A new anonymity-based protocol preserving privacy based cloud environment

Transcription

1 Abstract A new anonymty-based protocol preservng prvacy based cloud envronment Jan Wang 1*, Le Wang 2 1 College of Computer and Informaton Engneerng, Henan Unversty of Economcs and Law, Chna 2 SIAS Internatonal Unversty Zhengzhou, Chna Receved 1 March 2014, Wth the development of cloud computng applcaton, more and more people would lke to do busness under ths envronment. But more attenton should be pad to the dsclosure of prvacy durng the transacton. Customers wll reject to do busness on the cloud platform f the cloud envronment cannot avod dsclosng ther prvate data. Nowadays, lttle work has been done about how to prevent senstve attrbutes leakng between servce provders. Therefore, ths paper proposed a new anonymty-based protocol to protect prvacy. Keywords: anonymty, cloud computng, prvacy preservng, senstve attrbutes, protocol 1 Introducton Cloud computng rases a range of mportant prvacy ssues as acknowledged by a number of recent work [1]. Such ssues are due to the fact that, n the cloud, users' data and applcatons resde on the cloud cluster whch s owned and mantaned by a thrd party [2]. Concerns arse snce n the cloud t s not clear to ndvduals why ther personal nformaton s requested or how t wll be used or passed on to other partes [3, 4]. Despte ncreased awareness of the prvacy ssues n the cloud, lttle work has been done n ths space. Recently, Pearson et al. has proposed accountablty mechansms to address prvacy concerns of end users [5] and then develop a smple soluton, a prvacy manager, relyng on obfuscaton technques [6]. Ther basc dea s that the user's prvate data s sent to the cloud n an encrypted form, and the processng s done on the encrypted data. The output of the processng s de-obfuscated by the prvacy manager to reveal the correct result. However, the prvacy manager provdes only lmted features n that t does not guarantee protecton once the data s beng dsclosed [7-9]. There are many servce provders n the cloud, we can call each servce as a cloud, each cloud servce wll exchange data wth other cloud, when the data s exchanged between the clouds, and there exsts the problem of dsclosure of prvacy [10]. So my research ams at avodng the dsclosure of the senstve attrbutes of users when user ask for servce from the servce provder n cloud computng. 2 Related work There are some prvacy problems we want to address n the cloud computng [11]: The frst problem s the dsclosure of senstve prvate nformaton when exchangng data through the cloud servce. And the senstve prvate nformaton ncludes: personally dentfable nformaton, usage data, unque devce denttes and so on [12]. The second problem s that people gettng napproprate or unauthorzed access to personal data n the cloud by takng advantage of certan vulnerabltes, such as lack of access control enforcement, securty holes and so on [13]. The thrd problem s that: because the feature of cloud computng s that t s a dynamc envronment, n that servce nteractons can be created n a more dynamc way than tradtonal e-commerce scenaros [14]. Servces can potentally be aggregated and changed dynamcally by servce provders can change the provsonng of servces. In such scenaros, personal senstve data may move around wthn an organzaton or across organzatonal boundares, so adequate protecton of ths nformaton must be mantaned despte the changes. So desgn the method to protect the prvacy n cloud computng must meet the dynamcal exchange of data. Nowadays, some researchers focus on cloud data storage securty n cloud computng [15]. And other researchers focus on the dsclosure of senstve prvate nformaton when exchangng data through the cloud computng [16]. Some researchers use dentty technology to solve these prvacy problems n cloud computng [17]. They propose some requrements for dentty servces [18]. For * Correspondng author e-mal: goodjan121@126.com 139

