Research on Privacy Protection Approach for Cloud Computing Environments

Transcription

1 , pp Research on Prvacy Protecton Approach for Cloud Computng Envronments Xaohu L 1,2, Hongxng Lang 3 and Dan Ja 1 1 College of Electrcal and Informaton Engneer, Laonng Unversty of Technology Jnzhou, Laonng, , Chna 2 Computer Scence and Technology, Bejng Unversty of Technology, Bejng , Chna 3 Jnzhou Force, Jnzhou, Laonng , Chna lxaohu@emals.bjut.edu.cn,lhxlxh@163.com Abstract Cloud computng s a convenent and cost effcent way that refers to the runnng of software over a network, as on a local computer. But, what s cheap and easy, sn t always safe. Storng mportant data on cloud means that you gve up a certan control of prvacy. Prvacy protecton s a very mportant ssue n cloud computng. In ths paper,we focus on the need of cloud users managed servces and propose an approach for data protecton based trust mechansm, whch usng adaptve mappng resources based on trust to ensure the user data protecton ntatve, and data securty. The analyss shows that the cloud user can ndependently controls the content and manner of servces by usng the approach, whch can acheve the free deployment of resources and the balance of user data protecton and servce provded. Keywords: Cloud computng, prvacy, securty, trust 1. Introducton Cloud computng can be well postoned to meet the needs of the users anytme, anywhere access to resources and transacton processng, n ths computng archtecture, and ts essence s to make the data more and more exposed to the hazardous envronment. Storng mportant programs and fles on the cloud means that you gve up a certan level of control and your prvacy. Platform can be updated, perhaps you would be forced to fgure them out all over agan, or worse, cooperaton between the cloud platform would mean unlawful access by the former. The user n cloud computng requrements at any tme, any place can be carred out safely data access, Cloud has brought us unprecedented servce experence at the same tme, as the shadow of the user data securty ssues. The soluton to get the balance of user prvacy protecton and servces n cloud computng s the key to promote ts applcaton. Trust as an mportant mean of securty technology, whch takes on an ntegral role from the begnnng to the transmsson of the moble user nformaton nteracton. Authorzaton, access control and other securty mechansms are often accompaned by the provson of user prvacy nformaton n the cloud computng envronments, users do not know ther own nteractve objects utmost promnence of securty concerns. How to buld trust between the user and the servce provder, and to reconcle the balance between user prvacy and servce access? Approachs based on trust n prvacy protecton servce-orented technology wll characterze user prvacy trust granularty, and accordng to ts varablty and dynamc establsh mappng relato n- ISSN: IJSIA Copyrght c 2015 SERSC

2 shp; based access control approach accordng to the securty polcy set to control access to prvacy nformaton, dynamc adjustment and settng of user prvacy nformaton and access granularty. The above studes focus consderng the securty threats posed by the malcous acts by the servce requestng party and do not consder the securty threats posed by the servce provder. Trust between enttes n the cloud computng envronment assumptons no longer exst, from the pont of vew of the protecton of user prvacy, the above approaches are not applcable. In ths artcle, we focus on user data protecton ssues n cloud computng, propose a trust-based approach to data protecton, whle dynamcally generate trust relatonshp to release ts own data to acheve balance of prvacy protecton and servces provded. The rest of ths paper s organzed as follows. In Secton 2, we descrbe some related work. In Secton 3, we explan our approach for prvacy protecton n two aspects: one s to relevant defntons and the other s algorthm descrpton. We also gve an applcaton scenaro for better llustraton of our approach. Fnally, we conclude ths paper n Secton RELATED WORK In the commodty market model, resource owners specfy ther servce prce and charge users accordng to the amount of resource they consume. Servces are prced n such a way that supply-and-demand equlbrum s mantaned. Whch has two actors: The resource broker (workng for the user) s denoted by B, Whch can carry out the followng steps for executng applcatons: 1. the broker dentfes servce provders; 2. t dentfes sutable resources and establshes ther prces; 3. t selects resources that meet ts utlty functon and objectves; 4. t uses resource servces for job processng and ssues payments as agreed; In the model, resource consumer only can depend on the specfed prce of resource provder as a parameter, barganng s not permtted. Nash Equlbrum Theory does not requre the asumpton of ndvdual ratonalty and noncooperaton wth the three elements: partcpants collecton O, strategy space R and the utlty functon T, ts process n chronologcal order provdes as follows: 1 In accordance wth the probablty dstrbuton o( t ) for the sender S type, whch was establshed for each and select t from the type of a vable space; 2 Clent observed t,select a transmsson 3 Server observe the m j m ; j, and select an acton a from the feasble acton set; k 4 The revenue of the two sdes, respectvely, xcvv and q ( s, l, y ). r j k Wheren the requrements of the B for each of the m j gven posteror nference wth probablty dstrbuton p(t /m j ), the recpent's a k to maxmze revenue, empathy for the transmsson sgnal S, for a gven polcy, ts value s the optmal. 3. Data Protecton Model based on Trust 3.1 Approach Descrpton In the cloud computng envronment, servce provders and cloud user nformaton closely related to ther prvate nformaton, the user accordng to the degree of trust n the servce, and hope to get the safe use, therefore access to nformaton competton between servce provders. Assume that prvate nformaton of the servce provded by the user to provde the correspond- 114 Copyrght c 2015 SERSC

