surrealyz

pdfclassifier

On Training Robust PDF Malware Classifiers (Usenix Security'20) https://arxiv.org/abs/1904.03542

verified-global-properties

Learning Security Classifiers with Verified Global Robustness Properties (CCS'21) https://arxiv.org/pdf/2105.11363.pdf

growtrees

Cost-Aware Robust Tree Ensembles for Security Applications (Usenix Security'21) https://arxiv.org/pdf/1912.01149.pdf

EvadeML

An evolutionary framework for evading machine learning-based malware classifiers.

az

Downloads apks from androzoo repository https://androzoo.uni.lu/

pytorch-metric-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

VulnerabilityDetectionResearch

VulnerabilityDetectionResearch

AndroidNativeEmu

Allows you to partly emulate an Android native library.

RobustTrees

Robust Decision Trees Against Adversarial Examples (ICML 2019, 20 min long talk)

scikit-learn

scikit-learn: machine learning in Python

APIGraph

Building relation graph of Android APIs to catch the semantics between APIs, and used to enhancing Android malware detectors

avclass

AVClass malware labeling tool

BGP-SerialHijackers

Additional material for paper Profiling BGP Serial Hijackers: Capturing Persistent Misbehavior in the Global Routing Table, IMC ’19

CSrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

DeepBayes

Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"

disinfo-infra-public

Source code and training data for the academic paper "Identifying Disinformation Websites Using Infrastructure Features"

drebin

Drebin - NDSS 2014 Re-implementation

DroidEvolver

joern_cpg_to_neo4j

neo4jd3

Neo4j graph visualization using D3.js

ReVeal

simplify

Android virtual machine and deobfuscator

SoK

SoK: Cryptojacking Malware

spark

Apache Spark - A unified analytics engine for large-scale data processing

SupContrast

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

SVF-example

An external project example using SVF as a library

Twitter-API-v2-sample-code

Sample code for the Twitter API early access endpoints (Python, Java, Ruby, and Node.js).

UMNN

Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for modelling monotonic transformations in normalizing flows.

VELVET

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow