential upport for that hypothei [3]. Thee two meaure, derived from ma value, are defined a a map from a et of hypothee to interval [, ] a follow: Bel (A) = m (B), B A Pl (A) = A B = m (B). The um of ma function from different information ource, m j (j =,2,...M),combinedwiththeDSrulei known a the orthogonal um, which i commutative and (6) (7)

3 The Scientific World Journal 3 H H H H H H H H (a) (b) (c) (d) Figure : The CDF of received ignal energy at under abence and preence hypothei of PU ignal for (a) normal, (b) oppoite maliciou, (c) alway Ye maliciou, and (d) alway No maliciou. aociative. The reult i a new ma function, m(a k )=(m m 2 m d )(A k ), which incorporate the joint information provided by the ource a follow: m(a k )= ( m K j (A j )), A A 2 A d =A k j M K= ( m j (A j )), A A 2 A d =φ j M where K i the meaure of conflict between the different ource and i introduced a a normalization factor. 3. The Propoed Secure Cooperative Spectrum Sening Baed on GOF Tet There i a definite difference between the CDF of received ignal energy of normal and that of the maliciou uer a hown in Figure. TheCDFofthereceivedignalenergy of normal correponding to the preence of the PU i alway under that one correponding to the abence of the PU. On the contrary, the oppoite maliciou ha the CDF correponding to the preence of PU to be above the CDF correponding to the abence of PU. The alway Ye and alway No maliciou have a imilar CDF correponding to preence and abence of PU. Due to the difference between CDF of normal and maliciou, we utilize GOF tet to detect the appearance of maliciou uer in the network, o that their harmful effect can be rejected out of CSS proce. Multi-GOF tet including KS and CM tet will be applied for adaptive robut CSS. The DS theory will be ued to combine reult of multi-gof tet. In thi paper, we conider a CR network including N who cooperate to ene the ignal from a PU. There are p<nmaliciouappearinginthenetworkwhichcan be claified a three common type: alway Ye, alway No, and oppoite maliciou. All ue energy detector to perform pectrum ening and end their ening data tothefcthroughacontrolchannel.baedontheening data obtained from the, the FC make a global deciion concerningthepreenceorabenceofthepuignalbyuing (8) the propoed data fuion cheme. The propoed cheme ha 3 tep a follow. Step. All perform pectrum ening by uing energy detection method to determine received ignal energy E j = {e,j,e 2,j,...,e M,j },wherem ithenumberofeningample that the jth take in the ening interval. Step 2. At the FC, GOF tet tatitic of each will be computed according to hypothei of the PU a given in (). After that, BPA and final BPA for current ening data will be etimated baed on the reputation level of each, which i updated from previou ening interval. Baed on final BPA, a global deciion rule will be propoed to make global deciion abouttatuofpuignal. Step 3. Update reputation level of each according to the global deciion. The detailed decription of each tep will be given in the following ubection. 3.. Energy Detection. At the ening interval for the jth, the local pectrum ening i to decide between the two following hypothee: H : j (k) =n j (k), H : j (k) =h j p (k) +n j (k), where H and H correpond to the hypothei of the abence andpreenceofthepuignal,repectively,h j denote the amplitude gain of the channel, (k) i the ignal tranmitted from the PU, n j (k) i the additive white Gauian noie, and k i index of ening ample at each ening interval. A received ignal energy of a ening ample, e k,j,igiven a e k,j ={ n 2 j (k), H h 2 j (k) +n j (k), H. (9) () 3.2. BPA Etimation. The GOF tet tatitic of the current ening data e k,j (k =,...,M) of the jth will be