3 ng servce, but the user can not drectly determne the true qualty of the servce and to ntally approxmate nference can only be made n accordance wth the commtment of the servce provder. In other words, from the pont of vew of the protecton of user securty consderatons, users enjoy nformaton superorty recpent R, and servce provders n the asymmetrc nformaton dsadvantage, as the sender S. There s certan mappng between prvacy nformaton release and servce obtaned the release, whch s to be addressed n ths artcle. Cloud users based on attrbutes of ther own resources or statstcal nformaton on the hstory of servce selecton behavor, develop approprate tme factors and spatal factors to quantfy prvacy degree rules table. Cloud users based resource propertes wll be dvded nto n prvacy perods, for each prvacy nterzone develop approprate Servce demand nterval, the mplcaton s that cloud users at tme of servce, f, then randomly generates the tme factor to quantfy the value of trust. For each tme perod, the tme perod when the hstory of a certan number of servce provders, the statstcs of the tme perod and the total number of tmes to provde a number of fraud, the probablty of obtanng fraudulent perod. Accordng to prvacy degree to provde servces, mappng relatonshp as shown n Table 1: Prvacy degree Servce demand nterval Servce fraud probablty Table 1. Prvacy and Servce Mappng Table t, ) t, ) t, )..., t ] [ t 0 1 [ T 0 1 [ t 1 2 [ t 2 3 [ t n 1 n T, ) T, ) T, )..., T ] [ T 1 2 [ T 2 3 [ T n 1 n p p p 0... p 1 2 n 1 Collecton of the program partcpants {servce provder, the user}, servce provders to provde servces, qualty of servce s hgh (G) and (D) two types, and the selected sgnal s the trust X ranges from 0 to 1 {x: 0 x 1}, ther specfc trust value s based on the drect trust (X z ) and feedback trust (X f ), X = W 1 X z + W 2 X f, where W 1 andw 2 sad X z and X f of the rght weght; users decde ther own prvacy nformaton the release of granularty Y- C(δ,x) sad servces provded type, C (δ, x) table type for δ the servces provded by the trust for the cost of the case, ts value depends on the correspondence relatonshp of confdence and the servce type; H (δ, x) ndcates the type of servce provded by the user are provded servce gans; servce provder's revenue as Y-C (δ, x), the gans of the servce users for H (δ, x) Y. Sgnal theory-based research n cloud computng adverse selecton between servce users and provders, wth ncomplete nformaton based on the expected return of the moble user prvacy (n favor of the securty of the servce provder) servce provders to take the ntatve to abandon malcous decepton motvaton; moble user can get the qualty of servce expectatons and trust-based release prvacy nformaton, enablng moble user's prvacy protecton. 3.2 Program Structure Interactve servce provders and moble users' prvacy nformaton release decsons, accordng to the a pror probablty dstrbuton for the sgnal sender S type can be selected from the lne-type space, whch type of collecton T = {t d, t g } ndcates that the servce qualty low and hgh; then S from the sgnal set M = {m d,.., m g } select a transmt sgnal, whch sgnal set m d, m g respectvely, apply for a low level of prvacy nformaton and the applcaton of a hgh level of Copyrght c 2015 SERSC 115

