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
Link To Document :
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