DeHiDe: Deep Learning-based Hybrid Model to Detect FakeNews using Blockchain

Agrawal, P. and Peri, S. and et al, . (2021) DeHiDe: Deep Learning-based Hybrid Model to Detect FakeNews using Blockchain. In: 22nd International Conference on Distributed Computing and Networking 2021, 5 January 2021 through 8 January 2021, Virtual, Online.

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The surge in the spread of immensely powerful deep-fakes, pseudo-news, misleading information, lies, propaganda, and false facts, frequently known as fake news, raised questions concerning social media's influence in today's fast-moving society. It is challenging to overcome fake news in traditional centralized systems. Blockchain technology can help in contending with such problems. A novel idea of DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain is presented in this paper. DeHiDe is a blockchain-based framework for legitimate news sharing by filtering out the fake news. It combines the benefit of blockchain with an intelligent deep learning model to reinforce robustness and accuracy in combating fake news's hurdle.

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IITH Creators:
IITH CreatorsORCiD
Peri, Sathya 0000-0001-5633-5027
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Centralized systems, Hybrid model, Learning models, Misleading informations, Social media
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: Mrs Haseena VKKM
Date Deposited: 09 Dec 2021 06:45
Last Modified: 08 Mar 2022 11:49
Publisher URL:
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