saptajitbanerjee / SQL-Injection-DetectionLinks
My team built a Machine Learning model to detect SQL Injections. The dataset was prepared by capturing normal and malicious HTTP requests, extracting essential features for training the model effectively. It enhances web application security by accurately identifying and flagging SQL Injection attacks.
☆23Updated last year
Alternatives and similar repositories for SQL-Injection-Detection
Users that are interested in SQL-Injection-Detection are comparing it to the libraries listed below
Sorting:
- Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web …☆17Updated last year
- Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning, Recurrent Neural Netwo…☆17Updated last year
- Welcome this is a comprehensive repository dedicated to advancing Network Intrusion Detection Systems (NIDS) through the power of Machine…☆31Updated 6 months ago
- AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset☆73Updated 3 years ago
- Real-time Intrusion Detection System implementing Machine Learning. We combine Supervised Learning (RF) for detecting known attacks from …☆65Updated 2 weeks ago
- A custom GUI based NIDS (Network Intrusion Detection System) with stream follow capability for HTTP2 and TLS/TCP☆11Updated 9 months ago
- Web Applicaiton Firewall Implementation using Deep Learning☆14Updated 2 years ago
- Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN w…☆41Updated last year
- A project using Django, sklearn and pandas to detect anomalies in network traffic using machine learning☆45Updated 3 years ago
- IDS monitors a network or systems for malicious activity and protects a computer network from unauthorized access from users,including pe…☆99Updated 2 years ago
- A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach☆134Updated 3 years ago
- Network Intrusion Detection System☆44Updated 2 years ago
- The purpose of this repository is to demonstrate the steps of processing CICIDS2017 dataset using machine learning algorithms.☆63Updated 4 years ago
- This is a software application to detect network intrusion by monitoring a network or system for malicious activity and predicts whether …☆13Updated 2 years ago
- ☆28Updated 2 years ago
- Machine Learning in Cybersecurity☆83Updated last month
- DDoS attack analysis using Machine Learning☆44Updated 4 years ago
- Detection of network traffic anomalies using unsupervised machine learning☆26Updated 3 years ago
- An intrusion detection system (IDS) based on machine learning technique, specifically the anomaly detection algorithm.☆21Updated 4 years ago
- This repository contains an in-depth analysis of the Intrusion Detection Evaluation Dataset (CIC-IDS2017) for Intrusion Detection, showca…☆70Updated last year
- Cyber Attack Detection thanks to Machine Learning Algorithms☆104Updated 5 years ago
- Cross-site-scripting attacks: A Comprehensive dataset for AI techniques usage☆17Updated 3 years ago
- IoT networks have become an increasingly valuable target of malicious attacks due to the increased amount of valuable user data they cont…☆25Updated 2 years ago
- Code for intrusion detection system (IDS) development using CNN models and transfer learning☆169Updated 2 years ago
- Deep Model Intrusion Detection (IDS) Evaluation of NSL KDD and CIC IDS 2018 datasets.☆16Updated 2 years ago
- ☆11Updated 3 weeks ago
- Neural Network based Intrusion Detection System (NIDS) on Intrusion Detection Evaluation Dataset (CICIDS2017)☆12Updated 4 years ago
- Building an Intrusion Detection System on UNSW-NB15 Dataset Based on Machine Learning Algorithm☆85Updated 4 years ago
- Baseline experiments on training a Decision Tree Classifier and a Random Forest Classifier using Grid Search with Cross Validation on the…☆46Updated 3 years ago
- As society and technology develop, more and more of our time is spent online, from shopping to socialising, working to banking. Ensuring …☆13Updated 2 years ago