Weimin Huang

38 papers A* 1A 2B 4C 6Journal 11Unranked 14
YearRankTypeTitle / Venue / Authors
2025 J jnl
Biomed. Signal Process. Control.
Xuan Nie, Bosong Chai, Kun Zhang, Chen Liu, Zhongxian Li, Rennian Huang, Qianru Wei, Minggang Huang, Weimin Huang
2025 J jnl
CoRR
Weimin Huang, Ryan Piansky, Bistra Dilkina, Daniel K. Molzahn
2025 J jnl
CoRR
Junyang Cai, Weimin Huang, Jyotirmoy V. Deshmukh, Lars Lindemann, Bistra Dilkina
2025 conf
ISBI
Yuhe Dai, Zhiyong Huang, Weimin Huang
2024 conf
CBS
Yishi Shen, Shi Zhang, Weimin Huang, Chengrui Shang, Yiming Sun, Qing Shi
2024 conf
ICARM
Shi Zhang, Yishi Shen, Weimin Huang, Wendi Wang, Qing Shi
2024 A conf
ICST
Jiaxi Wu, Xin Wang, Ke Zhang, Weimin Huang, Lina Men, Shixiong Chen
2024 J jnl
CoRR
Weimin Huang, Taoan Huang, Aaron M. Ferber, Bistra Dilkina
2023 J jnl
CoRR
Yanling Chi, Yuyu Xu, Huiying Liu, Xiaoxiang Wu, Zhiqiang Liu, Jiawei Mao, Guibin Xu, Weimin Huang
2023 J jnl
IEEE Robotics Autom. Lett.
Shi Zhang, Yishi Shen, Weimin Huang, Chengrui Shang, Wenjie Chen, Qing Shi
2023 J jnl
IEEE Trans. Biomed. Eng.
Xin Wang, Qiong Tian, Mingxing Zhu, Yingying Wang, Boya Wang, Xiaobei Jing, Hiroshi Yokoi, Lin Li, Zhenzhen Liu, Weimin Huang, Shixiong Chen, Zhiyuan Liu, Guanglin Li
2023 A* conf
AAAI
Weimin Huang, Elias B. Khalil
2022 conf
BHI
Yongshen Zeng, Xiaoyan Song, Hongwu Chen, Weimin Huang, Wenjin Wang
2022 J jnl
IEEE Trans. Biomed. Eng.
Haoshi Zhang, Mingxing Zhu, Yanbing Jiang, Dan Wang, Xin Wang, Zijian Yang, Weimin Huang, Shixiong Chen, Guanglin Li
2022 J jnl
CoRR
Weimin Huang, Elias B. Khalil
2020 C conf
HealthCom
Yazan Ali Jarrah, Asogbon Mojisola Grace, Oluwarotimi Williams Samuel, Mingxing Zhu, Xin Wang, Alberto López Delis, Weimin Huang, Shixiong Chen, Guanglin Li
2008 conf
FSKD (1)
Weimin Huang, Leping Shen
2008 J jnl
IEEE Trans. Circuits Syst. Video Technol.
Ya-Dong Wang, Jian-Kang Wu, Ashraf A. Kassim, Weimin Huang
2008 C conf
ISCAS
Ruijiang Luo, Liyuan Li, Weimin Huang, Qibin Sun
2007 C conf
FUSION
Ya-Dong Wang, Jian-Kang Wu, Weimin Huang, Ashraf A. Kassim
2006 conf
ICPR (1)
Alex Yong Sang Chia, Weimin Huang, Liyuan Li
2006 B conf
ICIP
Alex Yong Sang Chia, Weimin Huang
2006 conf
ICPR (3)
Ya-Dong Wang, Jian-Kang Wu, Ashraf A. Kassim, Weimin Huang
2005 J jnl
IEEE Trans. Syst. Man Cybern. Part B
Haihong Zhang, Weimin Huang, Zhiyong Huang, Bailing Zhang
2005 conf
CVPR (1)
Haihong Zhang, Weimin Huang, Zhiyong Huang, Liyuan Li
2005 conf
ICIP (2)
Nan Hu, Weimin Huang, Surendra Ranganath
2004 C conf
ICARCV
Haihong Zhang, Weimin Huang, Zhiyong Huang, Bailing Zhang
2004 conf
Eurographics Multimedia Workshop
H. X. Zhang, Ruihua Ma, Weimin Huang, Zhiyong Huang
2004 conf
ICPR (2)
Haihong Zhang, Weimin Huang, Zhiyong Huang, Bailing Zhang
2004 conf
ICPR (2)
Haihong Zhang, Zhiyong Huang, Weimin Huang, Liyuan Li
2004 C conf
ICARCV
Liyuan Li, Ying Ting Koh, Shuzhi Sam Ge, Weimin Huang
2002 C conf
IEEE Workshop on Multimedia Signal Processing
Weimin Huang, Benghai Lee, Menaka Rajapakse, Liyuan Li
2000 B conf
ICPR
Weimin Huang, Robert Mariani
1998 B conf
ICPR
Weimin Huang, Qibin Sun, Chian-Prong Lam, Jian-Kang Wu
1998 conf
SSPR/SPR
Weimin Huang, Jian-Kang Wu
1998 B conf
FG
Qibin Sun, Weimin Huang, Jiankang Wu
1998 conf
EUSIPCO
Weimin Huang, Jian-Kang Wu, Qibin Sun, Chian-Prong Lam
1995 A conf
ICDAR
Weimin Huang, Gang Rong, Zhaoqi Bian
Docker-README.md
← Index Docker-README.md markdown
# REDB Docker Setup

