mortal12138 Goto Github PK

acid

Source code for the paper: Adaptive Clustering-based Malicious Traffic Classification at the Network Edge (https://homepages.inf.ed.ac.uk/ppatras/pub/infocom21.pdf)

adversarially-learned-anomaly-detection

ALAD (Proceedings of IEEE ICDM 2018) official code

ai-for-security-learning

安全场景、基于AI的安全算法和安全数据分析业界实践

ai-log-analyzer

art

The code for paper "ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks".

artif

An advanced real time threat intelligence framework to identify threats and malicious web traffic on the basis of IP reputation and historical data.

attackability-characterization-of-adversarial-evasion-attack-on-discrete-data

Source codes for "Attackability Characterization of Adversarial Evasion Attack on Discrete Data" (SIGKDD 2020)

auto_lirpa

[NeurIPS 2020]auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks

awesome-adversarial-machine-learning

A curated list of awesome adversarial machine learning resources

awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

blanket

bruteshark

Network Analysis Tool

cade

Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

certifiedrelurobustness

Efficient Robustness Verification for ReLU networks (this repository is DEPRECATED, don't use, see description)

cifar10_challenge

A challenge to explore adversarial robustness of neural networks on CIFAR10.

cnn-cert

Codes for reproducing the experimental results in "CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks", published at AAAI 2019

crown-ibp

Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).

crown-robustness-certification

CROWN: A Neural Network Robustness Certification Algorithm for General Activation Functions (This repository is DEPRECATED; use https://github.com/huanzhang12/RecurJac-and-CROWN instead)

dagmm

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

dagmm-1

A Pytorch implementation of the paper `Deep Autoencoding Gaussian Mixture Model For Unsupervised Anomaly Detection` by Zong et al.

deepcorr

deepdig

This repository contains the code for Characterizing the Decision Boundary of Deep Neural Networks

demo-routenet

Demo of RouteNet in ACM SIGCOMM'19

denoised-smoothing

Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs

df

The source code and dataset are used to demonstrate the DF model, and reproduce the results of the ACM CCS2018 paper

dl2

DL2 is a framework that allows training neural networks with logical constraints over numerical values in the network (e.g. inputs, outputs, weights) and to query networks for inputs fulfilling a logical formula.

efficient-gan-anomaly-detection

empirical_evaluation

fare

FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data

freelb

Adversarial Training for Natural Language Understanding