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This repository provides fuzzing scripts to analyze an IEC 61850 implementation
This survey includes recent researches related to BATADAL dataset and my experiment on it (BATADAL dataset is a time series dataset for anomaly detection).
Adversarial attack on RNN with CPS
Corresponding code to the paper "Active Fuzzing for Testing and Securing Cyber-Physical Systems" by authors: Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun and Fan Zhangin in ISSTA2020.
This is the official code for the paper "Ad2Attack: Adaptive Adversarial Attack for Real-Time UAV Tracking".
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Adaptive and fault tolerant flight control with Adaptive Neural Networks
Implementation of the paper "An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models"
Code for Adversarial Examples in Electrocardiograms
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Code and hyperparameters for the paper "Generative Adversarial Networks"
This repository contains the code and results for the project titled "Adversarial Attacks on Aerial Scene Classification" that I accomplished during my summer research internship at VIGIL Lab, IIT Hyderabad under the guidance of Prof. C. Krishna Mohan
Adversarial Driving v.s. Autonomous Driving.
Code example for the paper, "Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness."
Python library for adversarial attacks and defenses (evasion, poisoning) for neural networks with multiple framework support
This repository contains the trained model checkpoints and crafted adversarial samples of the paper: Attack and Defense: Adversarial Security of Data-driven FDC Systems, Yue Zhuo and Zhiqiang Ge.
Adversarial Machine Learning applications on network-based Intrusion Detection System (IDS).
Tensorflow implementation for generating adversarial examples using convex programming
VizSec17: Web-based visualization tool for adversarial machine learning / LiveDemo
ALAD (Proceedings of IEEE ICDM 2018) official code
Attacking Vision based Perception in End-to-end Autonomous Driving Models
AutoEncoders for Event Detection (AEED): a Keras-based class for anomaly detection in water sensor networks.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.