Protecting E-Commerce Systems From Online Fraud

Transcription

1 Protctng E-Commrc Systms From Onln Fraud Frst Author P.PhanAlkhya Studnt, Dpartmnt of Computr Scnc and Engnrng, QIS Collg of Engnrng & Tchnology, ongol, Andhra Pradsh, Inda. Scond Author Sk.Mahaboob Basha Assstant Profssor, Dpartmnt of Computr Scnc and Engnrng, QIS Collg of Engnrng &Tchnology, ongol, Andhra Pradsh, Inda. Abstract- Du to th advnt of Intrnt tchnologs, E- commrc wdly adaptd mod of busnss n modrn tms. Wth th growth of E-commnc doman crdt card usag has bcom a common phnomnon. Ths has gvn chanc to advrsars to commt fraud. In th ral world, thr wr plnty of nstancs of fraud cass. It has ts mpact on fnancal outfts that ssu crdt cards, th E-commrc busnss ntts and also th customrs of th E-commrc applcatons. To ovrcom ths problm and to buld confdnc n th stakholdrs of th E- commrc many tchnqus cam nto xstnc. As smpl pattrn matchng mthods ar nadquat to solv th problm many modrn tchnqus cam nto xstnc. Thy ar basd on Gntc programmng, Squnc Algnmnt, Machn larnng, Fuzzy logc, Data mnng and Artfcal ntllgnc. Ths tchnqus ar capabl of dtctng fraudulnt transactons. In ths papr w xplor varous tchnqus bng usd. W also buld a prototyp applcaton whch dmonstrats th ffcncy of Gntc Programmng to dtct crdt card fraud. Th mprcal rsults rvald that th proposd soluton s ffctv. Kywords Crdt card fraud dtcton, fraud dtcton tchnqus, E-commrc INTRODUCTION Crdt card fraud dtcton s an actv and contnuous rsarch ara as t nvolvs montary transactons. Th rsarch s mportant n th lght of wb tchnologs that support E-commrc applcatons n buldng and managng. Morovr busnsss n th world ar gong onln. Th onln busnsss ar abl to rach global markts and thy rach global customrs. Th E-commrc applcatons mak t possbl to shop tms anytm and anywhr. Thr ar no tm and gographcal rstrctons. Ths has plnty of advantags for both consumrs and busnsss. Thr ar many knds n E-commrc. B2B (Busnss to Busnss), B2C (Busnss to Consumr) and C2C (Consumr to Consumr) ar th thr popular forms of E-commrc applcatons. Th transactons n E- commrc mght hav fraudulnt transactons along wth gnun ons. It s ssntal to hav a systm that can dtct fraudulnt transactons. Varous tchnqus such as Hddn Markov Modl, Artfcal Intllgnc, Squnc Algnmnt, and Gntc Programmng cam nto xstnc to combat ths problm. In ths papr w mplmnt Gntc Algorthm (GA) n ordr to dtct crdt card fraud. Th GA has provson for valuatng populatons contnuously untl a bst ft s found. Th oprators lk cross ovr and mutaton hlp n ISSN: Pag3549