4 4 The Scientific World Journal Table : Reputation range according to each type of. Statu of PU Normal Alway Ye Alway No Oppoite H D t,j Dt,j Dt,j Dt,j D t,j Dt,j D t,j Dt,j D t,j Dt,j D t,j Dt,j r t,j (i) rt,j (i) rt,j (i) rt,j (i) H D t,j Dt,j Dt,j Dt,j D t,j Dt,j D t,j Dt,j D t,j Dt,j D t,j Dt,j r t,j (i) rt,j (i) rt,j (i) rt,j (i) calculated according to each hypothei of PU ignal baed on (3) and(5) a follow, repectively: D KS h,j = up { F(e k,j) F h (e k,j ) :k=,2,...,m}, D CM h,j = M 2M + [ 2i 2 2M F h (e k,j )], i= () where h={,}i index of hypothei H h of PU ignal, e k,j i thereceivedignalenergyofkth ening ample of the jth, F( ) and F h ( ) are empirical CDF of oberved ening ample and CDF of H h hypothei of PU, and M i the number of ample for each ening interval. It i noteworthy that normal and maliciou have different characteritic of D t,j and Dt,j a hown in Table, where t indexe type of GOF tet: KS and CM. Baed on the value of D t,j and Dt,j,wewilletimateBPA of current ening data of each and their reputation level for robut CSS a follow: D t,j Δ t,j = D,j t R t +Dt,j,,j (2) Δ t,j = D t,j D,j t R t +Dt,j,,j where R t h,j i reputation level ofthejth according to hypothei h, and it can be determined baed on hitory obervation of the jth a follow: R t h,j (i) = rt h,j (i ) j r t (3) h,j (i ), Ye and r t,j of alway No maliciou are almot negative andtendtodecreaeafterupdatingtep.ontheotherhand, both value of oppoite are negative and have a tendency to decreae. We define maliciou threhold aρ to reject the attack of maliciou CR in CSS, o that the, which ha either r t,j <or rt,j <, will be determined a maliciou. The ening data of maliciou will not be conidered to make global deciion by giving them r t,j =and rt,j =. The BPA of all will be combined with their reputation level a Δ t = n Ω D,j t R t +Dt,j,,j j Ω D t,j (6) Δ t = D t,j n Ω D,j t R t +Dt,j,,j j Ω where Ω and n Ω are et of normal and number of member of the et, repectively. BecauetheerrorinetimatingΔ t and Δt, Δt +Δt can be bigger than, we need to normalize thoe value a Δ t = Δ t Δ t, +Δt Δ t = Δ t Δ t. +Δt (7) 3.3. DS Theory Combination. The DS theory will be ued to combine the BPA of both GOF tet according to each hypothei a follow: Δ =Δ KS Δ KS = (Δ KS +Δ KS ), Δ =Δ KS = Δ KS (Δ KS +Δ KS ). Finally,theglobaldeciionwillbemadeafollow: (8) where i i the index of current ening interval and r t,j (i ) and r t,j (i ) areupdatedfromtheprevioueninginterval according to global deciion: G=H, if Δ η, Δ G=H, otherwie, (9) r t,j (i ) =rt,j (i 2) +(Dt,j (i ) Dt,j (i )), (4) r t,j (i ) =rt,j (i 2) +(Dt,j (i ) Dt,j (i )). (5) By uing r t,j and rt,j, type of will be eaily ditinguihed. The normal ha poitive value of both r t,j and r t,j that will be increaed after updating tep. rt,j of alway where η i the threhold for global deciion. According to the global deciion, r t,j or rt,j will be updated for the next ening interval a follow, repectively. (i) If the global deciion i G(i) =,weupdater t,j (i) by uing (4). (ii) Otherwie, we update r t,j (i) by uing (5).

5 The Scientific World Journal The propoed cheme ECG cheme MGC cheme Probability of fale alarm The propoed cheme ECG cheme MGC cheme Probability of fale alarm Figure 2: ROC of the propoed cheme and reference cheme when no maliciou i conidered. Figure 4: ROC of the propoed cheme and reference cheme when 4 alway Ye maliciou are conidered Probability of fale alarm The propoed cheme ECG cheme MGC cheme Figure 3: ROC of the propoed cheme and reference cheme when 4 alway No maliciou are conidered The propoed cheme ECG cheme MGC cheme Probability of fale alarm Figure 5: ROC of the propoed cheme and reference cheme when 4 oppoite maliciou are conidered. 4. Simulation Reult In thi ection, imulation reult of the propoed cheme and other oft combination cheme uch a maximum gain combination (MGC) and equal gain combination (EGC) are provided. The network i conidered in which 5 exit and omeofthemcanbemaliciou. In order to verify the reliability of the propoed combination cheme, we perform a imulation without conidering maliciou. The ening reult in Figure 2 how that the propoed cheme can obtain better ening performance in comparion with EGC cheme and obtain a imilar ening performance to that of the MGC cheme when no maliciou i conidered. The robutne of the propoed cheme will be invetigatedinthenetworkwiththeappearanceofalway No, alway Ye, and oppoite maliciou in the network. Figure 3 and 4 how performance of the propoed cheme when 4 are alway No or alway Ye maliciou among 5 in the network. The reult how that the propoed cheme with all can achieve much better ening performance than thatoneofthemgcandegccheme.thimeanthat,by applying GOF tet to CSS, the propoed cheme can detect the preence of thoe type of maliciou and reject their harmful effect to ening proce. Oppoite maliciou caue the mot damage to ening performance. However, the propoed cheme i expected to protect CSS againt thi type of maliciou. Figure 5 how the ening performance of the network when 4 are oppoite maliciou among 5.MGC and EGC with all provide very low performance due to the attack of oppoite maliciou.however,thepropoedchemecan defend their attack and achieve high ening performance.

