Assessfy Capstone Lab Advanced 6 milestones 100 marks

Cloud-Native Fake News and Deepfake Detection Web Platform for Indian Media Integrity

Branch: Information Technology Type: Industry-applied final-year Major Project Standard: Mumbai University Rev-2019 'C' Scheme (Major Project I + II) Group: up to 4 students Assessment: 6 review-based milestones (100 marks)

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About this project

Objective: To engineer and deploy a scalable web service that detects and flags fake news articles and video deepfakes specific to the Indian information ecosystem.

Fake news and deepfakes are an escalating threat to public trust, social harmony, and democratic processes in India, impacting citizens, media outlets, and government agencies by enabling misinformation to spread rapidly online.

This project proposes an end-to-end cloud-native web platform that utilizes machine learning and deep learning models to analyze news articles and multimedia content for authenticity, offering real-time detection and alerting for fake news and video deepfakes. The solution leverages state-of-the-art NLP models trained on Indian news datasets and GAN-based deepfake detection for video, with a user-friendly interface and RESTful APIs for integration with media or civic-tech portals.

Key deliverables include: a responsive web application for news and video uploads, backend microservices for AI-based verification, integration with credible Indian fact-checking databases, live demo with sample misinformation scenarios, and detailed documentation including cost analysis and deployment on a public cloud (e.g., AWS/GCP/Azure).

By supporting journalists, policy-makers, and the public in quickly identifying misinformation, this platform contributes to media integrity, civic awareness, and responsible technology adoption at scale across India.

Milestones

1. Synopsis & Problem Definition (Stage-I Review-1)

10 marks 24d

Deliver a detailed project synopsis outlining the fake news/deepfake problem in India, engineering objectives, and initial feasibility; reviewed by supervisor approval.

2. Literature / Market Survey & Requirement Analysis (Stage-I Review-2)

12 marks 27d

Present a market and literature survey of existing solutions, survey Indian datasets, and define user/system requirements; evaluated via documentation and oral review.

3. System Design, Methodology & Cost Analysis (Stage-I close)

16 marks 30d

Submit architecture diagrams, technology stack selection, model design, and cost analysis for cloud deployment; assessed through design review and cost justification.

4. Implementation / Fabrication of Working Model (Stage-II Review-1)

28 marks 44d

Develop the platform, train/deploy ML models, complete frontend/backend integration, and demonstrate a working web prototype; demonstration and code review conducted.

5. Testing, Results & Validation (Stage-II Review-2)

20 marks 32d

Perform functional testing with real and synthetic data, validate detection rates, document results and limitations; reviewed with test cases and result analysis.

6. Report, Paper & Demonstration / Oral Defense (Stage-II final Oral & Practical)

14 marks 28d

Submit final project report, IEEE paper, and demonstrate the live system to examiners; evaluated on documentation quality and oral defense.

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Upcoming sessions

Session	Window	Enrolled
Cloud-Native Fake News and Deepfake Detection Web Platfor...	11 Jun 2026 to 10 Jun 2028	0

Skills you'll learn

CapstoneFinal-year projectMajor projectInformation TechnologyMachine learning and deep learning for NLP and computer visionCloud-native web application development (frontend and backend)Containerization and deployment using Docker and KubernetesRESTful API design and integration with external platformsTesting and validation using public datasets (e.g.India-specific fake news and deepfake datasets)Project teamwork and agile software engineering practicesTechnical documentation and preparation of reports/papers

Tools used

Python (Flask/Django for backendTensorFlow/PyTorch for ML models)React.js or Angular for frontend developmentAWS/GCP/Azure for cloud deploymentDocker and Kubernetes for containerization and orchestrationOpenCV and pre-trained GAN detectors for deepfake analysisIndian fake news datasets (e.g.IndiaTodayFactlyFake News Detection Data)REST API standards and OpenAPI documentation

Prerequisites

Artificial Intelligence and Machine LearningWeb Programming and Database ManagementCloud ComputingComputer Networks and Information Security

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