Darwin's repositories
Paper_TNSM
Code for paper: Contrastive Learning Enhanced Intrusion Detection
flow_meter
extract payload sequence features from network traffic pcap files
pytorch-scarf
Implementation of SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption in Pytorch, a model learning a representation of tabular data using contrastive learning. It is inspired from SimCLR and uses a similar architecture and loss.
TLC
PyTorch implementation of the paper "Trustworthy Long-Tailed Classification" (CVPR 2022)
flow-feature
多进程读取pcap，基于五元组分流并提取流量特征。结果输出为csv文件，用于机器学习中对加密流量进行分类
Grey_Model
包含灰色预测模型：灰色单变量预测模型GM(1,1)模型，灰色多变量预测模型GM(1,N)模型，GM(1,N)幂模型，灰色多变量周期幂模型GM(1,N|sin)幂模型，以及灰色关联模型
SessionVideo
SessionVideo: A Novel Approach for Encrypted Traffic Classification via 3D-CNN Model
PCAPFeatureExtractor
Feature extraction from PCAP files.
FUSE
Cloned from 2020 Paper from NDSS
PyPASAD
This is a python implementation of the original work in the paper 'Truth will out', Departure-Based Process-Level Detection of Stealthy Attacks on Control Systems. Original Matlab implementation available at https://github.com/mikeliturbe/pasad
awesome-rl-for-cybersecurity
A curated list of resources dedicated to reinforcement learning applied to cyber security.
DeepAID
Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications (CCS'21)
malware-uncertainty
deep learning, malware detection, predictive uncertainty, dataset shift, calibration, uncertainty quantification, android malware
Patch-wise-iterative-attack
Patch-wise iterative attack (accepted by ECCV 2020) to improve the transferability of adversarial examples.
TMorph
Traffic Morphing Framework
HomePWN
HomePwn - Swiss Army Knife for Pentesting of IoT Devices
CyberBattleSim
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
DATSC
Deep Abstention Time Series Classifier
TLS-Malware-Detection-with-Machine-Learning
Leveraging machine learning to detect TLS based malware in encrypted traffic without decryption
SDC-IL
Semantic Drift Compensation for Class-Incremental Learning (CVPR2020)
FS-Net
Code for “FS-Net: A Flow Sequence Network For Encrypted Traffic Classification”