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Detection of Authenticity – of Content for Forensics Using Forenshield

Publication Type : Conference Paper

Publisher : IEEE

Source : 2023 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)

Url : https://doi.org/10.1109/ccem60455.2023.00021

Campus : Mysuru

School : School of Computing

Department : Computer Science and Engineering

Year : 2023

Abstract : The rampant spread of deepfake videos, a significant threat to media integrity, occurs widely on social media and news platforms. Detecting Deepfakes is a formidable challenge. The proposed study involves a novel algorithm to detect the deepfake. The model comprises of various pre-existing classifiers and a novel algorithm named ForenShield – which detects the deepfakes with an accuracy of 97%. The proposed novel technique works on voting strategy and it outperforms all the pre-existing classifiers, exhibiting the models excellence through the same.

Cite this Research Publication : Priya Govindarajan, Aswin Surendran P, Sanjeev Kumar S, Abebe Tesfahun, Detection of Authenticity - of Content for Forensics Using Forenshield, 2023 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), IEEE, 2023, https://doi.org/10.1109/ccem60455.2023.00021

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