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master-deep-learning-with-tensorflow-2.0-in-python-2019

Master Deep Learning with TensorFlow 2.0 in Python [2019]

mit-deep-learning

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

ml-based-intrusion-detection-system-for-software-defined-network

An algorithm was created to detect various anomalies, which was trained on a static dataset obtained from an SDN controller.

ml-nids-sdn

The work in paper "A novel Machine Learning-based Network Intrusion Detection System for Software-Defined Network" - Duc-Huy LE, Hai-Anh TRAN - NICS2020 Conference

ml.phishingemaildetection

mscdissertation-sdn-arp-mitigation

Intrusion Detection and Prevention and Proxy Hybrid using Software-Defined Networking: ARP Poisoning Defence

network-log-and-traffic-analysis

Identify malicious behavior and attacks using Machine Learning with Python

nlc-email-phishing

Detect email phishing with Watson Natural Language Classifier

phemail

PhEmail is a python open source phishing email tool that automates the process of sending phishing emails as part of a social engineering test

phishing-detection-in-email

phishing-detection-ml

Detecting phishing website using NN.

phishing-email-detection

Final year project

phishing-email-detection-1

phishing-emails-detection

phishing_emails

projectq-network-data-analysis-

We are practicing Machine Learning over Network Data to predict the volume of future network traffic.

real-world-python-deep-learning-projects

Real-World Python Deep Learning Projects [Video], Published By Packt

seq2seq-web-attack-detection

The implementation of the Seq2Seq model for web attack detection. The Seq2Seq model is usually used in Neural Machine Translation. The main goal of this project is to demonstrate the relevance of the NLP approach for web security.

simple-machine-learning-module-for-network-traffic-analysis

Using some basic Machine Learning Algorithms for Identifying network intrusions

simple_ids_using_ryu_sdn_controller_and_machine_learning

Implemented a network intrusion detection system for a software defined network using Random Forest method for classification of port and flow statistics.

spear-phishing

Detection of spear phishing emails

trench

Machine Learning for Encrypted Network Traffic Analysis

web-attack-cheat-sheet

Web Attack Cheat Sheet

web-attack-detuction-using-machine-learning-

Web Attack Detuction using Machine Learning , where we use the Machine Learning Algorithm using detect the Web attacks in form of network traffic.