Inference Attack Prevention Model on Social Networking Application Data Sanitization Method on User’s Profile
Abstract
Nowadays social media
is becoming very popular and used for marketing as per users profile. But for
this, social networking sites share user’s data with other marketing companies
and it is possible the third party companies can use user’s private data.
Significant factor in multimedia mobile systems is social network, where users
can send their photos, videos and other media files. On the other hand, the
information (e.g., user Bio, posts, etc. ) on social media platforms shared
usually reveals lots of users private information. That can be mined and
mistreated for the malicious reasons. To tackle privacy concerns, privacy
preserving mechanisms adopted by many social network service providers, e.g.
hiding users profiles, anonym zing user identity, etc. As an attributes result
from user profiles are usually set such that it could be accessed to prevent
personal information outflow only by friends. To understand the hidden
attributes to the numerous efficiency of current privacy protecting mechanisms
different attacks have been proposed. Almost solutions are based on the social
networking links along with users or their behaviors. The proposed work is an
inference attack prevention model on social networking application to solve
prevention problem. To prevent inference attack we proposed data sanitization
method on user’s profile.
Country : India
1 Veernala Sireesha
Assistant Professor, Department of Computer Science And Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
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