Detecting Fake Videos Using Block Chain and Smart Contracts
Swapnali N. Tambe1, A.B. Pawar2
1Swapnali N. Tambe, Department of Computer Engineering, Sanjivani Ruler Education Society, Kopargaon (Maharashtra), India.
2Dr. A.B Pawar, Department of Computer Engineering, Sanjivani Engineering College, Kopargoan (Maharashtra), India.
Manuscript received on 19 January 2020 | Revised Manuscript received on 02 February 2020 | Manuscript Published on 05 February 2020 | PP: 209-213 | Volume-8 Issue-4S5 December 2019 | Retrieval Number: D10491284S519/2019©BEIESP | DOI: 10.35940/ijrte.D1049.1284S519
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Rapid growth of agile gadgets has led to tremendous increase in digital media utilization, mostly for mobile video in ease of marketing. As encryption provides better user confidentiality and perseveration, greater number of online movement is associated with end-to-end encryption form. Irrevlant content such as unreal, violent and unconstitutional videos are being circulated online without being identified its truthfulness creating a platform for intruders and attackers. It is necessary for users to identify and report the contents of the video. Sometimes these videos act as evidence in courts to prove the guilty and the proper state and contents recorded in it .We aim a system to detect and classify the video’s truthfulness to solve these problems. A detailed collection of studies has been toted to demonstrate the efficacy of new program over current literature.
Keywords: Network Surveillance, Convolution Neural Network (CNN), Propaganda Videos.
Scope of the Article: Block Chain-Enabled IoT Device and Data Security and Privacy