dc.contributor.author |
Botha, Johannes G
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|
dc.contributor.author |
Pieterse, Heloise
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|
dc.date.accessioned |
2021-04-06T09:09:18Z |
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dc.date.available |
2021-04-06T09:09:18Z |
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dc.date.issued |
2020-03 |
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dc.identifier.citation |
Botha, J.G. & Pieterse, H. 2020. Fake news and deepfakes: A dangerous threat for 21st century information security. http://hdl.handle.net/10204/11946 . |
en_ZA |
dc.identifier.isbn |
978-1-912764-53-2 |
|
dc.identifier.uri |
https://search.proquest.com/openview/67064446abb3dec6bea4c680d5aa3a31/1?cbl=396500&pq-origsite=gscholar
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|
dc.identifier.uri |
DOI: 10.34190/ICCWS.20.085
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|
dc.identifier.uri |
http://hdl.handle.net/10204/11946
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|
dc.description.abstract |
Fake news, often referred to as junk news or pseudo-news, is a form of yellow journalism or propaganda created with the purpose of distributing deliberate disinformation or false news using traditional print or online social media. Fake news has become a significant problem globally in the past few years. It has become common to find popular individuals and even members of the state using misinformation to influence individuals’ actions whether consciously or subconsciously. The latest trend is using Artificial Intelligence (AI) to create fake videos known as “deepfakes”. Deepfake, a portmanteau of “deep learning” and “fake”, is an artificial intelligence-based human image synthesis technique. It is used to combine and superimpose existing images and videos onto source images or videos using a machine learning technique called a “generative adversarial network” (GAN). The combination of the existing and source videos results in a fake video that shows a person or persons performing an action at an event that never occurred in reality. This paper provides an overview of the currently available creation and detection techniques to identify fake news and deepfakes. The outcome of this paper provides the reader with an adequate literature review that summarises the current state of fake news and deepfakes, with special attention given to the tools and technologies that can be used to both create and detect fake news or deepfake material. |
en_US |
dc.format |
Fulltext |
en_US |
dc.language.iso |
en |
en_US |
dc.source |
Proceedings of the 15th International Conference on Cyber Warfare and Security, Norfolk, Virginia, 12-13 March 2020 |
en_US |
dc.subject |
Artificial intelligence |
en_US |
dc.subject |
Deepfakes |
en_US |
dc.subject |
Detection |
en_US |
dc.subject |
Fake news |
en_US |
dc.subject |
Machine-learning |
en_US |
dc.title |
Fake news and deepfakes: A dangerous threat for 21st century information security |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.description.pages |
10pp |
en_US |
dc.description.note |
Presented at the 15th International Conference on Cyber Warfare and Security, Norfolk, Virginia, 12-13 March 2020 |
en_US |
dc.description.cluster |
Defence and Security |
|
dc.description.impactarea |
Information Security Centre |
en_US |
dc.identifier.apacitation |
Botha, J. G., & Pieterse, H. (2020). Fake news and deepfakes: A dangerous threat for 21st century information security. http://hdl.handle.net/10204/11946 |
en_ZA |
dc.identifier.chicagocitation |
Botha, Johannes G, and Heloise Pieterse. "Fake news and deepfakes: A dangerous threat for 21st century information security." <i>Proceedings of the 15th International Conference on Cyber Warfare and Security, Norfolk, Virginia, 12-13 March 2020</i> (2020): http://hdl.handle.net/10204/11946 |
en_ZA |
dc.identifier.vancouvercitation |
Botha JG, Pieterse H, Fake news and deepfakes: A dangerous threat for 21st century information security; 2020. http://hdl.handle.net/10204/11946 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Botha, Johannes G
AU - Pieterse, Heloise
AB - Fake news, often referred to as junk news or pseudo-news, is a form of yellow journalism or propaganda created with the purpose of distributing deliberate disinformation or false news using traditional print or online social media. Fake news has become a significant problem globally in the past few years. It has become common to find popular individuals and even members of the state using misinformation to influence individuals’ actions whether consciously or subconsciously. The latest trend is using Artificial Intelligence (AI) to create fake videos known as “deepfakes”. Deepfake, a portmanteau of “deep learning” and “fake”, is an artificial intelligence-based human image synthesis technique. It is used to combine and superimpose existing images and videos onto source images or videos using a machine learning technique called a “generative adversarial network” (GAN). The combination of the existing and source videos results in a fake video that shows a person or persons performing an action at an event that never occurred in reality. This paper provides an overview of the currently available creation and detection techniques to identify fake news and deepfakes. The outcome of this paper provides the reader with an adequate literature review that summarises the current state of fake news and deepfakes, with special attention given to the tools and technologies that can be used to both create and detect fake news or deepfake material.
DA - 2020-03
DB - ResearchSpace
DP - CSIR
J1 - Proceedings of the 15th International Conference on Cyber Warfare and Security, Norfolk, Virginia, 12-13 March 2020
KW - Artificial intelligence
KW - Deepfakes
KW - Detection
KW - Fake news
KW - Machine-learning
LK - https://researchspace.csir.co.za
PY - 2020
SM - 978-1-912764-53-2
T1 - Fake news and deepfakes: A dangerous threat for 21st century information security
TI - Fake news and deepfakes: A dangerous threat for 21st century information security
UR - http://hdl.handle.net/10204/11946
ER - |
en_ZA |
dc.identifier.worklist |
24180 |
en_US |