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Safeguarding Educational Integrity through Deepfake Face Detection

Title: Safeguarding Educational Integrity through Deepfake Face Detection
Language: English
Authors: Ahmed J. Obaid; Muthmainnah Muthmainnah; S. Suman Rajest; Muhammad Mujtaba Asad; Luis Miguel Cardoso
Source: IGI Global. 2025.
Availability: IGI Global. 701 East Chocolate Avenue Suite 200, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; e-mail: cust@igi-global.com; Web site: http://www.igi-global.com/
Peer Reviewed: Y
Page Count: 488
Publication Date: 2025
Intended Audience: Administrators; Students
Document Type: Book; Collected Works - General
Education Level: Higher Education; Postsecondary Education
Descriptors: Artificial Intelligence; Deception; Ethics; Trust (Psychology); Video Technology; Influence of Technology; Computer Security; Higher Education; Technological Advancement; Digital Literacy; Misinformation
DOI: 10.4018/979-8-3373-3770-8
ISBN: 979-83-373-3770-8
Abstract: In this era of technological advancements, the rise of AI and deepfakes have become a threat to educational integrity. Hyper realistic synthetic videos and advanced machine learning techniques have the potential to manipulate and distort academic integrity. As online learning and distance learning become more prominent, the need for robust safeguards against identity fraud and content manipulation have become more urgent now than ever. The critical role of deepfake detection technologies in protecting the integrity of education, examining their potential to ensure that institutions can uphold academic standards in a digitally evolving world. "Safeguarding Educational Integrity through Deepfake Face Detection" explores the rising threat of deepfake technology within academic institutions. This book discusses how AI-driven misinformation is and its implications in higher education. Covering topics such as AI, security, and deepfake detection, this book is an excellent resource for academics, higher education administrators, AI developers, and graduate students.
Abstractor: As Provided
Entry Date: 2026
Accession Number: ED680090
Database: ERIC