This document describes the Docker containerization for the REDB malware analysis framework.

## Overview

REDB has been containerized as a single unified image that supports both feature extraction and decompilation analysis. The container is stateless, processes files from S3 or local mounts, and exports results to ClickHouse database or via API callbacks.

## Architecture

- **Single Unified Container**: One image handles both feature extraction and decompilation
- **Runtime Tool Installation**: Tools (CAPA, DIE, Binary Ninja) installed at runtime from host snapshots
- **Stateless Processing**: No persistent storage required between runs
- **Multiple Invocation Modes**: Supports `--nomad-job`, `--s3`, `--s3-solo`, and `--path` modes
- **External Dependencies**: Connects to external ClickHouse and S3 services

## Files Structure

```
├── Dockerfile                 # Single unified container definition
├── docker-build.sh            # Build script with Docker Desktop bug workaround
├── docker-push.sh             # Push script to registry
├── test-docker.sh             # Container testing script
├── test-nomad.sh              # Nomad job mode testing
├── .dockerignore              # Build context exclusions
└── scripts/
    └── setup-and-run.sh       # Runtime tool setup entrypoint
```

## Tool Installation Strategy

The container uses a **runtime installation** approach:

1. **Base Image**: Contains Python dependencies and REDB code
2. **Runtime Setup**: `scripts/setup-and-run.sh` configures tools at container start
3. **Host Snapshots**: Binary Ninja installed from `/opt/binaryninja` if available
4. **System Tools**: CAPA and DIE expected at `/usr/bin/capa` and `/usr/bin/nfdc`

## Build and Run

### 1. Build Container

```bash
# Build unified image
./docker-build.sh

# Manual build
docker build --platform linux/amd64 -f Dockerfile -t redb:latest .
```

### 2. Run Modes

#### Nomad Job Mode (Primary)
```bash
# Feature extraction
docker run --rm \
  -e JOB_ID="analysis_001" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="feature_extraction" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="BasicPropertiesExtractor,PEFeaturesExtractor" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e S3_ACCESS_KEY="your-key" \
  -e S3_SECRET_KEY="your-secret" \
  redb:latest python3 start.py --nomad-job

# Decompilation (same container, different flags)
docker run --rm \
  -e JOB_ID="analysis_002" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="decompilation" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="all" \
  -v /opt/binaryninja:/opt/binaryninja:ro \
  redb:latest python3 start.py --nomad-job --decompile
```

