CRIMINAL MAPPING BASED ON FORENSIC EVIDENCES USING GENERALIZED GAUSSIAN MIXTURE MODEL

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1 Voume No. 4 June 202 ISSN The Internatona Journa of Computer Scence & Appcaton TIJCSA RESEARCH AER Avaabe Onne at CRIMINAL MAING BASED ON FORENSIC EVIDENCES USING GENERALIZED GAUSSIAN MIXTURE MODEL Uttam Mande Y.Srnva J.V.R.Murthy Dept of CSE Dept of IT Dept of CSE GITAM Unverty GITAM Unverty J.N.T.Unverty Vakhapatnam Vakhapatnam Kaknada [email protected] [email protected] [email protected] Abtract: The Crme rate and crmna actvte have ncreaed enormouy n the pat few decade. Crme preventon and crmna dentfcaton are the prmary ue before the poce peronne nce property and ve protecton are the bac concern of the poce but to combat the crme the avaabty of poce peronne mted and on the other hand the number of crmna are ncreang dratcay. Hence to upport the aw keeper data about the crmna crmna htory together wth crmna atttude w be very much beneftted. Th paper am toward the contructon of new methodooge baed on Data mnng concept and erve a a decon upport ytem. Gven a et of avaabe cue from the forenc ab and the cue coected at the crme pot a methodoogy preented to map the evdence and dentfy a crmna. Key word: Data mnng Generaed Gauan Mxture mode Crme crmna mappng crmna dentfcaton forenc fnger prnt. Introducton TIJCSA A Rght Reerved 22

2 & Appcaton TIJCSA ISSN Vo. No. 4 June 202 The ever changng fe tye dere toward uxure envronmenta condton have drven the human toward the crmna actvte [] Many ubc and rvate agence are workng rgorouy to uphod aw and order. Wth the ncreae n the crmna actvte to combat the crme a data bae about the crmna to be mantaned [2]. Coverng the compete nformaton about the crmna and th data houd be made avaabe wth a the poce peron.a the crmna actvte have extended t wng at dfferent ocaton nformaton exchange between the poce taton at dfferent ocaton w be of great advantage [3] Th mechanm houd be hepfu n nformaton harng and thereby hapng toward a meanngfu crme anay. To upport effectve methodooge that hep n crmna nvetgaton for evauatng the phyca cue and determnng the dfferent tratege to be adopted for nvetgaton are to be formuated. Therefore the phyca evdence obtaned from the wtne and the forenc report hep toward the better crmna anay. Hence n th paper a databae generated from the crmna data avaabe from dfferent poce taton of Andhra radeh. The databae created by conderng two bac fact v. avaabty of wtne at the crmna port and the report from the forenc ab that are coected from the cue pot [4]. The data mnng concept are expoted for mnng the kehood of the crmna baed on the feature/ wtne avaabe. Cuterng performng baed on the type of crme. The crme actvte condered n th paper are Murder Rot kdnap and robbery. Baed on the feature decrbed about the crmna a face generated and the generated face compared wth that of the extng face for fndng the kehood of the crmna [6]. Thee dentte are further mapped wth the forenc cue to formuate a unque dentty. Data mnng technque hep to expore the enormou data and makng t pobe n reachng the utmate goa of crmna anay by ung the concept of cuterng and cafcaton. In th paper the concept of cuterng carred out bang on the type of crme. The ret of paper organed a foow ecton -2 of the paper dea wth feature n ecton- 3 deta about the crme dentfcaton preented Cuterng technque dcued n ecton - 4 the Generaed Gauan Mxture mode preented aong wth updated equaton ung EM agorthm expermentaton hghghted n ecton- 5 the ecton 6 of the paper focu on the concuon 2. Acquton of Feature from the wtne: Any crme nvetgaton hghght prmary on two ue Wtne avaabe and 2 Cue avaabe and reatng thee feature wth that of the data avaabe regardng the crmna. The TIJCSA A Rght Reerved 23

