Digital Security

SPOTIT.AI

SPOTIT.AI is an advanced deepfake detection system redefining the way we ensure media authenticity. Powered by the innovative MesoInception4 model, it delivers high-accuracy detection of manipulated images and videos, seamlessly integrated with Django for a smooth user experience.

Yellow Flower
Yellow Flower
Yellow Flower

My Role

Developer

Duration

6 months

Tools

Python, Machine learning, AI, Django,API

Overview

/Challenge

/Challenge

/Challenge

With the rise of deepfake technology, distinguishing manipulated videos and images has become increasingly critical, posing risks to security, privacy, and trust. Developing a reliable detection system capable of identifying these manipulations with high accuracy was a pressing need.

/Solution

/Solution

/Solution

SPOTIT.AI was created as a sophisticated deepfake detection system, leveraging the MesoInception4 model to achieve high accuracy in identifying altered media. Integrated with Django for seamless application management and connected to the MyriadB server for efficient data handling, SPOTIT.AI addresses the challenge with a robust and scalable solution.

Research

Through an extensive review of deepfake detection techniques, the MesoInception4 model was selected. This model uniquely combines the strengths of MesoNet's compact architecture with Inception modules, enabling it to effectively analyze both local and global features in manipulated media. The research also emphasized integrating a scalable application framework and robust data management system for seamless operation.

High Accuracy Achieved

The SPOTIT.AI system achieved an impressive 90.4% accuracy in detecting deepfakes, validated on a dataset comprising 12,000 real and manipulated images.

High Accuracy Achieved

The SPOTIT.AI system achieved an impressive 90.4% accuracy in detecting deepfakes, validated on a dataset comprising 12,000 real and manipulated images.

High Accuracy Achieved

The SPOTIT.AI system achieved an impressive 90.4% accuracy in detecting deepfakes, validated on a dataset comprising 12,000 real and manipulated images.

Advanced Model Utilization

Advanced Model Utilization

Advanced Model Utilization

Contribution to Digital Security

Contribution to Digital Security

Contribution to Digital Security

Design

The design centered on creating a seamless and intuitive user interface, incorporating secure login functionality, easy uploading of images and videos, and efficient navigation to enhance user engagement and accessibility.

Results

  • Achieved a robust deepfake detection system with 90.4% accuracy on a dataset of 12,000 images.

  • Reduced false positives, enhancing the reliability and precision of detections.

  • Designed an intuitive user interface with secure login and easy navigation.

  • Enabled seamless upload and analysis of images and videos, ensuring a smooth user experience.