shuwang127

Shu Wang's repositories

Algorithms_for_MachineLearning

Open Source Code for Machine Learning in Computer Vision

Language:C++GPL-2.036 40

SRCNN_Cpp

C++ Implementation of Image Super-Resolution using Convolutional Neural Network SRCNN (OpenCV version)

Language:CGPL-2.033 8 3

The source code in the paper "When the Differences in Frequency Domain are Compensated: Understanding and Defeating Modulated Replay Attacks on Automatic Speech Recognition". This paper is published in the ACM Conference on Computer and Communications Security (CCS) 2020.

Language:MATLAB5 10

SIEVE

The source code in the paper "Secure In-Vehicle Automatic Speech Recognition Systems". This paper is published in the 23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) 2020.

Language:MATLAB5 20

PatchRNN-demo

A demo program of security patch identification using the RNN model, which is demonstrated in the paper "PatchRNN: A Deep Learning-Based System for Security Patch Identification". This paper appears in the 2021 IEEE/AFCEA Military Communications Conference (MILCOM 2021), San Diego, USA, November 29–December 2, 2021.

Language:PythonApache-2.04 20

BlueRabbit

Data Analysis for Human Trafficking

Language:Python3 10

K-Nearest-Neighbor

K Nearest Neighbor and Condensed KNN Algorithm

Language:MATLABMIT3 10

PatchGNN-demo

A Demo Program of Security Patch Identification with Graph Neural Networks.

Language:PythonApache-2.03 10

BinRNN

Provenance Analysis of Binary Code with RNN model.

Language:PythonApache-2.02 10

MLClassifiers

Basic Machine Learning Classifiers with scikit-learn.

Language:Jupyter Notebook2 10

NLP-Baseline

Naive Bayes and Logistic Regression with Natural Language Processing

Language:Python2 10

PatchClearance

Data clearance for security patches and non-security patches. This method is described as Nearest Link Search in the paper "PatchDB: A Large-Scale Security Patch Dataset", which appears in 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2021), Taipei, June 21-24, 2021, pp. 149-160.

Language:PythonApache-2.02 10

PatchML

Security Patch Identification with Classical Machine Learning Algorithms.

Language:PythonApache-2.02 10

PatchOversampling

Oversampling operations on security/non-security patches. This method is described in the paper "PatchDB: A Large-Scale Security Patch Dataset", which appears in 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2021), Taipei, June 21-24, 2021, pp. 149-160.

Language:CApache-2.02 10

PatchOversamplingV2

Patch oversampling (synthesis) with direct patch analysis. This is an alternative solution to the PatchOversampling repository, providing a simpler and more direct way to synthesize patches. The original oversampling method is described in the DSN'21 paper "PatchDB: A Large-Scale Security Patch Dataset".

Language:PythonApache-2.02 10

PatchRNN

The source code in the paper "PatchRNN: A Deep Learning-Based System for Security Patch Identification". This paper appears in the 2021 IEEE/AFCEA Military Communications Conference (MILCOM 2021), San Diego, USA, November 29–December 2, 2021.

Language:Jupyter NotebookApache-2.02 10

PatchRNNExtra

RNN-based security patch identification with oversampling samples. This is an extension code in the MILCOM'21 paper "PatchRNN: A Deep Learning-Based System for Security Patch Identification".

Language:PythonApache-2.02 10