4 prvacy nformaton; moble user observatons feasble acton set prvacy nformaton and refused to provde prvacy nformaton; choose a behavor and calculate the two sdes revenue. In ths scheme, the cloud user based on the servces provded by the trust to determne the release of prvacy nformaton granularty, from the ntroducton of sgnal theory, the servce provders to maxmze ther own nterests, needs to take the ntatve to provde honest servces model servce revenue management, servce delvery, trust evaluaton, trust, decson-makng, prvacy and nformaton provded module, specfc structure shown n Fgure 1. Implementaton processes of the program are as follows: (1) the user U accordng to the probablty dstrbuton sgnal selecton and make the approprate servces accordng to ther own abltes t; (2) the servce provder S observed t from the correspondng set P, G l, sg G R, R, upd sk select send a m and gven ntal trust; (3) the recpent R observed m correspondng servce provdes assessment, ncludng trust update M,, l evaluaton, trust, decson-makng and feasble acton set, to select the approprate acton trust, sends t to the CSP; (4) Enforcement acton space A servce revenue for ratonal decson-makng cloud users, untl both maxmze the return on the end of the game process. The probablty of assumng n cloud servces to provde the level of qualty receves the request; replaces the block and outputs F ; replaces wth ; (5) responds the user wth an evdence for ths operaton, where n wth s for the verfcaton of n.the dp, sad users of the server to provde a hgh level of prvacy, g p expressed low levels of prvacy nformaton; g provde hgh-qualty servce users gan d sad to provde low-qualty servce user gans; p (g/g p ), p (d/g p ) denote the condtonal probablty of servces for hgh prvacy level of qualty of servce, users select the release of the prvacy of revenue. 3.3 Algorthm Descrpton Depends on the servce to apply for a balance between the cloud user prvacy protecton and access to prvacy, the level of qualty of servce, the relatonshp between both sdes revenue. Bayesan equlbrum pont s that the partes to smply observe the behavor of others to modfy ther subjectve probablty of the latter characterstcs, and thus choose ther own actons, thus provng that cloud servce provders correspondng combnaton and decson-makng consttutes a perfect Bayesan equlbrum, the analyss process s as follows: Frst analyss of the moble user's decson-makng, the ntal trust servce provders take the ntatve to provde moble users sgnal prvate nformaton to provde the moble user receves the sgnal selected acton, specfc actons, ncludng servce qualty evaluaton and correcton pror probablty. If the servce provder applcaton to the hgh-level prvacy nformaton, the moble user to select the expected revenue ssued E p = p (H/Y) I (H, Y) + (1-P (H/ Y)) Z (E, Y), E p = ( g -p g )> 0; Smlarly, f the servce to apply for low prvacy quantty, the cloud user to select payment expected revenue for E p = ( d -p d )> 0;. 116 Copyrght c 2015 SERSC

5 Fgure 1. The Amount of Informaton Released wth Optmal Trust Fgure 2. Servce Permsson Change And analyss of the decsons of the servce provder, the servce provder revenue maxmzaton condtons for max [H (δ, x)-c (δ, x)], the hgh qualty of servce to apply the proceeds of the hgh level of prvacy p g p d ; low servce qualty to provde the requested hgh-level prvacy gans, Z (F)-D (F x (E))> Z(H)-D (F-, x (H)), that ths decson s not sutable for only the applcaton of the low-level prvacy nformaton n order to acheve optmal. Suppose two partcpants n the ncomplete nformaton case the optmal trust shown n Fgure 1, where the horzontal axs represents the degree of the sender R's trust, the vertcal axs represents the release of the prvacy of the recpent S partcle sze, can be seen partcpatng under balanced Strategc correcton pror probablty, and accordng to a gven probablty dstrbuton on the set of nformaton and others nvolved n the follow-up strategy to mantan optmal acton, follow the above strategy Bayes rule to meet the needs of path nformaton on the balanced and ratonal sequence satsfy the refned Tony Yates balancng requrements. Wegh trust and securty, servce provders and get the two sdes wll acheve perfect Bayesan equlbrum, that the servces of a hgh qualty of servce wll requre hgh prvacy, low qualty level of servce wll conscously apply for a low level of prvacy, and moble prvacy, users must release servce applcaton level of servce to apply the amount of prvacy can completely reflect the true qualty of servce. 4. Concluson Copyrght c 2015 SERSC 117