2 example, the dentty servces should be ndependent of devces; should permt a sngle sgn-on to thousands of dfferent onlne servces; should allow pseudonyms and multple dscrete denttes to protect user prvacy; should be nteroperable, based on open standards, and should be transparent and audtable. When create an dentty management nfrastructure n the cloud computng, we should consder: 1) There are already a number of dentty management systems n place on a wde varety of platforms. These need to be supported by the dentty management nfrastructure. The nfrastructure must support crosssystem nteracton as well as nteroperaton and delegaton between them. Ths s only possble f the nfrastructure and the ndvdual systems are based on open standards, avalable on all platforms. 2) Identty management systems wll support a wde varety of prvacy and securty propertes, rangng from low-securty password-based one-factor authentcaton to hgh-end, attrbute-based systems deployng state-of-theart prvacy-enhancng certfcates. Whle the nfrastructure needs to support all of these systems, users should understand the mplcatons of usng one system over the other [19]. 3 Anonymty-based method Our paper proposed a new anonymty protocol for the cloud computng servces. Before the mcro data are publshed, ths anonymty algorthm wll process these data. And then send these anonymous data to servce provders n the cloud. Then the servce provder can ntegrate the auxlary nformaton (also called external knowledge, background knowledge, or sde nformaton that the servce provder can get from other channels such as the web, publc records, or doman knowledge) to analyse the anonymous data n order to mne the knowledge they want. For example, the traffc management board of a regon collects records of road accdents for research and analyss. Suppose each record has fve attrbutes, namely occupaton, age, vehcle-type, postcode, and faulty. Consder the tuples n Table 1. The traffc management board anonymsed the traffc accdent records on attrbutes age, vehcle-type, and postcode before the data can be released to the servce provder n the cloud. Suppose 2-anonymty s requred. Table 2 shows a 2-anonymous release of the records wth respect to quas-dentfer (age, vehcle-type, postcode). And then the traffc management board anonymsed the traffc accdent records on attrbutes occupaton, age, and postcode. Agan, suppose 2-anonymty s requred. Table 3 shows a 2-anonymous release of the records wth respect to quas-dentfer (occupaton, age, postcode). Suppose one servce provder n the cloud obtans both releases n Tables 2 and 3. By comparng the two tables, the servce provder mmedately knows that a famly doctor of age 30 drvng a whte Sedan lvng n area was faulty n an accdent. The vctm may be easly redentfed by both these anonymous tables. TABLE 1 A set of traffc accdent record Occupaton Age Vehcle Postcode Faulty Dentst 30 Red Truck No Famly doctor 30 Whte Sedan Yes Banker 30 Green Sedan No Mortgage broker 30 Black Truck No TABLE 2 2-anonymous release of Table 1 wth respect to quasattrbutes (age, vehcle-type, postcode) Occupaton Age Vehcle Postcode Faulty Dentst 30 Truck No Famly doctor 30 Sedan Yes Banker 30 Sedan No Mortgage broker 30 Truck No TABLE 3 A 2-anonymous release of Table 1 wth respect to quasattrbutes (occupaton, age, postcode) Occupaton Age Vehcle Postcode Faulty Medcal 30 Red Truck No Medcal 30 Whte Sedan Yes Fnance 30 Green Sedan No Fnance 30 Black Truck No Besdes, when publsh anonymous data, we should consder multple quas-dentfers (QI) attrbutes for dfferent servce provders carryng dfferent background knowledge [20]. So the data publshng sde should anonymse dfferent quas-dentfers (QI) attrbutes of the records for dfferent servce provders carryng dfferent background knowledge. We can take an example to explan. Suppose the traffc management board have records of road accdents for research and analyss. Suppose each record has fve attrbutes, namely occupaton, age, vehcle-type, postcode, and faulty. And the traffc management board wants to release these records to dfferent servce provders n the cloud. Suppose there are two servce provder named "auto nsurance companes" and "human resource department" n the cloud servce. Both of them want to use the anonymous records of road accdents. Importantly, dfferent servce provders may carry dfferent background knowledge. For example, the auto nsurance company may jon the traffc accdent records wth the vehcle regstraton