Darwin's repositories
Paper_TNSM
Code for paper: Contrastive Learning Enhanced Intrusion Detection
awesome-rl-for-cybersecurity
A curated list of resources dedicated to reinforcement learning applied to cyber security.
flow_meter
extract payload sequence features from network traffic pcap files
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
DeepAID
Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications (CCS'21)
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
FS-Net
Code for “FS-Net: A Flow Sequence Network For Encrypted Traffic Classification”
FUSE
Cloned from 2020 Paper from NDSS
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
HomePWN
HomePwn - Swiss Army Knife for Pentesting of IoT Devices
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.
PCAPFeatureExtractor
Feature extraction from PCAP files.
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
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.
SDC-IL
Semantic Drift Compensation for Class-Incremental Learning (CVPR2020)
SessionVideo
SessionVideo: A Novel Approach for Encrypted Traffic Classification via 3D-CNN Model
TLC
PyTorch implementation of the paper "Trustworthy Long-Tailed Classification" (CVPR 2022)
TLS-Malware-Detection-with-Machine-Learning
Leveraging machine learning to detect TLS based malware in encrypted traffic without decryption
TMorph
Traffic Morphing Framework