| Project Overview | This project direction is based on recent Text-to-SQL, database-assistant, and LLM-driven data-access research. The work can convert natural-language questions into database queries, explain SQL, generate ER diagrams, or support secure database analytics. The reference paper, 'Generative AI in Cybersecurity', provides the academic base for the topic. Instead of copying the paper abstract directly, this page keeps the same research intent in a safe paraphrased form: the system supports security analysis by classifying threats, summarizing reports, or detecting abnormal behaviour from logs or traffic. The final student implementation can include dataset preparation, model/API integration, dashboard or app interface, result explanation, and a short documentation-ready workflow. |
|---|---|
| Research Paper Title | Generative AI in Cybersecurity |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2024 |
| Project Area | Database Management Systems |
| Project Type | Database Project |
| Required Tools / Software | MySQL/PostgreSQL, Python, LangChain/LlamaIndex, Vector DB, Streamlit/React |
| Main Features / Working Principle | Collect or upload relevant data, preprocess it, apply an AI/ML/LLM/RAG/software workflow, and present the result through a dashboard or application interface for Database Management Systems. |
| Expected Output | A working B.Tech project prototype for Database Management Systems with input, processing, result display, and explanation/report sections. |
| Possible Add-ons | Admin panel, PDF report export, model comparison, source citations, login system, WhatsApp help button, and deployment on cloud/hosting. |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "Secure Database Access Anomaly Detection System" in "Computer Science & Engineering" |
This B.Tech Computer Science & Engineering project resource connects a recent research direction with a practical implementation plan, tools, expected output, and possible extensions.
