• 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