3 & Appcaton TIJCSA ISSN Vo. No. 4 June 202 crme data bae condered n th paper ncude are robbery 2 murder 3 kdnappng 4 rot. For the dentfcaton of any crme we need to have an dea about cue varabe 2 crmna reatng/dentfcaton. Crme cue pay a vta roe n the proper dentfcaton of crmna. The cue hep the teppng tone toward the crme anay and crmna reatng the mappng of the crmna baed on the cue wth data avaabe n the data bae by the ue of ntegent knowedge mappng. 3. Crme Identfcaton ung Crme nk The varou crme nk that were condered ncude Crme ocaton pace: retaurant theater road raway taton hop/god hop ma houe apartment 2 Crmna attrbutehar but eyebrow noe teeth beard age group mutache anguage known 3 Crmna pychoogca behavor can be recogned by type of kng We have condered the type of kng a mooth remova of part harh whch attrbute to the pychoogca behavor of the crmna 4 Modu operand object ued for crme to 2Rope 3Stck 4Knfe Thee crmna nk hep to anaye the dataet there by makng the crme nvetgator to pane for dentfcaton of the crmna. In th paper we have condered bnary cuterng to cuter the data bae baed on type of crme and the cafcaton carred out from the feature avaabe. 3. Bnary cuterng: In order to mpfy the anay proce the huge dataet avaabe to be cutered. The cuterng n th paper baed on the type of crme. A data et generated from the databae avaabe from the Andhra radeh poce department and a tabe created by conderng the FIR report The varou fed condered ncudng the crmna dentfcaton number crmna attrbute crmna pychoogca behavor crme ocaton tme of crme day/nght wtne /cue the data et generated by ung the bnary data of & 0 ndcatng the preence of attrbute TIJCSA A Rght Reerved 24

4 & Appcaton TIJCSA ISSN Vo. No. 4 June 202 and 0 ndcatng the abence of attrbute then cuterng of the bnary data done a propoed by Tao H 2005 ung the bnary cuterng Crme are categored n many way here we have gven weght to each type of crme where weghng cheme condered n the manner a the reatve crme w be gven wth near vaue after appyng cuterng agorthm on th type of crme feature we have got four cuter of crme data they are robbery kdnap murder and rot Fg categore of crme 4. Generaed Gauan Mxture mode The robabty Denty functon the Generaed Gauan mxture mode gven by f µσ e 2 Γ + A σ Z µ A σ TIJCSA A Rght Reerved 25

5 & Appcaton TIJCSA ISSN Vo. No. 4 June TIJCSA A Rght Reerved 26 The nta etmate are updated ung the EM agorthm and the fna updated parameter are gven by A σ σ σ Γ > Γ N N t t / 3/ Γ Γ + θ µ θ σ + N N N k t t N γ θ θ µ γ

6 & Appcaton TIJCSA ISSN Vo. No. 4 June Expermentaton The feature are taken a nput from forenc cue and fnger prnt are condered for th purpoe. The fnger prnt avaabe at pot are compared wth that of the databae compared for the reevancy n crmna. we have condered two varant Aumng the fngerprnt are obtaned at the crme pot In order to ratfy a crmna baed on the fnger prnt we have condered the bood group of the crmna f avaabe to map the unquene of the crmna In order to dentfy a crmna baed on the fnger prnt we have ued a Generaed Gauan Mxture Mode The Feature obtaned from the fnger prnt are condered and the robabty Denty Functon cacuated Th DF matched wth that of the extng crmna to dentfy a crmna In order to dentfy a crmna baed on the fnger prnt we have ued a Generaed Gauan Mxture Mode The Feature obtaned from the fnger prnt are condered and the robabty Denty Functon cacuated Th DF matched wth that of the extng crmna to dentfy a crmna The man reaon for utng Generaed Gauan Mxture Mode that any fngerprnt may be contanng two type of feature Ø Ø Macro feature Mcro feature Macro feature are thoe feature whch can be dentfed drecty uch a Core and Rdge TIJCSA A Rght Reerved 27