2 accurat prdcton of fraud cass. W also bult a prototyp applcaton that dmonstrats th ffcncy of th proposd soluton. Th xprmntal rsults rvald that th applcaton s vry usful n ral tm systms. Th rmandr of th papr s organzd as follows. Scton II rvws rlvant ltratur. Scton III prsnts som of th fraud dtcton tchnqus. Scton IV provds dtals about th proposd fraud dtcton tchnqu and also th prototyp dtals. Scton V shows xprmntal rsults whl scton VI concluds th papr. Th Dmpstr Shafr thory and Baysan larnng approach s th combnaton of two approachs [17], [18], [19]. Th vdncs from past and corrct ar combnd n ordr to dtct fraud. Informaton fuson s th approach followd by ths hybrd tchnqu. Fgur 1 shows th ovrvw of ths hybrd approach. RELATED WORKS Crdt card fraud dtcton has bcom an nvtabl part of E-commrc applcatons. As th applcatons nvolv montary transactons, fraud dtcton tchnqus ar ndspnsabl. Lot of rsarch has bn mad n ths ara [1], [2], and [3]. Many algorthms cam nto xstnc to dtct crdt card fraud [4], [2]. Th algorthms nclud fuzzy logc [5], squnc algnmnt algorthm [6], [7], data mnng tchnqus [8], [9], machn larnng and artfcal ntllgnc approachs [10], [11], [12]. Thr ar othr tchnqus such as Wb Srvcs Basd CCFD, CCFD wth Artfcal Immun Systm [13], [14], Cardwatch [15], Baysan Blf Ntworks [4], Intruson Dtcton [13], Cas Basd Rasonng for CCFD [4], Advancd Fraud Dtcton [16], CCFD basd on computatonal ntllgnc [13], CCFD usng slf-organzng maps [13]. Many ar basd on pattrn matchng, Mta larnng and artfcal ntllgnc. In ths papr w compar som of th tchnqus whch ar good for CCFD. COMPARISON OF CCFD SYSTEMS In ths scton w compar varous crdt card fraud dtcton tchnqus such as Dmpstr Shafr thory and Baysan larnng, Hddn Markov Modl (HMM) and Gntc Programmng (GP). Dmpstr Shafr thory and Baysan larnng approach Fg. 1 Hybrd approach for CCFD (xcrpt from [16]) As sn n fgur 1, ths approach has four componnts. Thy ar rul basd fltr, Baysan larnr, transacton hstory databas and Dmpstr-Shafr addr. Th vdncs found from multpl componnts ar fusd and th dtcton s mad. Ths approach s mor accurat but consums mor rsourcs bsds bng slow. CCFD usng Hddn Markov Modl (HMM) Ths modl s usd to analyz crdt card transactons. It nds tranng data and also tst data n ordr to dtct fraud. It uss K-mans data mnng algorthm ntrnally. Th K-mans algorthm taks all crdt card transactons ISSN: Pag3550

3 and numbr of clustrs as nput and gnrats clustrs that ar usd n HMM. All th transactons ar dvdd nto low, mdum and hgh, th thr clustrs. Onc th clustrs ar formd thy ar kpt n a HMM. Th HMM s usd for vry nw transacton. Th amount n nw transacton should blong to thr low, or mdum or hgh. If not th transacton s suspctd to b fraudulnt and th corrspondng popl or organzatons ar alrtd. Th gnral ovrvw of HMM s as shown blow. th crdt card, and crdt card book balanc. Th ovrvw of th GP approach s as shown n fgur 3. Fg. 3 Ovrvw of proposd archtctur for GP As can b sn n fgur 3, th data of crdt cards s takn from data warhous. Thn th data s subjctd to ruls ngn. Th ruls ngn contans fraud cas ruls. Th fltr and prorty componnts tak car of fltrng and prorty sttng. Th gntc algorthm s rsponsbl to dtct fraud. Fg. 2 Ovrvw of HMM Modl (xcrpt from [16]) CCFD usng GP Gntc programmng s wdly usd for solvng varous problms. In ths papr w mplmntd a Gntc Algorthm to dtct crdt card fraud. Ths algorthm maks us of xstng transactons of crdt cards. It uss multpl crtra to dtct fraud. Th crtra nclud crdt card usag frquncy, crdt card usag locaton, ovrdraft on PROTOTYPE IMPLEMENTATION A prototyp applcaton has bn bult n Java platform. Th applcaton s dvlopd wth Graphcal Usr Intrfac (GUI) to b usr-frndly. Th nvronmnt usd to buld th applcaton ncluds a PC wth 4GB RAM, Cor 2 dual procssor runnng Wndows XP opratng systm. NtBans s usd as IDE. Th mportant applcaton scrns ar prsntd n fgur 4 and 5. ISSN: Pag3551

4 ths papr. Th rsults hlp n undrstandng th fraud transactons and thy can b usd to tran th systm furthr n ordr to mak nw ruls and achv hghr accuracy of fraud dtcton. EXPERIMENTAL RESUTLS W compard th rsults of our approach wth that of Artfcal ntllgnc, Hddn Markov Modl, Squnc Algnmnt, and Machn Larnng. Th comparson s mad n trms of tru postvs and fals postvs. Hghst tru postvs and last fals postvs ar achvd by GP. Fg. 4 Datast usd for xprmnts As sn n fgur 4, th datast contans crdt card transacton dtals for numbr of nstancs. Ths data s usd by GA proposd n ths papr. Th GA maks us of th componnts as dscrbd n fgur 3 n ordr to dtct fraudulnt transactons. Th rsults of dtcton ar shown n fgur 5. T r u P o s80 t60 v40 s20 Comparson of CCFD Tchnqus CCFD Tchnqus 0 Fg. 6 Prformanc of CCFD tchnqus wth rspct to tru postvs As can b sn n fgur 6, th prformanc of Gntc Programmng s 100%. It has achvd 100% tru postvs whn compard wth othr tchnqus such as AI, HMM, SA and machn larnng. Fg. 5 Rsults of Fraud Dtcton As can b sn n fgur 5, basd on varous crtra mntond arlr, th fraud dtcton s don. Th crtra ar usd as part of gntc programmng modl proposd n ISSN: Pag3552

