information-security Cybersecurity involves protecting systems, networks, and data from cyber threats. This field encompasses a wide range of practices and technologies designed to safeguard information from unauthorized access, attacks, damage, or theft.
This project presents a full-stack web application designed for the detection of UPI (Unified Payments Interface) fraud using advanced analytical techniques. The system leverages historical transaction data to identify patterns and anomalies indicative of fraudulent activities.
How to run the app This streamlit app python file. demonstrates how the cGAN-Powered Intrusion Detection System developed to generate synthetic IoT intrusion data, preprocess the generated data, use lightGBM multi-class classification machine learning model, and provide post-model insights.
This project implements an IoT-based object detection system using an ESP8266 microcontroller, an IR sensor, and a buzzer. The system monitors objects using the IR sensor, triggers a buzzer when an object is detected, and logs the detection data to ThingSpeak, a cloud-based platform for data visualization.
This project demonstrates creating a robust Employee Management System (EMS) with React and Node.js. It features a MySQL database for data storage, Axios for frontend-backend communication, JWT for secure authentication, and hash functions for data security. This guide equips developers to build efficient and secure employee management solutions.
The project leverages decentralized storage using the InterPlanetary File System (IPFS), creating an alternative to platforms like Google Drive. However, it goes a step further by incorporating blockchain technology to enhance data security. By utilizing IPFS, the project ensures that files are distributed across a network of nodes.
A data science project aimed at creating a machine learning-based email spam detection system. It effectively identifies and classifies emails into spam and non-spam categories, enhancing email security and user experience.
Network Security ML Project for URL Security Analysis This project focuses on building a Network Security System that processes phishing data using ETL (Extract, Transform, Load) pipelines. A project designed to empower users with a robust tool for analyzing URLs and detecting potential security threats, such as phishing and malicious links.
