Is it real? A study on detecting deepfake videos

Nyein Nyein Thaw; Thin July; Aye Nu Wai; Dion Hoe Lian Goh; Alton Y.K. Chua

doi:10.1002/pra2.366

Is it real? A study on detecting deepfake videos

Nyein Nyein Thaw^*, Thin July, Aye Nu Wai, Dion Hoe Lian Goh, Alton Y.K. Chua

^*Corresponding author for this work

Nanyang Technological University

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

We present an exploratory study of how people detect deepfake videos. Through watching a set of real and fake videos, and semi-structured interviews, participants identified a set of characteristics such as blurred faces and unnatural voices, present in deepfake videos. A list of verification strategies, including checking other sources and repeated viewing, were also derived.

Original language	English
Article number	e366
Journal	Proceedings of the Association for Information Science and Technology
Volume	57
Issue number	1
DOIs	https://doi.org/10.1002/pra2.366
Publication status	Published - 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
83rd Annual Meeting of the Association for Information Science & Technology October 25-29, 2020. Author(s) retain copyright, but ASIS&T receives an exclusive publication license.

ASJC Scopus Subject Areas

General Computer Science
Library and Information Sciences

Keywords

Deepfake videos
detection
verification strategies

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10.1002/pra2.366

Cite this

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AU - July, Thin

AU - Wai, Aye Nu

AU - Goh, Dion Hoe Lian

AU - Chua, Alton Y.K.

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PY - 2020

Y1 - 2020

N2 - We present an exploratory study of how people detect deepfake videos. Through watching a set of real and fake videos, and semi-structured interviews, participants identified a set of characteristics such as blurred faces and unnatural voices, present in deepfake videos. A list of verification strategies, including checking other sources and repeated viewing, were also derived.

AB - We present an exploratory study of how people detect deepfake videos. Through watching a set of real and fake videos, and semi-structured interviews, participants identified a set of characteristics such as blurred faces and unnatural voices, present in deepfake videos. A list of verification strategies, including checking other sources and repeated viewing, were also derived.

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KW - detection

KW - verification strategies

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Is it real? A study on detecting deepfake videos

Abstract

Bibliographical note

ASJC Scopus Subject Areas

Keywords

Access to Document

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