#### S3 Solo Mode
```bash
# Process single sample by S3 key (standard sharded path)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Process private sample (with prepath)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

#### Local Files Mode
```bash
# Mount local samples
docker run --rm \
  -v /path/to/samples:/samples:ro \
  -v ./logs:/app/logs \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  redb:latest python3 start.py --path /samples --repo local_test --index_prefix redb
```

## Environment Variables

### Required for Nomad Job Mode
- `JOB_ID` - Unique job identifier
- `S3_KEY` - S3 object key for sample
- `S3_BUCKET` - S3 bucket name
- `WORKER_TYPE` - "feature_extraction" or "decompilation"
- `CALLBACK_URL` - API endpoint for results
- `ANALYSIS_MODULES` - Comma-separated extractor list or "all"

### Database Configuration
- `CLICKHOUSE_HOST` - ClickHouse server hostname
- `CLICKHOUSE_PORT` - Port (default: 8123)
- `CLICKHOUSE_USER` - Database user (default: default)
- `CLICKHOUSE_PASSWORD` - Database password
- `CLICKHOUSE_DATABASE` - Database name (default: default)

### S3 Configuration
- `S3_ENDPOINT` - S3 endpoint URL
- `S3_ACCESS_KEY` - S3 access key
- `S3_SECRET_KEY` - S3 secret key
- `S3_SECURE` - "true" or "false" for HTTPS

### Processing Configuration
- `INDEX_PREFIX` - Database table prefix (default: redb)
- `REPO` - Repository identifier for this analysis batch
- `BATCH_SIZE` - Processing batch size (default: 10)
- `REDB_TIMEOUT` - Analysis timeout in seconds (default: 300)

### Tool Timeouts
- `CAPA_TIMEOUT` - CAPA analysis timeout (default: 300)
- `DIE_TIMEOUT` - DIE analysis timeout (default: 180)
- `BINJA_TIMEOUT` - Binary Ninja timeout (default: 1200)
- `DECOMPILE_EXTRACTOR_TIMEOUT` - Decompilation timeout (default: 2580)

## Binary Ninja Setup

For decompilation capabilities, mount Binary Ninja from host:

```bash
# Mount Binary Ninja installation
-v /opt/binaryninja:/opt/binaryninja:ro

# Mount license file
-v /path/to/license.dat:/home/analyzer/.binaryninja/license.dat:ro
```

The container will automatically detect and configure Binary Ninja at runtime.

## Registry Deployment

### Push to Registry
```bash
# Tag and push
./docker-push.sh

# Or manually
docker tag redb:latest your-registry/redb:latest
docker push your-registry/redb:latest
```

### Pull and Run
```bash
docker pull your-registry/redb:latest
docker run your-registry/redb:latest python3 start.py --nomad-job
```

## Testing

### Container Functionality Test
```bash
# Test with S3 key (standard sharded path)
./test-docker.sh "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Test with private sample S3 key
./test-docker.sh "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

### Nomad Job Architecture Test
```bash
# Test Nomad job mode
./test-nomad.sh
```

## Development

### Interactive Container
```bash
# Debug container interactively
docker run -it --entrypoint /bin/bash redb:latest

# Check tool availability
docker run --rm redb:latest which python3
docker run --rm redb:latest ls -la /usr/bin/capa
```

### Build Troubleshooting

The build script includes workarounds for Docker Desktop bugs:

```bash
# If build hangs at "exporting to image", press Ctrl+C
# The image will still be created and tagged automatically
./docker-build.sh
```

### Container Logs
```bash
# View logs from mounted directory
docker run -v ./logs:/app/logs redb:latest python3 start.py --path /samples
tail -f logs/*.txt
```

## Production Notes

### Resource Requirements
- **Memory**: 2-4GB recommended (8GB for decompilation)
- **CPU**: 2+ cores recommended
- **Disk**: Minimal (stateless container)
- **Network**: Access to ClickHouse and S3 services

### Security
- Container runs as non-root user `analyzer` (UID 1000)
- Sample files should be mounted read-only
- No persistent state between container runs
- Isolated processing environment for malware analysis

### Deployment Architecture

This container is designed for:
- **Nomad job dispatch**: Single-use containers processing one sample each
- **Kubernetes jobs**: Batch processing with external orchestration
- **CI/CD pipelines**: Automated analysis in build systems
- **Development**: Local testing and debugging

The unified container approach means the same image handles both feature extraction and decompilation - the difference is only in the command-line flags used when starting the container.