Final year project presentation 4th year

Final year project presentation of 4th year

1. SHRI SAI SHIKSHAN SANSTHA’S NAGPUR INSTITUTE OF TECHNOLOGY, NAGPUR Department of Information Technology 2025-2026 Session 2025-26 Final Year Project Progress Seminar -2 Title:- Mindguard : Dynamic Alert System     Project Members 1) Mr. Amar Surushe 2) Mr. Vishal Ghanwat 3) Mr. Irfan Shaikh 4) Ms. Gayatri Patange 5) Ms. Sakshi Patil Guided by Prof. Dhananjay Kondekar Information Technology Department @ NIT,Nagpur

2. Introduction The Dynamic Alert System is a security application that analyzes user download behavior to mitigate threats proactively. It addresses user tendencies to ignore initial warnings by calculating a dynamic risk score from their actions. If a user ignores a first-level risk alert , the system does not stop. On the next risky attempt , a more severe warning is generated. This approach helps adapt to user carelessness and It prevents breaches caused by “warning fatigue.” NIT,Nagpur

3. Objectives NIT,Nagpur To track and log all user file download attempts and ignored warnings. To implement a BehaviorTracker that calculates a dynamic risk score based on user actions . To design an escalating alert system (Warning, High Risk, Critical) that becomes more severe as risk increases. To automatically block downloads when a user's behavior is classified as critically dangerous. To provide a user interface for simulating and testing the system's adaptive responses.

4. We propose a web-based Dynamic Alert System that actively monitors user file download behavior to proactively mitigate threats The core of the system is a server-side BehaviorTracker module that analyzes user patterns and actions, such as ignored warnings. This module calculates a dynamic risk score for each user session. Based on this score, the system generates escalating alerts (Warning, High Risk, Critical) At the highest risk level, the system will automatically block the download to prevent a potential breach caused by user carelessness or "warning fatigue". Proposed Solution NIT,Nagpur

5. Methodology NIT,Nagpur The project is built on a client-server architecture , communicating via a RESTful API using JSON for data exchange. Back-End: Powered by Node.js/Express.js , leveraging its asynchronous nature to handle concurrent user sessions and real-time data processing efficiently. . Front-End: A dynamic and responsive user interface built with HTML, CSS, and JavaScript Core Logic ( BehaviorTracker ): The server-side BehaviorTracker class analyzes user patterns to determine the correct security response. It analyzes behaviors like ignored security alerts to calculate a dynamic risk score . Based on this score, it triggers an adaptive security response , such as requiring MFA or terminating the session.

6. Block Diagram/ Circuit Diagram/ Flowcharts NIT,Nagpur

7. Implementation and Working of Software Model NIT,Nagpur

8. Outcomes / Results NIT,Nagpur

9. Progress NIT,Nagpur The Dynamic Alert System project successfully achieves its goal of creating an intelligent, behavior-based security model. It effectively counters user tendencies to ignore warnings by implementing a functional system of risk scoring and escalating alerts. This confirms that an adaptive approach is a more robust defense against security threats.

10. Future work NIT,Nagpur Database Integration: Use a persistent database (e.g., MongoDB) to track user behavior over time. Machine Learning: Implement an ML model to predict risky behavior before it happens. Real-Time Dashboard: Use WebSockets for a live administrative dashboard to monitor all users.

11. References NIT,Nagpur [1] Express.js Team, "Express.js API Reference," Accessed: 2025, https://expressjs.com/ . [2] OpenJS Foundation, "Node.js Documentation," Accessed: 2025, https://nodejs.org/ . [3] Liew, A. J. L., Siew, F. S. T. E. E., & Tan, W. L. L. (2012). "Towards an Adaptive Alerting System." In 2012 International Conference on Cyber Security, Cyber Warfare and Digital Forensic ( CyberSec ) , 114-119. [4] Singh, M. K. P., Singh, V. K., & Singh, S. K. (2013). "Risk-based authentication: a new perspective for securing enterprise resources." Journal of Global Research in Computer Science, 4 (9), 41-46.