Covering the Sensitive Subjects to Protect Personal Privacy in Personalized Recommendation

Abstract

Covering the Sensitive Subjects to Protect Personal Privacy The rapid development of the Internet leads to an explosive increase in the quantity of information, which leads to a serious problem of information overload and thus significantly reduces the use of information efficiency.projects on Covering the Sensitive Subjects Currently, personalized recommendation has achieved great success in many fields of application (typically e-commerce). Almost all large-scale ecommerce sites (such as Amazon and Jingdong) have introduced personalized recommendations to a variable extent.

Conclusion

We proposed an approach to protecting users ‘ personal privacy when using a personalized recommendation service, the basic idea of which is to construct a group of fake preferential profiles to cover sensitive subjects in the user preferential profile and, in turn, to protect them.

Projects on Covering the Sensitive Subjects We used a client-based system framework that requires not only no change to existing recommendation algorithms, but also no compromise on the accuracy of recommendation results.

Finally,both theoretical analysis and experimental evaluation have demonstrated the effectiveness of our approach,it can generate a group of good-quality fake preference profiles that not only have high feature distribution similarities with the genuine user preference profile (to hide the genuine profile),but can also be used to effectively reduce the risk of user sensitivity exposure.

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