tartaruszen Goto Github PK
Type: User
Type: User
465 example scripts
Explore the Aalborg University social network and test network analysis algorithms.
Code and supplementary material for "Automatic Bayesian Density Analysis", AAAI 19
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 rejection sampling on log-concave functions
Anomaly Detection Discriminative GAN (ADD-GAN)
Adversarial Examples: Attacks and Defenses for Deep Learning
PyTorch implementation of adversarial patch
Implementation of adversarial attacks and defences.
This is a library dedicated to adversarial machine learning. Its purpose is to allow rapid crafting and analysis of attacks and defense methods for machine learning models. The Adversarial Robustness Toolbox provides an implementation for many state-of-the-art methods for attacking and defending classifiers. https://developer.ibm.com/code/open/projects/adversarial-robustness-toolbox/
ALAD (Proceedings of IEEE ICDM 2018) official code
*From Adversarial Training to Generative Adversarial Networks*
博理论读书笔记
The first Osmotic Computing Agent
Free Communications For Everyone.
A python script to automate the process of cracking a wpa/wpa2 network. QT gui version is in the works.
Accelerated Local Anomaly Detection in Attributed Networks
Python library to fetch the top 1..N (where N < 1 million) sites from alexa
A server-side Website Fingerprinting defence called "Application Layer Padding Concerns Adversaries"
Asymmetric Multi-Task Learning code, If you want to use it, please let me know and cite AMTL paper
Attributed graph summarization
Implementation of AnoGAN (Anomaly GAN)
Dynamic anomaly detection in crowded scene videos using sparse autoencoders
The Domain Name System is a fundamental component of the internet since it maps the easy-to-remember domain names to IP addresses. Therefore, it is usually the primary target for most of the malicious attacks such as DNS Poisoning and Rogue DNS servers. With the help of 0x20 bit encoding, the problem of DNS Poisoning is mitigated to quite a large extent. Although, it has a minor requirement that the authoritative nameserver should be able to preserve the case of the DNS query. It is usually difficult to detect the rogue DNS server above the stub resolver. We propose an anomaly detection system which would be able to raise a red flag in case of DNS Poisoning and malicious DNS authority by passive DNS analysis of domain names and then comparing them with the 0th day cluster of the database. We perform the passive DNS analysis for 27 days by querying the whois server of CYMRU, compare the network profiles of the domain names crawled with the 0th day cluster and categorize the domain names as static, benign anomaly and malicious anomaly depending upon the cluster a domain name shifted. In the process, we also create a WHOIS repository for Alexa domain names which is faster to query than the WHOIS server.
Anomaly detection in time evolving graphs
some anomaly detection models and experiments.
Outlier detection books, papers, videos, and implementations
A list of anomaly detection and classification papers for robotics and the other area
A simple and effective method for single-class classification of images
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.