records on attrbutes age, vehcle-type, and postcode to fnd out whether ts customers were at fault n some accdents. Typcally, the company does not have the occupaton nformaton of ts customers, as such nformaton s not requred n applyng for auto nsurance. Therefore, to protect prvacy, the traffc management board has to anonymse the traffc accdent records on attrbutes age, vehcle-type, and postcode before the data can be released to the auto nsurance company. Smultaneously, the human resource department may jon the traffc accdent records wth the resdent records on attrbutes occupaton, age, and postcode to fnd out whch resdents were faulty n some accdents. Therefore, to protect prvacy, the traffc management board needs to anonymse the traffc accdent records on attrbutes occupaton, age, and postcode. Note that vehcle-type s 140

3 not part of the anonymsaton, because the human resource department typcally does not have nformaton about resdents' vehcle types. Our method s dfferent from the tradtonal cryptography technology to protect ndvduals prvacy n the cloud computng servces. If we use the cryptography technology. Then we should use cryptography technology to process the data, and send the processed data to servce provder n the cloud. Then ths servce provder can t use these data f t ddn t get the key of cryptography. So the servce provder n the cloud should use the key to restore the data frstly and then can use these data. However, f we use anonymty technology to process these data and send these anonymous data to servce provders n the cloud. Then the servce provder can drectly use these data wthout any key and wthout restorng these data. So ths wll be more flexble and safe to protect ndvduals prvacy n the cloud computng servces. 4 Prvate matchng protocol 5b) S encrypts each y Yc, wth S key es and sends back to C the pars <y, Fes (y)>=<fec (h (v)), Fes (Fec (h (v)))>. 6) C encrypts each y Ys, wth C s key ec, obtanng Zs=Fec (y)=fec (Fes (h (v))), here the v Vs. Also, from pars <Fec (h (v)), Fes (Fec (h (v)))> obtaned n Step 5b for the v Vc, It creats pars <v, Fes (Fec (h (v)))> by replacng Fec (h (v)) wth the correspondng v. 7) Because the Vc has only one element v (that s to say Vc has only one tuple). So f ths element v Vc meets (Fes (Fec (h (v)))) Zs, then ths v Vs. then Vs and Vc has one dentcal element, else Vs and Vc has no dentcal element. Vs and Vc has one dentcal element s equal to V V =1. s c Vs and Vc has no dentcal element s equal to V V =0. s c The man purpose for our research s to use prvate matchng technology [21] to ntersect user s data and datasets of servce provder wthout accessng each other s data, so ths can let the user check whether hs anonymous data meet k-anonymty to the datasets of servce provder, meanwhle avodng the dsclosure of each other s data. Our proposed prvate matchng protocol: 1) Both the Clent and the SP seralze the attrbutes and concatenate them to convert ther data set nto a strng of concatenated attrbute values, and produce set Vs and set Vc. Whch Vc s the set of elements (tuples) n Clent, correspondng to the attrbutes requested by the SP n the current servce request, whle Vs s the set of elements (tuples) n SP, correspondng to the attrbutes requested by the SP n the current servce request. Noton 1: Before the user n clent adds hs tuple to the table of SP, the user should check whether the one new tuple meets k-anonymty to the table of SP. So Vc =1. Because before addng one new tuple to the table of SP, the set of Vc only has one tuple to check. But Vs >=1. Because the set of Vs may have many tuples before checkng. 2) Both Clent (named C, for short) and SP (named S, for short) apply hash functon h to ther sets. Xc=h (Vc), Xs=h (Vs). Each party randomly chooses a secret key. And ec s the key for C, es s the key for S. 3) Both partes encrypt ther hashed sets: Yc=Fec (Xc)=Fec (h (Vc)), Ys=Fes (Xs)=Fes (h (Vs)). 4) C sends to S ts encrypted set Yc=Fec (h (Vc)). 