Simple pytorch implementation of FGSM and I-FGSM
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Updated
Mar 21, 2018 - Python
Simple pytorch implementation of FGSM and I-FGSM
A curated list of MLSecOps tools, articles and other resources on security applied to Machine Learning and MLOps systems.
pretrained BERT model for cyber security text, learned CyberSecurity Knowledge
Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications
CTF challenges designed and implemented in machine learning applications
Adversarial Machine Learning (AML) Capture the Flag (CTF)
Train AI (Keras + Tensorflow) to defend apps with Django REST Framework + Celery + Swagger + JWT - deploys to Kubernetes and OpenShift Container Platform
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)
Do you want to learn AI Security but don't know where to start ? Take a look at this map.
Datasets for training deep neural networks to defend software applications
This repository contains the code for our ACM CCS'22 paper "StolenEncoder: Stealing Pre-Trained Encoders in Self-Supervised Learning"
Summary of the presentation on Real and Stealthy Attacks on State-of-the-Art Face Recognition Systems at the Seminar: Machine Learning in Cyber-security at FU Berlin
Awesome-ML-Supply-Chain-Security-Papers
Final Year Thesis Project (COMP4981H) for Computer Science Students in HKUST
Adversarial perturbation intensity strategy achieving chosen intra-technique transferability level for logistic regression
A stochastic input pre-processing technique based on a process of down-sampling/up-sampling using convolution and transposed convolution layers. Defending convolutional neural network against adversarial attacks.
This is the repository for Homeworks of COMP 530 Data Privacy and Security course given by Emre Gursoy at Koc University.
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