Generative adversarial networks (GANs) and diffusion models have dramatically advanced deepfake technology, and its threats to digital security, media integrity, and public trust have increased rapidly. This research explored zero-shot deepfake detection – an emerging method even when the models have never seen a particular deepfake variation. In this work, we studied self-supervised learning, transformer-based zero-shot classifier, generative model fingerprinting, and meta-learning techniques that better adapt to the ever-evolving deepfake threat. In addition, we suggested AI-driven prevention strategies that mitigated the underlying generation pipeline of the deepfakes before they occurred. They consisted of adversarial perturbations for creating deepfake generators, digital watermarking for content authenticity verification, real-time AI monitoring for content creation pipelines, and blockchain-based content verification frameworks. Despite these advancements, zero-shot detection and prevention faced critical challenges such as adversarial attacks, scalability constraints, ethical dilemmas, and the absence of standardized evaluation benchmarks. These limitations were addressed by discussing future research directions on explainable AI for deepfake detection, multimodal fusion based on image, audio, and text analysis, quantum AI for enhanced security, and federated learning for privacy-preserving deepfake detection. This further highlighted the need for an integrated defense framework for digital authenticity that utilized zero-shot learning in combination with preventive deepfake mechanisms. Finally, we highlighted the important role of interdisciplinary collaboration between AI researchers, cybersecurity experts, and policymakers to create resilient defenses against the rising tide of deepfake attacks.
Zero-shot visual deepfake detection: can ai predict and prevent fake content before it is created? Available to Purchase
Ayan Sar Student Member, IEEE, is currently pursuing a PhD from the School of Computer Science, UPES Dehradun. He has a Bachelor of Technology in Computer Science at the School of Computer Science, UPES Dehradun, with a specialization in Big Data, Artificial Intelligence, and Machine Learning. His research interests include computer vision, geoinformatics, cybersecurity, and applied AI solutions.
Ayan has authored and co-authored several research papers published in prestigious venues such as IEEE and Springer Nature, focusing on AI applications, computer vision, geospatial intelligence, and computational security. His academic rigor is complemented by hands-on industry experience, including an internship at Microsoft India R&D Pvt. Ltd., where he contributed to optimizing database queries and developing spam detection models for Microsoft 365 Copilot.
He is a National Record Holder in the India Book of Records (Academic Category) and a Gold Medalist in the International Mathematics Olympiad, underscoring his dedication to academic excellence and innovation. He has authored first-author publications in FnT Signal Processing, IEEE Access, Discover Food, Engineering Applications of Artificial Intelligence, NeuroComputing, and co-authored many other peer-reviewed high-quality journals, along with Core B and A conferences.
Sampurna Roy Student Member, IEEE, is currently pursuing a Bachelor of Technology in Computer Science and Engineering at the University of Petroleum and Energy Studies (UPES), Dehradun, specializing in Artificial Intelligence, Machine Learning, Cybersecurity, and UI/UX Design. She has a strong foundation in deep learning algorithms and natural language processing, with a keen interest in integrating AI-driven technologies and computer vision into practical, real-world applications.
Her notable projects include Comic Craft, a creative storytelling platform featuring automated character generation and narrative flow based on user input, and Emotion Analysis through Voice, a system designed to detect mental health patterns through vocal data. She also has experience in frontend development using Node.js and React, complemented by her growing expertise in UI/UX design for building intuitive and visually engaging user interfaces.
Sampurna has gained hands-on experience through internships at Quality AI and PortWol, where she worked on developing machine learning models and enhancing user interface designs. She has authored first-author publications in FnT Computer Graphics and Vision, IEEE Transactions on AgriFood Electronics, NeuroComputing and many other peer-reviewed high-quality journals along with Core B and A conferences.
Tanupriya Choudhury Senior Member, IEEE, received his B.Tech. in Computer Science and Engineering from West Bengal University of Technology, Kolkata (2004–2008), and his M.Tech. in Computer Science and Engineering from Dr. M.G.R. University, Chennai (2008–2010). He earned his Ph.D. from Jagannath University, Jaipur, in 2016.
With over 15 years of experience in teaching and research, he is currently a Professor at the University of Petroleum and Energy Studies (UPES), Dehradun, India, and a Visiting Professor at Daffodil International University, Bangladesh. He has previously served at several prestigious institutions, including Symbiosis International Deemed University, Graphic Era Hill University (as Research Professor), and Amity University, where he was Assistant Professor (Grade-III) and International Department Head. He also held academic and industry roles at Dronacharya College of Engineering, Lingaya’s University, BBDIT, and Syscon Solutions Pvt. Ltd., among others.
His research interests include AIML, Deep Learning, Human Computing, Soft Computing, Cloud Computing, and Data Mining. A prolific innovator, he has filed 25 patents and received 16 software copyrights from the Ministry of Education (formerly MHRD), India. He has actively contributed to numerous national and international conferences as a speaker and participant.
Dr. Choudhury holds lifetime membership with IETA (International Engineering & Technology Association) and is affiliated with several professional bodies, including IEEE, IET (UK), and other technical societies. He serves as a Technical Advisor to multiple corporate organizations such as Deetya Soft Pvt. Ltd., Noida, IVRGURU, and Mydigital360. He is also the Honorary Secretary of the Indian Engineering Teachers’ Association (IETA-India) and holds Senior Advisory roles in the INDO-UK Confederation of Science, Technology and Research Ltd., London, UK, and the International Association of Professional and Fellow Engineers, Delaware, USA.
Ajith Abraham Senior Member, IEEE, received the B.Tech. degree in Electrical and Electronics Engineering from the University of Calicut in 1990, the M.S. degree from Nanyang Technological University, Singapore, in 1998, and the Ph.D. degree in Computer Science from Monash University, Melbourne, Australia, in 2001.
He is currently serving as the Vice Chancellor of Bennett University, India. Prior to this, he held several notable academic leadership positions, including Dean of the Faculty of Computing and Mathematical Sciences at FLAME University, Pune, and Founding Director of the Machine Intelligence Research Laboratories (MIR Labs), USA—an international, not-for-profit scientific research network fostering innovation and excellence in AI by bridging academia and industry.
Dr. Abraham has held professorial roles worldwide, including positions as a Professor of Artificial Intelligence at Innopolis University, Russia, and as the Yayasan Tun Ismail Mohamed Ali Professorial Chair of Artificial Intelligence at UCSI University, Malaysia.
He is an internationally renowned researcher with a multi-disciplinary focus, having authored or co-authored over 1500 research publications, including more than 100 books across various domains of computer science. His work has been widely recognized, with one of his books translated into Japanese, and several articles translated into Russian and Chinese. His scholarly impact is reflected in over 57,000 citations and an H-index exceeding 115 (Google Scholar).
Dr. Abraham has delivered over 250 plenary talks and tutorials across 20+ countries. From 2008 to 2021, he chaired the IEEE Systems, Man, and Cybernetics Society’s Technical Committee on Soft Computing, comprising over 200 members. He served as the Editor-in-Chief of Engineering Applications of Artificial Intelligence (EAAI) from 2016 to 2021 and continues to serve on the editorial boards of over 15 Thomson ISI-indexed journals. He also held the position of IEEE Computer Society Distinguished Lecturer for Europe from 2011 to 2013.