5 Case studes Despte ncreased awareness of the prvacy ssues n the cloud, lttle work has been done n ths space. When users order servce n the cloud, lots of data ncludng users' attrbutes need to be transmtted between users and servce provders. How to protect users' senstve attrbutes and avod the dentfcaton by adversary s stll an mportant problem to solve. Most exstng methods are that the user s prvate data s sent to the cloud n an encrypted form [22], and the processng s done on the encrypted data. However, n ths method, the servce provder needs to decode these data before they access them. So ths wll be a waste of tme and wll be very nconvenent to servce provders. Besdes, once the data s decrypted the user s prvacy may be at rsk, snce the SP has full control of t. So our proposed approach s dfferent from tradtonal methods to avod dsclosure of ndvduals' prvacy. In our proposed approach, the datasets of servce provder meet k-anonymty. If a user wants to request a servce n the cloud, the user should anonymsed hs attrbutes correspondng to the attrbutes requested by the SP n the current servce request, then f ths user's anonymsed data meet k-anonymty to datasets of ths servce provder, ths user can send hs anonymsed data to ths servce provder. Then the servce provder wll prepare servce for ths rght user. Our proposed approach has two advantages, the frst one s the data transmtted n the cloud are anonymsed data, so f the adversary get these anonymsed data, he cannot dentfy users. The second advantage s that when servce provder gets these anonymsed data, servce provder can drectly use these data wthout restorng these data. So ths wll be more flexble and safe to protect ndvduals prvacy n the cloud. 5a) S shps to C ts set Ys=Fes (h (Vs)). 141

4 6 Avodng prvacy ndexng In order to avod the dsclosure of ndvduals prvacy n cloud, our research address that the user should send the anonymous data to servce provder (SP) n the cloud, and the datasets n SP should meet k-anonymty. The k-anonymty approach publshes a table T' whch changes the values on the quas-dentfer attrbutes so that every tuple n T s publshed n a group-by of at least k tuples on the quas-dentfer. Publshng T' nstead of T can protect prvacy effectvely aganst prvacy ndexng, snce the attacker cannot re-dentfy any ndvdual wth a confdence more than 1/k. In fact the k-anonymty approach meets the second condton of prvacy-preservng ndex (PPI) s defnton n paper [23]. Because the datasets n SP meet k-anonymty, so the datasets n SP also meet the second condton of prvacy-preservng ndex (PPI) s defnton. If an adversary wants to dentfy who satsfy the query, ths adversary executes query on the datasets of SP, then the returned results contan k users (both true postves users and false postves users are n the k users), therefore the probablty that the adversary can dentfy the real user s 1/k. So our based on k-anonymty approach lke the method n paper [23], can avod prvacy ndexng ssue. Let us take an example. If an adversary executes a query on the datasets of SP, and ths adversary wants to dentfy user s phone number (senstve attrbute) through ths query. Assume table s dataset of one servce provder, and table meets 3- anonymty. Then assume the adversary s query s on table. The query s (select phone number from table where Age=27 & Zp code= & gender=m). So the returned results wll be ( , , , ). In these results, s true postves and the other three phone numbers are false postves. So the adversary gets four dfferent phone numbers and ths adversary can t dentfy the user whose other attrbutes satsfy ths query. So executng query on these datasets whch meet k-anonymty wll avod prvacy ndexng ssue. Another reason s that the datasets n SP meet 3- anonymty, so ths query wll return at least 3 dfferent results. All of these results wll contan both true postves and false postves. Accordng to the defnton of prvacypreservng ndex (PPI) n paper [23], our proposed approach can avod prvacy ndexng ssue. 7 Securty analyss Now we use a formal proof method proposed by [24] to prove the securty of proposed protocol. Frstly we gve some defntons of the sgns used n the proof process. PD : Prvate data. PDDM : Prvacy-preservng data mnng protocol. PD : Prvate data of P. P EXT P : Extra nformaton P can obtan through the underlyng protocol. GAIN P : Advantage of P to get access to any other party s prvate data usng a protocol. GAIN SEC : Advantage of P to get