AD Security Intrusion Detection System

Slips, a free software behavioral Python intrusion prevention system (IDS/IPS) that uses machine learning to detect malicious behaviors in the network traffic. Stratosphere Laboratory, AIC, FEL, CVUT in Prague.

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

This is the repo of the research paper, "Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber Security".

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

ebpH (Extended BPF Process Homeostasis) monitors process behavior on your system to establish normal behavioral patterns. ebpH reports anomalous behavior and prevents attacks by denying anoamlous access requests.

Whenever founds internet connectivity confirms is it you, if not log you off and send you image of intruder.

Network data classifier based on the recurrent neural network.

source code for USENIX Security paper xNIDS

Real-time Intrusion Detection System implementing Machine Learning. We combine Supervised Learning (RF) for detecting known attacks from CICIDS 2018 & SCVIC-APT datasets, and Unsupervised Learning (AE) for anomaly detection.

SNORT GUI: Your very own trusted blueteam forensic companion for SNORT IDS. OPTIMIZED, SECURE AND ABSOLUTELY FREE!

Intrusion detection engine for Cloud Systems built using Alternative Fuzzy C-mean Clustering and Artificial Neural Network

Adversarial Machine Learning applications on network-based Intrusion Detection System (IDS).

An intrusion detection system prototype for attacks on automobile CAN buses.

Intrusion Detection System - IDS example using Dense, Conv1d and Lstm layers in Keras / TensorFlow

The DearBytes remote integrity tool is an IDS (Intrusion Detection System) that keeps track of files on a remote server and logs an event if a file gets added, removed or modified.

DNN-Ensemble IDS is a machine learning based classification model for intrusion detection exploiting ensembles of classifiers.

🕵️ IDS with accuracy rates of 94.4% for misuse detection and 99.0% for anomaly detection

Code for paper: Contrastive Learning Enhanced Intrusion Detection