• DocumentCode
    3779487
  • Title

    Multi-factor authentication based on multimodal biometrics (MFA-MB) for Cloud Computing

  • Author

    Abdeljebar Mansour;Mohamed Sadik;Essaid Sabir

  • Author_Institution
    NEST Research Group, National Higher School of Electricity and Mechanics (ENSEM), Hassan II University of Casablanca, Morocco
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Cloud Computing (CC) was introduced recently as a new paradigm to host and deliver Information Technology Services. Despite its advantages and maturity, security and privacy issues in CC remain an open challenge. Usually, cloud-based systems use login and password combination, PINs, smart cards, or unimodal biometrics for users authentication; Multimodal biometrics can be considered as an alternative solution and additional factor to increase CC authentication security level. First, the paper deals with the authentication security in CC and proposes a new approach to implement a multimodal biometric systems for authentication and identity management using user´s physiological and/or behavioral traits. Second, combining the advantages of multi-factor and multimodal biometric techniques we develop a hybrid scheme called Multi-factor Authentication based on Multimodal Biometrics (MFA-MB) in order to authenticate and allow access for cloud consumers. Further, a classification of different practical multiple biometrics combinations is given for a wide number of MFA-MB real applications.
  • Keywords
    "Authentication","Cloud computing","Access control","Iris recognition"
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications (AICCSA), 2015 IEEE/ACS 12th International Conference of
  • Electronic_ISBN
    2161-5330
  • Type

    conf

  • DOI
    10.1109/AICCSA.2015.7507257
  • Filename
    7507257