Publishing Search Logs – A Comparative Study Of Privacy Guarantees

NANO SCIENTIFIC RESEARCH CENTRE PVT.LTD.,  AMEERPET, HYD

WWW.NSRCNANO.COM, 09640648777, 09652926926

DOT NET PROJECTS LIST--2013

DOT NET 2013 IEEE PAPERS

Publishing Search Logs – A Comparative Study

Of Privacy Guarantees

Abstract:

            Search engine companies collect the “database of intentions”, the histories of their users’ search queries. These search logs are a gold mine for researchers. Search engine companies, however, are wary of publishing search logs in order not to disclose sensitive information. In this paper we analyze algorithms for publishing frequent keywords, queries and clicks of a search log. We first show how methods that achieve variants of k-anonymity are vulnerable to active attacks. We then demonstrate that the stronger guarantee ensured by differential privacy unfortunately does not provide any utility for this problem. Our paper concludes with a large experimental study using real applications where we compare ZEALOUS and previous work that achieves k-anonymity in search log publishing. Our results show that ZEALOUS yields comparable utility to k−anonymity while at the same time achieving much stronger privacy guarantees.

Existing System:                      

            We show that existing proposals to achieve anonymity in search logs are insufficient in the light of attackers who can actively influence the search log. However, we show that it is impossible to achieve good utility with differential privacy.

Disadvantages:

            Existing work on publishing frequent itemsets often only tries to achieve anonymity or makes strong assumptions about the background knowledge of an attacker

Proposed System:

          The main focus of this paper is search logs, our results apply to other scenarios as well. For example, consider a retailer who collects customer transactions. Each transaction consists of a basket of products together with their prices, and a time-stamp. In this case ZEALOUS can be applied to publish frequently purchased products or sets of products. This information can also be used in a recommender system or in a market basket analysis to decide on the goods and promotions in a store.

Advantages:

                Our results show that ZEALOUS yields comparable utility to k−anonymity while at the same time achieving much stronger privacy guarantees.

Soft ware and hard ware requirements

Hardware Required:                            

System                        :           Pentium IV

Hard Disk                   :           80 GB

RAM                           :           512 MB

Software Required:

O/S                              :           Windows XP.

Language                    :           Asp.Net, c#.

Data Base                    :           Sql Server 2005.

Modules

·         Query Substitution

·         Index Caching

·         Item Set Generation and Ranking