A NEW APPROACH FOR SOCIAL MEDIA NETWORK PRIVACY PROTECTION USING DATA MINING

Ms. P.S.Khorgade; Dr . S. S. Sherekar; Dr. V. M. Thakare

doi:10.17605/OSF.IO/NMEYV

Authors

Ms. P.S.Khorgade PG Department of Computer Science SGBAU,Amravati, India
Dr . S. S. Sherekar PG Department of Computer Science SGBAU,Amravati, India
Dr. V. M. Thakare PG Department of Computer Science SGBAU,Amravati, India

DOI:

https://doi.org/10.17605/OSF.IO/NMEYV

Keywords:

Social media, Social network, Security, Privacy protection.

Abstract

Online Social Networks (OSNs) have become an important part of daily digital interactions for more than half a billion users around the world. Privacy protection model uses type, frequency, and initiation factor of social interactions to calculate relationship strength. This model minimum real-life interaction patterns and makes online social networks more privacy friendly. Social media provided user with a social sharing platform, they can interact with their friends by intentionally sharing their comments /rating on items, block, photos, videos or real time locations. Users in the same social circle (group) have similar behavior, such as similar education background, hobbies, and similar privacy references. The proposed approach to recommend privacy policies for newly uploaded data items or newly added contacts. And facilitate online social network users to group their contacts into social circles with common interests. The proposed social interaction-based audience segregation model for online social networks.