
60+
Workshop & Invited Talks

100+
Projects

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Conferences
Recent Workshops & Events
Important Projects
Comparative Study of Deep Learning Models for Multiclass Network Anomaly Detection using CICIDS 2017
Conference: IEEE International Conference 2026, BNMIT Bangalore Vaishnavi KM (USN: 1RN22CY045)
Guide: Ms. Likitha R
This project focuses on developing an intelligent system for detecting and analysing network anomalies using advanced techniques such as deep learning and data-driven models. It aims to enhance cybersecurity by improving the accuracy, efficiency, and real-time detection of diverse network attacks in practical environments.
Advanced Persistent Threat Detection through Machine Learning
Conference: CCIC 2026, Tirupati Ayush Shanmukha (USN: 1RN22CY008),DS Sai Suhas (USN: 1RN22CY012), Harish Ashok (USN: 1RN22CY016)
Guide: Mr. Dhanraj
This project focuses on detecting Advanced Persistent Threats (APTs) using machine learning techniques by analyzing network behavior and identifying hidden attack patterns. It aims to improve early detection and strengthen cybersecurity systems against sophisticated and long-term cyber threats.
Decentralised Health Monitoring: A Blockchain Approach to Patient Data Security
Conference: IEEE International Conference 2026, BNMIT Bangalore Priyadarshini S (USN: 1RN22CY031)
Guide: Dr. Kiran P
This project proposes a decentralized health monitoring system using blockchain technology to secure patient data. By leveraging the immutability and transparency of blockchain, the system ensures privacy, prevents unauthorized access, and allows secure sharing of medical records among healthcare providers, enhancing overall data security and trust in digital healthcare systems.
Automated Vehicle Collision Detection: Multi-Model Computer Vision Framework
Conference: IEEE International Conference 2026, BNMIT Bangalore Purnesh B R (USN: 1RN22CY032)
Guide: Dr. Swati Darla
This project presents an automated vehicle collision detection system using a multi-model computer vision framework. By integrating advanced image processing and deep learning techniques, the system aims to accurately detect collisions in real-time, enhancing road safety and enabling prompt emergency response.
Deepfake Image Detection System
Conference: IEEE International Conference 2026, BNMIT Bangalore Suraj Kumar (1RN22CY040),Ayush Kapoor (1RN22CY007),Harsh Ranjan (1RN22CY017)
Guide: Yashaswini Nag MN
This project focuses on detecting deepfake images using advanced machine learning and computer vision techniques. The system analyzes visual inconsistencies and manipulations to accurately identify synthetic media, aiming to enhance digital security and prevent misinformation.
Forest Fire Detection System for Hybrid Drones
BHARATH V, HEMANTH KUMAR R & MOURYA S HALLI
Guide: Mr. DHANRAJ
A cutting-edge approach utilizing hybrid drones for early forest fire detection, integrating image processing and deep learning models to provide a scalable and efficient solution for monitoring vast forested areas.
IcedID Malware Analysis Tool over Wi-Fi
ALKAMA EQBAL, YASH MAURYA & YASHASWINI S
Guide: Dr KIRAN P
A real-time network monitoring solution that detects IcedID’s C2 communication over Wi-Fi, analyzes traffic anomalies, generates security recommendations, and enhances efficiency through an intuitive user interface.
Women’s Safety Device – A Technological Approach to Personal Security
Bhuvhan Chandra , Tanmayee & Saranya
Guide: Dr R Rajkumar
An AI-powered wearable device designed to enhance women's personal safety, integrating GPS tracking, SOS alerts, and real-time location sharing, with predictive threat detection, voice/gesture activation, seamless mobile connectivity, and encrypted cloud storage for a scalable urban and remote safety solution.
Eminent Speakers
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principal@rnsit.ac.in
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RNS Institute of Technology,
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