7 & Appcaton TIJCSA ISSN Vo. No. 4 June 202 In the tuaton where the macro feature are not avaabe mcro feature w be of great ue.mcro feature ncude vaey deta pont whroo crong Thee feature are mapped and DF are obtaned the tet equence are compared and the crmna ratfed Thee feature are mapped and DF are obtaned the tet equence are compared and the crmna ratfed Fg 2 howng the nput gven to mode Fngerprnt avaabe at crme pot Fnger prnt match wth Crmna fnger prnt TIJCSA A Rght Reerved 28

8 & Appcaton TIJCSA ISSN Vo. No. 4 June 202 Fg 3 Fg 4 Fg 34 howng the output of Fngerprnt mappng wth crmna databae Fg 5 :the nap hot of data et TIJCSA A Rght Reerved 29

9 & Appcaton TIJCSA ISSN Vo. No. 4 June 202 When more than one upect gven The mode ue the other cue ke bood or any other cue for further fterng the t of crmna. 6. Concuon: If the wtne not avaabe at the crme ncdent and f the forenc report are avaabe then n uch cae dentfcaton of the crmna a condered n th paper. The crmna fnger prnt are mapped wth that of the avaabe from the data bae. and f there a map the crmna can be dentfed..if the data avaabe from the wtne not uffcent aong wth the forenc report we conder bood ampe and type of kng n order to ratfy crmna. Th paper preent a nove methodoogy of dentfyng a crmna n the preence of cue by the forenc expert. In thee tuaton n th paper we have tred to dentfy the crmna by mappng the crmna ung the Generaed Gauan mxture mode.. Reference:.Care of Berrew Q.C Data mnng: The new weapon n the war on terrorm retrved from the Internet on Cate H. Fred Lega Standard for Data Mnng retreved from the nternet on Cfton Chrtopher 20. Encycopeda Brtannca: data mnng Retreved from the web on Jeff and Harper Jm Effectve Counterterrorm and the Lmted Roe of redctve Data Mnng retreved from the web U.M. Fayyad and R. Uthuruamy Evovng Data Mnng nto Souton for Inght Comm. ACM Aug pp W. Chang et a. An Internatona erpectve on Fghtng Cybercrme roc. t NSF/NIJ Symp. Integence and Securty Informatc LNCS 2665 Sprnger-Verag 2003 pp TIJCSA A Rght Reerved 30

10 & Appcaton TIJCSA ISSN Vo. No. 4 June H. Kargupta K. Lu and J. Ryan rvacy-sentve Dtrbuted Data Mnng from Mut- arty Data roc. t NSF/NIJ Symp. Integence and Securty Informatc LNCS 2665 Sprnger-Verag 2003 pp Apr M.Chau J.J. Xu and H. Chen Extractng Meanngfu Entte from oce Narratve Report roc.nat Conf. Dgta Government Reearch Dgta Government Reearch Center 2002 pp A. Gray. Sa and S. MacDone Software Forenc: Extendng Authorhp Anay Technqueto Computer rogram roc. 3rd Bannua Conf.Int Aoc. Forenc Lngutc Int Aoc. Forenc Lngutc 997 pp R.V. Hauck et a. Ung Copnk to Anaye Crmna-Jutce Data Computer Mar pp T. Senator et a. The FnCEN Artfca Integence Sytem: Identfyng otenta Money Launderng from Report of Large Cah Tranacton AI Maganevo.6 no pp W. Lee S.J. Stofo and W. Mok A Data Mnng Framework for Budng Intruon detecton Mode roc. 999 IEEE Symp. Securty and rvacy IEEE CS re 999 pp O. de Ve et a. Mnng E-Ma Content for Author Identfcaton Forenc SIGMOD Record vo. 30 no pp G. Wang H. Chen and H. Atabakhh Automatcay Detectng Deceptve Crmna Identte Comm. ACM Mar pp S. Waerman and K. Faut Soca Network Anay:Method and Appcaton Cambrdge Unv. re TIJCSA A Rght Reerved 3