access to any other party s prvate data usng a protocol by lookng at a semantcally secure cphertext whch s neglgble when usng an RSA [25] type of encrypton. Pr( PD ) : Probablty of dsclosng the prvate data PD wthout usng prvacy preservng protocol. : Level of securty. As stated n [24] that f you want to prove whether our proposed protocol named PRPT s prvacy preservng, accordng to any prvate data, you can fnd a such that: Pr( PD PDDM ) Pr( PD). So f we want to prove whether the proposed PRPT protocol s prvacy preservng, we only need to fnd such that: Pr( PD PRPT ) Pr( PD). Because the advantage of each party P j by the protocol can access another party s prvate data can be shown as: GAIN Pr( PD EXT, PRPT ) Pr( PD EXT ), Pj Pk Pj Pk Pj ( k j). Because each party P j only runs secure dot product protocol wth P j by usng hs own randomly generated vector. And party P j runs secure mult-party addton protocol [26] wth other partes by usng hs prvate output share. Therefore: GAIN Pj GAIN, ( j ). SEC Because GAIN SEC means that advantage of P j to get access to any other party s prvate data, usng a protocol by lookng at a semantcally secure [27] cphertext whch s neglgble, when usng an RSA type of encrypton. So GAIN s also neglgble. P Partcpant P j by decryptng the message receved from other partes and decryptng the sgns of ther prvate output, can only know hs prvate value of the fnal weght vector, whch s hs own fnal output. So we can conclude: max( GAIN, GAIN ) GAIN. Therefore for each conclude: P P j P j k, j 1,..., n, k j, we can Pr( PD EXT, PRPT ) Pr( PD EXT ) GAIN. Pk Pj Pk Pj P So at last we can fnd GAIN P, such that Pr( PD PRRT ) Pr( PD). Therefore, the proposed PRPT protocol s prvacy preservng. 142

5 Executon Tme(sec ) COMPUTER MODELLING & NEW TECHNOLOGIES (9) Expermental evaluaton In ths secton we desgn experments to show the applcaton and performance of our proposed protocol named PRPT. We have used Java language to mplement our experments. The experments are carred out on Wndows XP operatng system wth 2.13 GHz Intel Core 3 processor and 4 GB of memory. In the followng experments we use IBM Quest Synthetc Data Generator to generate the expermental data. Fgure 1 llustrates that dstorton rato changes dependng on the varaton of l-value, k-value and -value. When l-value ncreases, prvacy protecton degree ncreases. The number of dfferent senstve attrbutes wthn the same equvalent group ncreases, resultng n the generalzaton level of dentfer attrbutes ncreased, then leadng to substantal nformaton loss from the orgnal data ncreased, ultmately causng dstorton rato of multple senstve attrbutes set ncreased. When other condtons are dentcal, k-value ncreased, the group sze becomes larger. Because the grouped data should meet dverse, attrbutes n equvalent group ncrease. Then generalzaton levels ncrease and data dstorton rate also ncreases. When the number of data sets and the parameters are equal, the dmenson of senstve attrbute ncreases, the dstorton rate of multple senstve attrbutes s hgher, whch s caused by senstve property dversty n each dmenson. By contrastng the followng fgure, we can conclude that PRPT protocol by usng multple senstve attrbutes generalzaton can avod excessve generalzaton of the dentfer attrbutes, so the total dstorton rate s less than the other method. Therefore the total dstorton rato of PRPT protocol s smaller than other algorthm. And compared to the l-dversty, k-l-senstve rules has a relatvely low level of data loss. Ths experment suggests that PRPT protocol has lower nformaton loss than l-dversty algorthm and k-l algorthm. Accordng to the above expermental results analyss, we can conclude that PRPT protocol can get References better performance than other algorthm under the same condtons FIGURE 1 Dstorton rato changes dependng on l-value changes (k=40, =3) 9 Conclusons Cloud computng has been envsoned as the next generaton archtecture of IT Enterprse. Ths technology not only gave us more convenence, but also exposed some securty problem. When people access cloud servce or receve cloud servce, they should provde many attrbutes to ensure ths servce accomplsh successfully. But much prvate data are ncluded n these