6 6 The Scientific World Journal 5. Concluion In thi paper, multi-gof tet are propoed to meaure the difference between ening data of normal and that of maliciou. Further, the DS theory i ued to combine reult of multi-gof tet. The propoed cheme conider the appearance of the mot common type of maliciou : alway Ye, alway No, and oppoite type. The imulation reult prove that the propoed cheme can reject almot harmful effect from thoe maliciou to protect CSS. Conflict of Interet The author declare that there i no conflict of interet regarding the publication of thi paper. of the 53rd IEEE Global Communication Conference (GLOBE- COM ), pp. 5, December 2. [] X. Zheng, J. Wang, Q. Wu, and J. Chen, Cooperative pectrum ening algorithm baed on Dempter-Shafer theory, in Proceeding of the th IEEE Singapore International Conference on Communication Sytem (ICCS 8),pp.28 22,November 28. [2] N. Nguyen-Thanh and I. Koo, Empirical ditribution-baed event detection in wirele enor network: an approach baed on evidence theory, IEEE Senor Journal, vol. 2, no. 6, pp , 22. [3] K. Sentz and S. Feron, Combination of evidence in Dempter- Shafer theory, Sandia Report SAND22-835, Sandia National Laboratorie, Albuquerque, NM, USA, 22. Acknowledgment Thi work wa upported by the KRF funded by the MEST (NRF-22RAA23883). Reference [] Federal Communication Commiion, Spectrum policy tak force, Tech. Rep. 2-35, ET Docket, 22. [2] Y. Hur, J. Park, W. Woo et al., A wideband analog Multi- Reolution Spectrum Sening (MRSS) technique for cognitive radio (CR) ytem, in Proceeding of the IEEE International Sympoium on Circuit and Sytem (ISCAS 6),pp , Iland of Ko, Greece, May 26. [3] A. Sahai, N. Hoven, and R. Tandra, Some fundamental limit on cognitive radio, in Proceeding of the Allerton Conference on Communication, Control, and Computing, Monticello,Va, USA, 24. [4] G. Ganean and Y. Li, Cooperative pectrum ening in cognitive radio network, in Proceeding of the t IEEE International Sympoium on New Frontier in Dynamic Spectrum Acce Network (DySPAN 5), pp.37 43,Baltimore,Md,USA, November 25. [5]S.M.Mihra,A.Sahai,andR.W.Broderen, Cooperative ening among cognitive radio, in Proceeding of the IEEE International Conference on Communication (ICC 6), vol.5, pp ,July26. [6] R. Deng, J. Chen, C. Yuen, P. Cheng, and Y. Sun, Energyefficient cooperative pectrum ening by optimal cheduling in enor-aided cognitive radio network, IEEE Tranaction on Vehicular Technology,vol.6,no.2,pp ,22. [7] J. Ma and Y. Li, Soft combination and detection for cooperative pectrum ening in cognitive radio network, in Proceeding of the 5th Annual IEEE Global Telecommunication Conference (GLOBECOM 7),pp ,November27. [8] P. Kaligineedi, M. Khabbazian, and V. K. Bhargava, Secure cooperative ening technique for cognitive radio ytem, in Proceeding of the IEEE International Conference on Communication (ICC 8), pp , May 28. [9] P. Kaligineedi, M. Khabbazian, and V. K. Bhargava, Maliciou uer detection in a cognitive radio cooperative ening ytem, IEEE Tranaction on Wirele Communication,vol.9,no.8,pp , 2. [] J. Li, J. Liu, and K. Long, Reliable cooperative pectrum ening algorithm baed on Dempter-Shafer theory, in Proceeding

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