Secretflow – A Unified Framework For Privacy-Preserving Data Analysis And Machine Learning

SecretFlow is a unified framework for privacy-preserving data intelligence and machine learning. To achieve this goal, it provides: An abstract device layer consists of plain devices and secret devices which encapsulate various cryptographic protocols. A device flow layer modeling higher algorithms as device object flow and DAG. An algorithm layer to do data analysis andRead More

DeepTraffic – Deep Learning Models For Network Traffic Classification

For more information please read our papers.  Wei Wang’s Google Scholar Homepage Wei Wang, Xuewen Zeng, Xiaozhou Ye, Yiqiang Sheng and Ming Zhu,”Malware Traffic Classification Using Convolutional Neural Networks for Representation Learning,” in the 31st International Conference on Information Networking (ICOIN 2017), pp. 712-717, 2017. Wei Wang, Jinlin Wang, Xuewen Zeng, Zhongzhen Yang andRead More

DroidDetective – A Machine Learning Malware Analysis Framework For Android Apps

A machine learning malware analysis framework for Android apps. DroidDetective is a Python tool for analysing Android applications (APKs) for potential malware related behaviour and configurations. When provided with a path to an application (APK file) Droid Detective will make a prediction (using it’s ML model) of if the application is malicious. Features and qualitiesRead More

HaccTheHub – Open Source Self-Hosted Cyber Security Learning Platform

Open source self-hosted cyber security learning platform About The Project HaccTheHub is an open source project that provides cyber security The HaccTheHub system consists of 3 main parts: Docker: containing all of the boxes creating the environment in which we’ll be learning on. The backend: controlling Docker and responsible for starting/destroying indivisual box in theRead More

SyntheticSun – A Defense-In-Depth Security Automation And Monitoring Framework Which Utilizes Threat Intelligence, Machine Learning, Managed AWS Security Services And, Serverless Technologies To Continuously Prevent, Detect And Respond To Threats

SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats. You sleep in fragmented glassWith reflections of you,But are you feeling alive?Yeah let me ask you,Are you feeling alive?– Norma Jean, 2016 Synopsis Uses event-Read More

In0ri – Defacement Detection With Deep Learning

In0ri is a defacement detection system utilizing a image-classification convolutional neural network. Introduction When monitoring a website, In0ri will periodically take a screenshot of the website then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifierRead More

AutoPentest-DRL – Automated Penetration Testing Using Deep Reinforcement Learning

AutoPentest-DRL is an automated penetration testing framework based on Deep Reinforcement Learning (DRL) techniques. The framework determines the most appropriate attack path for a given network, and can be used to execute a simulated attack on that network via penetration testing tools, such as Metasploit. AutoPentest-DRL is being developed by the Cyber Range Organization andRead More

Pesidious – Malware Mutation Using Reinforcement Learning And Generative Adversarial Networks

Malware Mutation using Deep Reinforcement Learning and GANs The purpose of the tool is to use artificial intelligence to mutate a malware (PE32 only) sample to bypass AI powered classifiers while keeping its functionality intact. In the past, notable work has been done in this domain with researchers either looking at reinforcement learning or generativeRead More

uriDeep – Unicode Encoding Attacks With Machine Learning

Unicode encoding attacks with machine learning. Tool based on machine learning to create amazing fake domains using confusables. Some domains can deceive IDN policies (Chrome & Firefox). I created the best (big) dictionary of confusables using neural networks. It is used in the tool and it can be download from: https://github.com/mindcrypt/uriDeep/blob/master/data/deepDiccConfusables.txt [email protected]:~/tool/uriDeep# python3 uriDeep.py _Read More

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