• DocumentCode
    3722473
  • Title

    Anti-Counterfeit Scheme Using Monte Carlo Simulation for E-commerce in Cloud Systems

  • Author

    Keke Gai;Meikang Qiu;Hui Zhao;Wenyun Dai

  • Author_Institution
    Dept. of Comput. Sci., Pace Univ., New York, NY, USA
  • fYear
    2015
  • Firstpage
    74
  • Lastpage
    79
  • Abstract
    E-commerce using cloud-based trading platforms has become a popular approach with the growth of global development in recent years. However, the existence of counterfeits on the platform has threatened the benefits of all stakeholders. This paper proposes a novel scheme named Anti-Counterfeit Deterministic Prediction Model (ADPM), which is designed for detecting counterfeits by using Monte Carlo Model (MCM) to predict the potential malicious information in e-commerce. We consider the discriminations of the fake merchandises a crucial issue in preventing counterfeits on the online business platforms. The proposed mechanism provides a paradigm of machine-learning with using a novel algorithm that derives from MCM. The main algorithm used in our proposed mechanism is Monte Carlo Model-based Prediction Analysis Algorithm (M-PAA). Our experiment has evaluated that the proposed approach can provision the predictions of the insecure information in e-commerce.
  • Keywords
    "Predictive models","Prediction algorithms","Monte Carlo methods","Mathematical model","Cloud computing","Algorithm design and analysis","Adaptation models"
  • Publisher
    ieee
  • Conference_Titel
    Cyber Security and Cloud Computing (CSCloud), 2015 IEEE 2nd International Conference on
  • Type

    conf

  • DOI
    10.1109/CSCloud.2015.75
  • Filename
    7371462