• Sneha V Masaguppi
• S.H Manjula

Sharing any form of information is now easier. There are many social media sites that allow people to communicate with each other or share any information through these kinds of sites. There is a lot of advantages in using these sites except the major concern is security. The technique of inferring anything about a user's characteristics from the form and substance of their writing present in a collection of data is known as cyber security forensics. The rise of social media as a key medium of communication has thrown into question the long-held belief that forensic investigators will have access to form writing. We presented the Sensitive Message Blocking System (SMBS) in this system, which extracts characteristics from very short samples of text and uses scalable supervised learning to train Sensitive-Keyword models and make predictions to classify whether the message is sensitive or non-sensitive. If the message is sensitive then it will classify whether it is Less Sensitive, Medium Sensitive, or More Sensitive. There is a decision-making system that will decide whether to post the message on the wall or not.

Sensitive Message Blocking System, Classifier, Supervised Model

"Forensic Cyber Security in Sensitive Message Blocking for Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 9, page no.d442-d448, September-2021, Available :http://www.jetir.org/papers/JETIR2109349.pdf

"Forensic Cyber Security in Sensitive Message Blocking for Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 9, page no. ppd442-d448, September-2021, Available at : http://www.jetir.org/papers/JETIR2109349.pdf