Detecting Deepfakes in Healthcare: A Review and Proposed Solution

Document Type

Conference Proceeding

Source of Publication

2024 International Conference on Engineering and Emerging Technologies (ICEET)

Publication Date

12-28-2024

Abstract

The widespread use of Deepfake technology presents serious challenges to the integrity and security of healthcare systems. This study provides a detailed review of Deepfake de-tection methods designed particularly for the healthcare domain. We investigate the present methodologies, privacy concerns, and data security risks associated with Deepfakes in medical contexts. Based on a thorough analysis of the current literature, we offer a new approach framework for healthcare-specific Deepfake detection that incorporates powerful machine learning algorithms and privacy-preserving strategies. We highlight research gaps, challenges, and future possibilities for research in this crucial domain, emphasizing the need for reliable, ethical, and adaptive Deepfake detection systems in healthcare.

ISBN

979-8-3315-3289-5

Publisher

IEEE

Volume

00

First Page

1

Last Page

6

Disciplines

Computer Sciences

Keywords

Deepfake detection, Healthcare systems, Privacy concerns, Data security, Machine learning

Indexed in Scopus

no

Open Access

no

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