Deepfake Detection: An Exploration of Deepfake Mediums

Rishita Milind Kapile; Rajiv Suresh Surgoniwar; Swati More

Deepfake Detection: An Exploration of Deepfake Mediums

Author(s)	Rishita Milind Kapile, Rajiv Suresh Surgoniwar, Swati More
Country	India
Abstract	The rapid advancement of deepfake technology, powered by artificial intelligence, has intensified the challenge of distinguishing authentic media from sophisticated synthetic manipulations, posing critical risks to digital security and trust. This paper presents a Full-Stack Deepfake Detection Application that leverages a 10-layer Deep Convolutional Neural Network (CNN) to identify deepfake images with exceptional accuracy. The model architecture integrates dilated convolutions to capture intricate spatial artifacts and employs dropout regularization (rate = 0.5) to mitigate overfitting, achieving robust generalization. Trained on a diverse dataset of real and synthetic images, the system attains >99.9% training accuracy and >99% validation accuracy, demonstrating high reliability in detecting state-of-the-art deepfakes. The application is implemented as an end-to-end solution, combining TensorFlow for model training, FastAPI for backend inference, and React.js for an intuitive frontend interface, enabling real- time image analysis. Users can upload media via a web interface and receive instantaneous classification results, supported by a confidence score. This research provides a helpful instrument to fight media scams, theft of identities, and disinformation by handling adaptability, automated processes, and real-time performance. The high accuracy and modular design of the suggested system highlight its potential for use in security- critical settings, boosting confidence in the legitimacy of digital media. Future updates may expand the reach of detection to incorporate asymmetrical attack resilience and audiovisual deep fakes.
Keywords	Deepfake Detection, Convolutional Neural Network (CNN), Dilated Convolutions, Dropout Regularization, Synthetic Media Manipulation, Binary Classification, Real-Time Image Processing, Digital Security, Media Authenticity, Deep Learning, Image Preprocessing, Scalable Systems.
Field	Engineering
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-16

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Deepfake Detection: An Exploration of Deepfake Mediums

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