• Sreevidhya J Menon
• Sandy Joseph

In recent times, easy access and use of digital video editing tools become a challenge for forensic video professionals, to prove authenticity accurately in any case of suspected digital video content. Fake video detection aims to expose and test the basic facts about the video file to detect if the video content has been subjected to unscrupulous conduct. The need to test new or more efficient (or blind) Passive Fraudulent video detection methods are gaining value daily. This study has been undertaken to investigate the latest developments in the field of digital video forgery detection. This work is a detailed description of the different techniques used in machine learning methods to detect forged videos and gives researchers a broader perspective on the various aspects of forgery detection

Digital Video Forgery Detection, SVM, Motion Feature, Noise Feature, Machine Learning

"Study on Different Techniques Used In Video Forgery Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.1105-1112, April-2021, Available :http://www.jetir.org/papers/JETIR2104352.pdf

"Study on Different Techniques Used In Video Forgery Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp1105-1112, April-2021, Available at : http://www.jetir.org/papers/JETIR2104352.pdf