Department of Computer Science and Engineering Sree Buddha College of Engineering, Alappuzha, IndiaDepartment of Computer Science and Engineering Sree Buddha College of Engineering, Alappuzha, India
作者
Sofia Sayed;Reeba. R
摘要
This paper proposes an advanced method for providing privacy protection in explicit feedback system. At present the usage of search engine are increased rapidly because of the huge websites and data. The main purpose of search engine is to provide appropriate result to the user according to their requirements. Although it provide relevant information to the users but it doesn't provide any security for user profile. So there is a possibility for the leakage of users profile details. During search time they are worried for the leakage of their private information. Many method are available to avoid such a situation but its main drawback is all based on server side protection. Here introduced a client side technique called user customizable privacy search procedure (UPS) using Greedy algorithms for minimizing the privacy risk. We present two greedy algorithms, namely GreedyDP and GreedylL, for runtime generalization of user profile. Here introduced a closed high utility method, which is used to find the most used items in a profile tree in terms of the cost function of transaction and privacy is applied based on it. The system is experimentally checked by constructing a Profile tree from a web environment and testing queries in it. At last an evaluation is also done with GreedyDP and CHUD GreedyDP.
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关键词
Privacy;Personalised web search;internal utility;incompatible metrics;closed high utility itemsets;User Customisable Privacy Preserving Search
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