A framework for social media network to curtail the banned and abused images

Social Media Networks (SMN) are slanted to a load of oddities nowadays. There is no incorporated control to screen and separate the activities followed in the SMNs. Along these lines we have proposed a framework to analyze and limit to the substance being partaken in the SMNs. As a part of the framework, two algorithms namely CBI and CAI is proposed for banned and abused images respectively. Support Vector Machine (SVM) classifier is adopted to identify and restrict the abused images being shared. The confined but unabused pictures are filtered using K-means clustering algorithm and Harrish-Stephens corner point detection algorithm. The proposed framework is implemented as a model SMN called SatbookLTE, which effectively diminishes the mishandled substance being partaken as pictures. The system analyzes the content being shared through the SMN without influencing the privacy of the client.