6 In ths paper, we proposed a user data protecton approach n cloud computng envronment n whch we defne trust metrcs as a dynamc and flexble process that offers a new perspectve for decson-makng. The analyss shows that the performance of our approach s obvous and t can help acheve less prvacy loss and more benefts. That the hgh fraud costs make the servces and prvacy provded both sdes to get the maxmum beneft, ths approach can effectvely protect users' prvacy and contanment malcous servce sde, from another pont of vew, t s also benefcal to the securty of the servce sde. The approach proposed n ths paper exposes us to a number of possble research drectons n the future. One drecton that we wll mplement the approach to study the performance ssues. We wll take s to refne our approach to support mult-servces and to help us further optmze the approach. Acknowledgments The work n ths paper has been supported by Natonal Natural Scence Foundaton of Chna (Grant No ). Bejng Natural Scence Foundaton ( ). Pre-launch of Bejng Cty Government Major Tasks and Dstrct Government Emergency Projects (Z ) References [1] M. A. Moharrum and M. Eltowessy, A Study of Statc Versus Dynamc Keyng Schemes n Sensor Networks, Proc. of the 2nd ACM Int l Workshop on Performance Evaluaton of Wreless Ad Hoc, Sensor, and Ubqutous Networks. New York, USA: ACM Press, (2005), pp [2] L. Sweeney, Achevng k-anonymty Prvacy Protecton Usng Generalzato n and Suppresso n, Internatonal Journal of Uncer tanty, Fuzzness and Knowledge Based Systems, vol. 10, no. 5, (2002), pp [3] L. Ibram, M. Petkovc, S. Nkova, P. Hartel and W. Jonker, Cphertext-Polcy attrbute-based threshold decrypton wth flexble delegaton and revocaton of user attrbutes, Techncal Report, Centre for Telematcs and Informaton Technology, Unversty of Twente, (2009). [4] D. Nurm, R. Wolsk and C. Grzegorczyk, Eucalyptus: A Techncal Report on an Elastc Utlty Computng Archetcture Lnkng Your Programs to Useful Systems Tech., Rep , Unversty of Calforna, Santa Barbara, (2008) October. [5] C. Castelfranch, R. Falcone and G. Pezzulo, Integratng trustfulness and decson usng fuzzy cogntve maps, Trust Management, LNCS, vol. 2692, (2003), pp [6] D. D. Salber and G. Abowd, A Conceptual Framework and a Toolkt for Supportng the Rapd Prototypng of Context-Aware Applcatons, Specal ssue on Context-Aware Computng n the Human-Computer Interacton (HCI) Journal, vol. 16, no. 2-4, (2001), pp [7] B. J. Jansen, A. Spnk and T. Saracevc, Real Lfe, Real Users, and Real Needs: A Study and Analyss of User Queres on the Web, Informaton Processng and Management, vol. 36, no. 2, (2000), pp [8] A. N. Ramjattan and P. A. Gross, A Kalman flter model for an ntegrated land vehcle navgaton system, The Journal of Navgaton, vol. 48, no. 2, (1995), pp [9] R. Gbbons, An Introducton To Applcable Game Theory, Journal of Economc Perspectves, vol. 11, no. 1, (1997), pp [10] M. Blaze, J. Fegenbaum and J. Lacy, Decentralzed Trust Management, Proceedngs of the 17th Symposum on Securty and Prvacy, (1996), pp [11] P. B. Ardagnad, "Adaptve servce composton n flexble processes", IEEE Transactons on Software Engneerng, vol. 33, no. 6, (2007), pp [12] M. Spence, Job Market Sgnalng, The Quarterly Journal of Economcs, vol. 87, no. 3, (1973), pp Author 118 Copyrght c 2015 SERSC

7 Xaohu L s currently a lecturer of the college of Electrcal and Informaton Engneer at Laonng Unversty of Technology and a Ph.D. canddate n the College of Computer Scence and Technology at Bejng Unversty of Technology. Her research nterests nclude network securty and trust management. Emal: lxaohu@emals.bjut.edu.cn Copyrght c 2015 SERSC 119

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