🔒 A compiled checklist of 300+ tips for protecting digital security and privacy in 2024
-
Updated
May 12, 2024 - TypeScript
🔒 A compiled checklist of 300+ tips for protecting digital security and privacy in 2024
HardeningKitty and Windows Hardening settings and configurations
ESB, SOA, REST, APIs and Cloud Integrations in Python
A pytorch adversarial library for attack and defense methods on images and graphs
HardeningKitty - Checks and hardens your Windows configuration
A curated collection of adversarial attack and defense on graph data.
Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
💡 Adversarial attacks on explanations and how to defend them
Production-ready detection & response queries for osquery
Adversarial attacks and defenses on Graph Neural Networks.
Group satellites into constellations such that their average observation coverage is maximized
Demo for analyzing the structural imbalance on a signed social network.
A certifiable defense against adversarial examples by training neural networks to be provably robust
This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.
Demonstrate a max independent set problem with antennas
Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)
Add a description, image, and links to the defense topic page so that developers can more easily learn about it.
To associate your repository with the defense topic, visit your repo's landing page and select "manage topics."