ReACT_OCRS: An AI-Driven Anonymous Online Reporting System Using Synergized Reasoning and Acting in Language Models

5,500.00
  • Categories: Artificial Intelligence, Cyber Security, Deep Learning, Java, Projects, Python, Web Application
  • Tags: Artificial Intelligence, B.Tech, BTech, BTech CSE, Cyber Security, Deep Learning, Final Year Project, Java, M.Tech, MCA, MCA Project, MTech, MTech CSE, NLP, Python, Research Project, Web Application
  • Includes: Source code, report, PPT, installation support, viva notes

An original final-year project concept for ReACT_OCRS: An AI-Driven Anonymous Online Reporting System Using Synergized Reasoning and Acting in Language Models. The project focuses on cyber security and can be implemented as a working prototype with clear problem definition, system design, implementation, testing, and result analysis. Process: 1. Define the problem scope and user requirements. 2. Collect or prepare the required dataset, modules, or inputs. 3. Design the architecture for the cyber security workflow. 4. Build the core model, application logic. 5. Integrate storage, UI, API as needed. 6. Test using realistic cases and document accuracy, performance, limitations, and future scope. Tech stack: Python, scikit-learn/TensorFlow/PyTorch as applicable, Flask or Streamlit, SQLite/MySQL, Java, Spring Boot/JSP/Servlets, MySQL, HTML/CSS/JavaScript Suitable for: BTech, BTech CSE, Final Year Project, MTech, MTech CSE, Research Project. Main domain tags: Java, Deep Learning, Artificial Intelligence, Python, Cyber Security.

Aim

To implement a final year project with clear input, processing, output, result analysis, and documentation for academic presentation.

Proposed System

The project includes implementation workflow, source code, screenshots, result explanation, report content, and PPT guidance.

Advantages

Ready-to-demo structure, easier viva preparation, clear module explanation, and WhatsApp support for setup doubts.

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