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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

homoglyph

improvediuptis

Publication 'Realistically Fingerprinting Social Media Webpages in HTTPS Traffic'

iotanomaly

Anomaly Detection in Network Traffic of IOT Devices

iot_sentinel

IoT SENTINEL : Automated Device-Type Identification for Security Enforcement in IoT https://arxiv.org/pdf/1611.04880.pdf

kdd99_feature_extractor

Utility for extraction of subset of KDD '99 features from realtime network traffic or .pcap file

kitnet-py

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

malicious_domain_whois

:beginner: 非法域名挖掘与画像系统

malware-prediction-rnn

RNN implementation with Keras for machine activity data to predict malware

malware-uncertainty

deep learning, malware detection, predictive uncertainty, dataset shift, calibration, uncertainty quantification, android malware

masktune

mdan

Demo code for the MDAN paper.

mobilegt_dataclean

处理mobilegt产生的数据

mptanalysis

Code for USENIX'18 paper: "Effective Detection of Multimedia Protocol Tunneling using Machine Learning"

multimodalautoencoder

Code supporting the paper "Multimodal Autoencoder: A Deep Learning Approach to Filling In Missing Sensor Data and Enabling Better Mood Prediction"

multitasktrafficclassification

Multitask Learning Approach for Network Traffic Classification

obfs-detection

Scripts for CCS 2015 "Seeing through Network Protocol Obfuscation"

open-set-traffic-classification

outlier-exposure

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

paper_tnsm

Code for paper: Contrastive Learning Enhanced Intrusion Detection

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.

privacypreservingtrafficobfuscation

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.

ransomware-detection-with-deep-learning

Detecting ransomware delivery with DNNs

sdc-il

Semantic Drift Compensation for Class-Incremental Learning (CVPR2020)