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Security and Verification of Server Data Using Frequent Itemset Mining in Ecommerce
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Author(s): Zuber Shaikh (Dr. D. Y. Patil School of Engineering and Technology, Pune, India), Antara Mohadikar (Dr. D. Y. Patil School of Engineering and Technology, Pune, India), Rachana Nayak (Dr. D. Y. Patil School of Engineering and Technology, Pune, India)and Rohith Padamadan (Dr. D. Y. Patil School of Engineering and Technology, Pune, India)
Copyright: 2017
Volume: 8
Issue: 1
Pages: 13
Source title:
International Journal of Synthetic Emotions (IJSE)
DOI: 10.4018/IJSE.2017010103
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Abstract
Frequent itemsets refer to a set of data values (e.g., product items) whose number of co-occurrences exceeds a given threshold. The challenge is that the design of proofs and verification objects has to be customized for different data mining algorithms. Intended method will implement a basic idea of completeness verification and authentication approach in which the client will uses a set of frequent item sets as the evidence, and checks whether the server has missed any frequent item set as evidence in its returned result. It will help client detect untrusted server and system will become much more efficiency by reducing time. In authentication process CaRP is both a captcha and a graphical password scheme. CaRP addresses a number of security problems altogether, such as online guessing attacks, relay attacks, and, if combined with dual-view technologies, shoulder-surfing attacks.
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