Machine Learning system for Access Control in content sharing online social Networks

Abstract: Online social networks (OSNs) have experienced tremendous growth in recent years and become a de facto portal for hundreds of millions of Internet users. These OSNs offer attractive means for digital social interactions and information sharing, but also raise a number of security and privacy issues. The OSNs allow users to restrict access to shared data; Currently they do not provide any mechanism to enforce privacy concerns over data associated with multiple users. One basic issue in today’s Online Social Networks (OSNs) is to give users the power to regulate the messages denote on their own non-public house to avoid the display of unwanted content is displayed. In the existing Apriori algorithm user cannot safeguard his or her blog, because unwanted message causes many problems. To overcome this problem Naive Bayes algorithm is proposed in this project. In the proposed system, the technique applied is novel machine learning algorithm for text classification based on Naive Bayes classifiers. The experimental results obtained in Naive Bayes classifier algorithm has improved accuracy.

Keywords: Data mining, Online Social Networks, Filtering Message, Apriori Algorithm and Naive Bayes Classifier Algorithm.