Topic: intrusion-detection-system Goto Github
Some thing interesting about intrusion-detection-system
Some thing interesting about intrusion-detection-system
intrusion-detection-system,A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach
User: abhinav-bhardwaj
intrusion-detection-system,Adversarial Machine Learning applications on network-based Intrusion Detection System (IDS).
User: ahsanayub
intrusion-detection-system,UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.
User: albertsr
Home Page: https://github.com/Albertsr/Anomaly-Detection
intrusion-detection-system,OPNSense's Suricata IDS/IPS Detection Rules Against NMAP Scans
User: aleksibovellan
intrusion-detection-system,Are you you? π ML model in Python to determine if it is me who is using my computer
User: ana06
intrusion-detection-system,Machine learning based Intrusion detection system (IDS)
User: bibs2091
intrusion-detection-system,source code for USENIX Security paper xNIDS
Organization: cactilab
intrusion-detection-system,An intrusion detection system prototype for attacks on automobile CAN buses.
User: cjholoday
intrusion-detection-system,An Ubuntu 16.04 build containing Suricata, PulledPork, Bro, and Splunk
User: clong
intrusion-detection-system,Machine Learning with the NSL-KDD dataset for Network Intrusion Detection
User: cynthiakoopman
intrusion-detection-system,Aoandon (ιθ‘η) is a minimalist network intrusion detection system (NIDS).
User: cyril
Home Page: https://cyrilllllll.medium.com/a-hundred-network-stories-bc0ba5ef6a41
intrusion-detection-system,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.
Organization: dearbytes
intrusion-detection-system,Intrusion detection engine for Cloud Systems built using Alternative Fuzzy C-mean Clustering and Artificial Neural Network
User: doneria-anjali
intrusion-detection-system,Intrusion Detection System - IDS example using Dense, Conv1d and Lstm layers in Keras / TensorFlow
User: dwday
intrusion-detection-system,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
User: ggulgun
intrusion-detection-system,Network related services, programs and applications are developing greatly, however, network security breaches are also developing with them. Network security is an evolving, challenging and a critical task. It is essential that there is a system in place to identify any harmful movement happening in network. An Intrusion detection system (IDS) has become the prerequisite software addressing cyber security in the modern era. Especially, with the greater complexity of advanced cyber-attacks and as such the uncertainty surrounding the detection of the types of attacks. This thesis proposes a novel approach using an ensemble of K-Means and Gaussian Mixture clustering combined with a deep neural network (DNN) algorithm. When compared with traditional artificial neural networkβs (ANNβs) used within an IDS, our approach implements modern advances in deep learning such as initialising the parameters through the unsupervised pre-training clustering ensemble, therefore improving the detection accuracy. We hope our results will show that the proposed approach can provide a real-time response to the attack with a greatly increased detection ratio for false flags.
User: grannyprogramming
intrusion-detection-system,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.
User: hoangnv2001
intrusion-detection-system,Intrusion Detection System for IoT Devices
User: jayluxferro
intrusion-detection-system,Advanced Access Point Anomaly Detection System
User: mateusz-peplinski
intrusion-detection-system,CSE-CIC-IDS-2018 analyze with Random Forest
User: nadhirfr
intrusion-detection-system,Machine Learning Based - Intrusion Detection System
User: nadhirfr
intrusion-detection-system,Suricata is a network Intrusion Detection System, Intrusion Prevention System and Network Security Monitoring engine developed by the OISF and the Suricata community.
Organization: oisf
Home Page: https://suricata.io
intrusion-detection-system,An Intrusion Detection System based on Deep Belief Networks
User: othmbela
intrusion-detection-system,The OWASP SecureTea Project provides a one-stop security solution for various devices (personal computers / servers / IoT devices)
Organization: owasp
Home Page: https://securetea.org
intrusion-detection-system,This is the repo of the research paper, "Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber Security".
User: rahulvigneswaran
intrusion-detection-system,Entropy scanner for Linux to detect packed or encrypted binaries related to malware. Finds malicious files and Linux processes and gives output with cryptographic hashes.
Organization: sandflysecurity
Home Page: https://www.sandflysecurity.com
intrusion-detection-system,Sandfly Security Agentless Compromise and Intrusion Detection System For Linux
Organization: sandflysecurity
Home Page: https://www.sandflysecurity.com
intrusion-detection-system,Security Onion is a free and open platform for threat hunting, enterprise security monitoring, and log management. It includes our own interfaces for alerting, dashboards, hunting, PCAP, detections, and case management. It also includes other tools such as osquery, CyberChef, Elasticsearch, Logstash, Kibana, Suricata, and Zeek.
Organization: security-onion-solutions
Home Page: https://securityonion.net
intrusion-detection-system,Network Intrusion Detection System on CSE-CIC-IDS2018 using ML classifiers and DNN ( ANN , CNN , RNN ) | Hyper-parameter Optimization { learning rate, epochs, network architectures, regularisation } | Adversarial Attacks - Label flip , Adversarial samples , KNN (defence)
User: shahanhasan
intrusion-detection-system,CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level
User: shahriar0651
Home Page: https://github.com/shahriar0651/canshield/
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.
Organization: stratosphereips
intrusion-detection-system,Baseline experiments on training a Decision Tree Classifier and a Random Forest Classifier using Grid Search with Cross Validation on the CIC IDS 2018 dataset for training Machine Learning network intrusion detection classifier models.
User: tamerthamoqa
intrusion-detection-system,Real-time HTTP Intrusion Detection
Organization: teler-sh
Home Page: https://teler.app
intrusion-detection-system,IoT intrusion Detection Model based on neural network and random forests
User: tgyaldeen
intrusion-detection-system,Whenever founds internet connectivity confirms is it you, if not log you off and send you image of intruder.
User: the-vishal
intrusion-detection-system,Collection of Snort 2/3 rules.
User: thereisnotime
Home Page: https://snort.org
intrusion-detection-system,Network Intrusion Detection System
User: vicky60629
Home Page: https://nids-api.herokuapp.com/
intrusion-detection-system,Network data classifier based on the recurrent neural network.
User: vvsotnikov
intrusion-detection-system,This repository includes code for the AutoML-based IDS and adversarial attack defense case studies presented in the paper "Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis" published in IEEE Transactions on Network and Service Management.
Organization: western-oc2-lab
intrusion-detection-system,Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
Organization: western-oc2-lab
intrusion-detection-system,Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
Organization: western-oc2-lab
intrusion-detection-system,Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems" published in IEEE Transactions on Industrial Informatics.
Organization: western-oc2-lab
intrusion-detection-system,An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in IEEE Internet of Things Magazine.
Organization: western-oc2-lab
intrusion-detection-system,Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.
Organization: western-oc2-lab
intrusion-detection-system,SNORT GUI: Your very own trusted blueteam forensic companion for SNORT IDS.
User: whitehatcyberus
Home Page: https://whitehatcyberus.github.io/SNORT-GUI/
intrusion-detection-system,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.
User: willfindlay
intrusion-detection-system,wolfSSL Intrusion Detection and Prevention System (IDPS)
Organization: wolfssl
Home Page: https://www.wolfssl.com/
intrusion-detection-system,Code for paper: Contrastive Learning Enhanced Intrusion Detection
User: yue123161
Home Page: https://ieeexplore.ieee.org/abstract/document/9935282
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