Ideja predstavljena u ovom radu opisuje proces elektronskog plaćanja korišćenjem koncepta multicard pametne kartice koja koristi model autentifikacijom PIN-a koji je enkodiran iz biometrijskih podataka otiska prsta. Softver biometrijskog skenera integrisanog u PIN PAD uređaj proverava autentifikaciju vlasnika kartice, koristeći predstavljeni algoritam koji kodira biometrijski podatak otiska prsta u PIN broj. Kodirani PIN uspoređuje se sa PIN-om ugrađenim u čip multicard pametne kartice. Multicard pametna kartica ima integrisano funkcijsko dugme kojim upravlja korisnik. Ukoliko korisnik želi izvršiti elektronsko plaćanje potrebno je jednom ili nekoliko puta pritisnuti ovo dugme kako bi aktivirao virtuelnu karticu koja se koristi za elektronsko plaćanje.

Implementacija ove ideje omogućava korisniku upravljanje elektronskim plaćanjem korišćenjem samo jedne multicard pametne kartice bez potrebe za ručnim unosom PINa. Korišćenjem ovog modela elektronskog plaćanja korisnik će imati poboljšano korisničko iskustvo.
Ideja ovog rada je nastavak dosadašnjih autorovih istraživanja kako bi se dobio algoritam koji će maksimalno pojednostaviti proces elektronskog plaćanja. Cilj rada je predstaviti konceptuelni model elektronskog plaćanja koji zadovoljava “Strong Customer Authentication and Secure Communication” koju zahtevaju EU propis: “Directive on payment services (PSD2)”.


Literatura:
1) Andrew Boyd (2009). Comparing fingerprints, no.2529.
2) Bhanu B., Tan, X. (2003). Fingerprint indexing based on novel features of minutiae tripets, IEEE Trans. On Pattern Analysis and Machine Intelligence, 25(5), pp 616-622.
3) Bhanu, B., Tan, X., (2004). Computational algorithms for fingerprint recognition. Kluwer Academical Publishers,
4) Cao, K., & Jain, A., K. (2015). Learning Fingerprint Reconstruction: From Minutiae to Image, IEEE Transactions on Information Forensics and Security, Vol. 10, No. 1, pp. 104-117.
5) Fengling, H., Jiankun H., Leilei H., Yi W., (2007). Generation of Reliable PINs from Fingerprints, Published 2007 in 2007 IEEE International Conference on Communication.
6) FuzeX White paper v.1.7. (2018).
7) FVC2002, Fingerprint verification Competition 2002,
8) Germain, R., S., Califano, A., & Colville, S., (1997). Fingerprint Science and Eng., vol.4, pp. 42-49.
9) Horst F. (2018). Payment cards in Europe.
10) Iwasokun, G., B., Akinyokun, O., C., & Dehinbo, O., J., (2014). Minutiae Inter-Distance Measure for Fingerprint Matching, Int’l Conference on Advanced Computational Technologies & Creative Media (ICACTCM’2014) Aug. 14-15, Pattaya (Thailand) .
11) Jadhav, S., D., Barbadekar, A., B., Prof., Dr Patil, S., P. (2011). Euclidean Distance Fingerprint Matching, Institute of Technology, Pune, INDIA.
12) Jain, A., K., Lin H., & Ruud, B. Online fingerprint Verification, 1977.
13) Jain, A., K., Pankanti, S. Prabhabar, S. Hong, L. and Ross, A. (2004). Biometrics: A grand challenge. Procccedings of international conference on pattern recognition, vol.2, 935-942.
14) Lisa S. Nelson (2011). American identified: Biometric technology and society, Massachusetts Institute of Technology.
15) Rawlson, K., (2016). Biometrics in Banking & Financial Services, June 27-29, 2016. Ravichandran, Krishnamurthy, M. (2018). Near Field Communication Based Digital Transaction Card, Department of Information Technology, AMET University, Chennai, Vol. 9, No. 3, March 2018, pp. 587~590, ISSN:2502-4752, DOI:10.11591/ijeecs.v9.i3.pp587-590
16) Sankalp B. (2014). Authenticating Transactions using Bank–Verified Biometrics,
17) Vahid K. Alilou, Mathlab script: FingerPrint Matching: A simple approach version 1.0 by Vahid K. Alilou
18) Woei-Jiunn T., Chia-Chun W., Wei-Bin, L., (2004). A smart card-based remote scheme for password authentication in multi-server Internet services, Department of Information Management, Da-Yeh University, 112 Shan-Jiau Rd., Taiwan.
19) Zhao, Q., Zhang, Y., Jain, A., K., Paulter, N. G. & Taylor, M. (2013). A Generative Model for Fingerprint Minutiae, ICB, Madrid, Spain

