Zercurity Python API
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Updated
Oct 16, 2017
Zercurity Python API
Worked on three use cases- Churn data analysis, Movie recommendation engine and Intrusion detection system.
Командный проект на тему "Методы машинного обучения для обнаружения вторжений в сетях интернета вещей" в рамках курса "Введение в искусственные нейронные сети" магистратуры НИТУ МИСИС
Unmanarc's Auditd Analyzer
Subvert detection by IDS/IPS rule sets when conducting web application and MiTB attacks, etc.
The code to train and test models.
Simple IPS to automatically block hosts performing automated attacks in the local firewall.
A Python notebook demonstrating an Intrusion Detection System for surveillance videos using OpenCV, focusing on real-time threat detection and alert notifications.
Performance Evaluation of Supervised Machine Learning Algorithms for Intrusion Detection
An animal intrusion detection mechanism for CSD513 course mini project
Automatically profile your network, building a packet-filter of common known-good traffic. Useful for IDS filtering and network monitoring.
Explanation of research paper ( A Framework for the Application of Association Rule Mining in Large Intrusion Detection )
Machine Learning Coursework (Matlab). Report - Implemented a supervised learning neural network model to determine if intrusion occurred on a network. Set Exercise - Implemented K-Means Clustering Algorithm on to categories a dataset.
A security system made using Raspberry Pi and various sensors which include Ultrasonic Sensor, PIR Sensor and LDR Sensor. To raise an alarm, a buzzer is integrated along with a LED.
A deep learning model that utilizes principal component analysis (PCA) for feature reduction and employs multi-layer perceptron to classify unforeseen cyber-attack IoT-based healthcare devices.
Near real-time intrusion detection for blacklisting
Ranomware monitor and alert service with inotifywait.
A predictive model capable of distinguishing between bad connections and good connections using machine learning.
SELID: Selective Event Labeling for Intrusion Detection Datasets
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