Real-time HTTP Intrusion Detection
A framework for secure and scalable network traffic analysis - https://netcap.io
Feature coded UNSW_NB15 intrusion detection data.
Network intrusion detection with Machine Learning (Deep Learning) experiment : 1d-cnn, softmax, neural networks, convolution
Intrusion Detection is a technique to identify the abnormal behavior of system due to attack. The unusual behavior of the environment is then identified and steps are taken and methods are formed to classify and recognize attacks. Data set containing a number of records sometimes may decrease the classifiers performance due to redundancy of data...
SecRep Is a Repository That Contain Useful Intrusion, Penetration and Hacking Archive Including Tools List, Cheetsheet and Payloads
Intrusion. Custom Asterisk dial plan for listen, whisper and barge in calls. For Asterisk FreePBX, Issabel, Asterisk based Elastix call centers.
Mata Elang is the evolution of Mata Garuda Internet Monitoring Project for Indonesia. This project was initialized as private repository in 2018 by LabJarkomC307 - Politeknik Elektronika Negeri Surabaya. Currently, Mata Elang become one of collaboration research between PENS, Universitas Indonesia and BPPT.
Mirai Eye
A powerful penetration testing tool for network reconnaissance and infiltration.
RedLoad-X is an ethical cybersecurity demonstration tool for educational and authorized network stress testing. It consists of various network stress attack types, provides real-time statistics, and helps users understand attack impacts. For responsible use only!
Shelly: Reverse shell simple con Python
Training materials and code examples using Python in security-related tasks. The focus is on teaching users how to use Python to automate common security tasks, such as vulnerability scanning, penetration testing, and network monitoring.
This is my final year Research Project.. There are 4 components as a). Voter Registration & Authentication Management b). Votes Management and Analyzing System c). Live Data Ingestion & Attacks Detection System d). Staff Members and Security Members Allocation.
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