DocumentCode :
3777673
Title :
Artificial neural network-based methodology for vulnerabilities detection in EMV cards
Author :
Noura Ouerdi;Ilhame ElFarissi;Abdelmalek Azizi;Mostafa Azizi
Author_Institution :
Lab. ACSA, Faculty of Sciences, Mohammed First University, Oujda, Morocco
fYear :
2015
Firstpage :
85
Lastpage :
90
Abstract :
The Artificial Neural Network(ANN) was exploited in several research works as a mechanism of clustering, diagnostic, detection and classification. This is what our proposal is aimed at. Indeed, we had used the neural network to evaluate the integrity of an EMV (Europay MasterCard and Visa) Card by detecting the vulnerabilities. First of all, we had used the state transition diagram presenting the interaction between a terminal and an EMV card to generate the authorized interactions and unauthorized ones (considered as vulnerabilities). Then, we had exploited these data to implement a neural network with the ability to evaluate the EMV specifications by distinguishing between the vulnerabilities and normal cases of interaction. In this paper, we will discuss in detail the mentioned steps.
Keywords :
"Biological neural networks","Cryptography","Authentication","Training","Standards"
Publisher :
ieee
Conference_Titel :
Information Assurance and Security (IAS), 2015 11th International Conference on
Type :
conf
DOI :
10.1109/ISIAS.2015.7492750
Filename :
7492750
Link To Document :
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