Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2024.2400640
Securing online integrity: a hybrid approach to deepfake detection and removal using Explainable AI and Adversarial Robustness Training
R. Uma Maheshwari
; Department of Electronics and Communication Engineering, Hindusthan Institute of Technology, Coimbatore, India
*
B. Paulchamy
; Department of Electronics and Communication Engineering, Hindusthan Institute of Technology, Coimbatore, India
* Dopisni autor.
Sažetak
As deepfake technology becomes increasingly sophisticated, the proliferation of manipulated
images presents a significant threat to online integrity, requiring advanced detection and mitigation strategies. Addressing this critical challenge, our study introduces a pioneering approach
that integrates Explainable AI (XAI) with Adversarial Robustness Training (ART) to enhance
the detection and removal of deepfake content. The proposed methodology, termed XAI-ART,
begins with the creation of a diverse dataset that includes both authentic and manipulated
images, followed by comprehensive preprocessing and augmentation. We then employ Adversarial Robustness Training to fortify the deep learning model against adversarial manipulations.
By incorporating Explainable AI techniques, our approach not only improves detection accuracy but also provides transparency in model decision-making, offering clear insights into how
deepfake content is identified. Our experimental results underscore the effectiveness of XAI-ART,
with the model achieving an impressive accuracy of 97.5% in distinguishing between genuine
and manipulated images. The recall rate of 96.8% indicates that our model effectively captures
the majority of deepfake instances, while the F1-Score of 97.5% demonstrates a well-balanced
performance in precision and recall. Importantly, the model maintains high robustness against
adversarial attacks, with a minimal accuracy reduction to 96.7% under perturbations.
Ključne riječi
Adversarial attacks; Adversarial Robustness Training (ART); deepfake technology; detection strategies; digital content integrity; Explainable AI (XAI)
Hrčak ID:
326343
URI
Datum izdavanja:
10.9.2024.
Posjeta: 0 *