5 F a l s Fg. 7 Prformanc of CCFD tchnqus wth rspct to fals postvs Comparson of CCFD Tchnqus P o s t v s Machn Larnng Squnc Algnmnt HMM AI GP As can b sn n fgur 7, th prformanc of Gntc Programmng s mor. It has achvd vry lss prcntag of fals postvs whn compard wth othr tchnqus such as AI, HMM, SA and machn larnng. CONCLUSIONS AND FUTURE WORK CCFD Tchnqus In ths papr w studd th problm of crdt card fraud n E-commrc applcatons. W xplord varous approachs to solv th problm. Th knowldg of varous approachs can mprov th scop of protctng E-commrc applcatons. Fnally w mplmntd gntc algorthm for crdt card fraud dtcton. As th advrsars chang thr mans of attack vry tm, t s mportant to hav constant vgl on th mthods thy us and updat th tchnqus accordngly. In ths papr buld a prototyp applcaton n Java platform n ordr to dmonstrat th proof of concpt. Th applcaton uss gntc algorthm to dtct crdt card fraud. Data mnng and othr tchnqus ar avalabl to solv ths problm. Howvr, w prfrrd GA as t s ffcnt n dtctng crdt card fraud. Th xprmntal rsults rval that th proposd applcaton s usful and can b usd n ral world systms. REFERENCES [1] Tj Paul Bhatla, Vkram Prabhu & Amt Dua Undrstandng Crdt Card Frauds, [2] Lnda Dlamar, Hussn Abdou, John Ponton, Crdt card fraud and dtcton tchnqus: a rvw, Banks and Bank Systms, pp , [3] Barry Masuda, Crdt Card Fraud Prvnton: A Succssful Rtal Stratgy, crm prvnton, Vol. 6, [4] Ezawa.K. & Norton.S, Constructng Baysan Ntworks to Prdct Uncollctbl Tlcommuncatons Accounts, IEEE Exprt, Octobr;45-51, [5] Ptr J. Bntly, Jungwon Km, Gl-Ho Jung and Jong-Uk Cho, Fuzzy Darwnan Dtcton of Crdt Card Fraud, In th 14th Annual Fall Symposum of th Koran Informaton Procssng Socty, 14 th Octobr [6] Amlan Kundu, S. Sural, A.K. Majumdar, Two-Stag Crdt Card Fraud Dtcton Usng Squnc Algnmnt, Lctur Nots n Computr Scnc, Sprngr Vrlag, Procdngs of th Intrnatonal Confrnc on Informaton Systms Scurty, Vol. 4332/2006, pp , [7] Amlan Kundu, Suvasn Pangrah, Shamk Sural and Arun K.Majumdar, BLAST-SSAHA Hybrdzaton for Crdt Card Fraud Dtcton, IEEE Transactons On Dpndabl And Scur Computng, vol. 6, Issu no. 4, pp , Octobr-Dcmbr [8] Phlp K. Chan,W Fan, Andras L. Prodromds, Salvator J. Stolfo, Dstrbutd Data Mnng n Crdt Card Fraud Dtcton, IEEE Intllgnt Systms ISSN, Vol. 14, Issu No. 6, Pags: 67 74, Novmbr [9] C. Phua, V. L, K. Smth, R. Gaylr, A Comprhnsv Survy of Data Mnng-basd Fraud Dtcton Rsarch, Artfcal Intllgnc Rvw, [10] Ray-I Chang, Lang-Bn La, Wn-D Su, Jn-Chh Wang, Jn-Shang Kouh, Intruson Dtcton by Backpropagaton Nural Ntworks wth Sampl-Qury and Attrbut-Qury, Rsarch IndaPublcatons, pp.6-10, Novmbr 26, [11] Ghosh, D.L. Rlly, Crdt Card Fraud Dtcton wth a Nural-Ntwork, Procdngs of th Intrnatonal Confrnc on Systm Scnc, pp , ISSN: Pag3553

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