  Advancements in generative models, like Deepfake allows users to imitate a
targeted person and manipulate online interactions. It has been recognized that
disinformation may cause disturbance in society and ruin the foundation of
trust. This article presents DeFakePro, a decentralized consensus
mechanism-based Deepfake detection technique in online video conferencing
tools. Leveraging Electrical Network Frequency (ENF), an environmental
fingerprint embedded in digital media recording, affords a consensus mechanism
design called Proof-of-ENF (PoENF) algorithm. The similarity in ENF signal
fluctuations is utilized in the PoENF algorithm to authenticate the media
broadcasted in conferencing tools. By utilizing the video conferencing setup
with malicious participants to broadcast deep fake video recordings to other
participants, the DeFakePro system verifies the authenticity of the incoming
media in both audio and video channels.
