THE SOCIAL IMPACT OF GENERATED PHOTOS AND INFORMATION POISONING / SHAANA ABDUL NASSER MOYINAKATH KALATHIL.
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TextPublication details: Kuala Lumpur : Asia Pacific University, 2019Description: 68 pages : illustrations ; 30 cmSubject(s): Machine learning -- Technological innovations | Artificial intelligence -- Computer programsLOC classification: PG-21-0147Dissertation note: A project submitted in partial fulfilment of the award of the BSc. (Hons) in Forensic Computing (APT3F1902FRC). Summary: Recent development of generative adversarial networks (GAN) and machine learning has shocked the world of what AI is capable of achieving in generating by itself a realistic information. Although this is deemed as an accomplishment, but it equally raised concerns on how these technologies can be misused. This paper discusses on how it can be used for the creation of fake photos and its capability of poisoning our data and information. The study will look of how deepfakes and GANs may affect these three security domains – digital security, physical security, and political security.
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Reference
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APU Library Reference Collection | Undergraduate Theses | PG-21-0147 (Browse shelf (Opens below)) | 1 | Not for loan (Restricted access) | 00018651 |
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A project submitted in partial fulfilment of the award of the BSc. (Hons) in Forensic Computing (APT3F1902FRC).
Recent development of generative adversarial networks (GAN) and machine learning has shocked the world of what AI is capable of achieving in generating by itself a realistic information. Although this is deemed as an accomplishment, but it equally raised concerns on how these technologies can be misused. This paper discusses on how it can be used for the creation of fake photos and its capability of poisoning our data and information. The study will look of how deepfakes and GANs may affect these three security domains – digital security, physical security, and political security.
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