attrbutes. If these senstve attrbutes are dsclosed, t wll brng sufferng to people. Ths paper llustrated the mportance of protectng customers' prvate data n cloud computng. We have argued that t s very mportant to take prvacy nto account and we proposed a novel anonymty-based protocol preservng prvacy based cloud envronment. Acknowledgements PRPT Number of Nodes k-anonymty Ths research s supported by the Educaton Scence and Technology Project of Henan Provnce under the grant No. 13A and by the Technology Bureau Project of Zhengzhou Cty under the grant No. 131PPTGG [1] Wang J,, Zhao Y, Shuo J, Le J 2009 Provdng Prvacy Preservng n Cloud Computng n ICTM Proceedngs IEEE [2] Almorsy M 2011 Collaboraton-Based Cloud Computng Securty Management Framework, n CLOUD Proceedngs IEEE [3] Kretzschmar M, Gollng M 2011 Securty management spectrum n future mult-provder Inter-Cloud envronments-method to hghlght necessary further development n SVM Proceedngs IEEE 1-8 [4] Bouayad A, Bllat A, El Houda Mejhed N, El Ghaz M 2012 Cloud computng: Securty challenges n CIST Proceedngs IEEE [5] Khall I, Khreshah A, Bouktf S, Ahmad A 2013 Securty Concerns n Cloud Computng n ITNG Proceedngs IEEE [6] Kandukur B, Patur V, Raksht A 2009 Cloud Securty Issues n SCC Proceedngs IEEE [7] Hamd M 2012 Securty of cloud computng, storage, and networkng n CTS Proceedngs IEEE 1-5 [8] Behl A, Behl K 2012 Securty Paradgms for Cloud Computng n CICSYN Proceedngs IEEE [9] Al Awadh E, Salah K, Martn T 2013 Assessng the securty of the cloud envronment n GCC Proceedngs IEEE [10] Wang J, Le J A New Prvacy Preservng Approach Used n Cloud Computng Journal of Key Engneerng Materals (1) (n Chnese) [11] Francs T, Vadvel S 2012 Cloud computng securty: Concerns, strateges and best practces n ICCCTAM Proceedngs IEEE [12] Wang J, Novel 2012 A Anonymty Algorthm for Prvacy Preservng n Publshng Multple Senstve Attrbutes Research Journal of Appled Scences, Engneerng and Technology 4(22) [13] Mell P 2012 What's Specal about Cloud Securty Journal of IT Professonal 14(4) 6-8 [14] Vega J 2012 Cloud Securty: Not a Problem Journal of Securty & Prvacy 10(4) 3 [15] Goth G 2011 Publc Sector Clouds Begnnng to Blossom: Effcency, New Culture Trumpng Securty Fears Journal of Internet Computng 15(6) 7-9 [16] Kaufman L M 2009 Data securty n the World of Cloud Computng n Securty and Prvacy Proceedngs IEEE 61-4 [17] Behl A, Behl K 2012 An analyss of cloud computng securty ssues n WICT Proceedngs IEEE

6 [18] Wang J, Le J 2010 Novel Prvacy Preservng Classfcaton Mnng Approach Based Cloud Envronment n BTMC Proceedngs IEEE [19] Wang J, Luo Y, Zhao Y, Le J 2009 A Survey on Prvacy Preservng Data Mnng n DBTA Proceedngs IEEE [20] Zhang Q, Koudas N, Srvastava D, Yu T 2007 Aggregate query answerng on anonymzed tables n ICDE Proceedngs IEEE [21] L Y, Tygar JD, Hellersten J M 2005 Prvate Matchng, n Computer Securty Proceedngs Sprnger [22] San P, Yun S, Mranda M 2009 A prvacy manager for cloud computng In CloudCom Proceedngs IEEE [23] Mayank B, Rakesh A, Jadeep V 2009 Prvacy-preservng ndexng of documents on the network The VLDB Journal (n Chnese) [24] Zhan J, Matwn S 2006 A Crypto-Based Approach to Prvacy- Preservng Collaboratve Data Mnng n Data Mnng Proceedngs IEEE [25] Wang S, Lu G 2011 Fle Encrypton and Decrypton System Based on RSA Algorthm n Computatonal and Informaton Scences Proceedngs IEEE [26] Lu W, Wang Y, Cao Y 2011 Research on Secure Mult-Party Closest Strng Problem n Wreless Communcatons, Networkng and Moble Computng Proceedngs IEEE 1-4 [27] Lee J, Chang J 2007 Semantcally Secure Authentcated Encrypton Scheme and the Same Scheme for Ad-hoc Group Called a Rng n Informaton Technology Proceedngs IEEE Authors Jan Wang, born n 1981, November 26th, Chna Current poston: an nstructor n Henan Unversty of Economcs and Law. Unversty studes: Ph.D. degree from Donghua Unversty, Shangha, Chna n June Scentfc nterest: prvacy preservng n cloud computng, nformaton securty. Publcatons: 10 papers. Le Wang, born n 1983, October 29th, Chna Current poston: an nstructor n SIAS Internatonal Unversty. Unversty studes: Bachelor degree from Zhengzhou Unversty, Zhengzhou, Chna n June Scentfc nterest: computer scence, database applcaton. 144