Wei Lin

60 papers A* 13A 7B 1C 9Journal 12Unranked 17
YearRankTypeTitle / Venue / Authors
2024 conf
AIM
Jay Karhade, Haiyue Zhu, Ka-Shing Chung, Rajesh Kumar Tripathy, Wei Lin, Marcelo H. Ang
2023 C ed.
PSIVT
Han Wang, Wei Lin, Manoranjan Paul, Guobao Xiao, Kap Luk Chan, Xiaonan Wang, Guiju Ping, Haoge Jiang
2023 conf
ISER
Ka-Shing Chung, Marcelo H. Ang, Wei Lin, Haiyue Zhu, Joel Stephen Short, Pey Yuen Tao
2022 C ed.
IAS
Marcelo H. Ang Jr., Hajime Asama, Wei Lin, Shaohui Foong
2022 J jnl
CoRR
Jay Karhade, Haiyue Zhu, Ka-Shing Chung, Rajesh K. Tripathy, Wei Lin, Marcelo H. Ang Jr.
2022 J jnl
IEEE Trans Autom. Sci. Eng.
Haiyue Zhu, Xiong Li, Wenjie Chen, Xiaocong Li, Jun Ma, Chek Sing Teo, Tat Joo Teo, Wei Lin
2021 J jnl
IEEE Trans. Ind. Electron.
Xiong Li, Haiyue Zhu, Wei Lin, Wenjie Chen, Kin Huat Low
2020 J jnl
Unmanned Syst.
Han Wang, Wei Lin, Xiaonan Wang
2020 A conf
IROS
Haiyue Zhu, Yiting Li, Fengjun Bai, Wenjie Chen, Xiaocong Li, Jun Ma, Chek Sing Teo, Pey Yuen Tao, Wei Lin
2020 J jnl
CoRR
Haiyue Zhu, Yiting Li, Fengjun Bai, Wenjie Chen, Xiaocong Li, Jun Ma, Chek Sing Teo, Pey Yuen Tao, Wei Lin
2019 J jnl
IEEE Trans. Ind. Electron.
Nazir Kamaldin, Si-Lu Chen, Chek Sing Teo, Wei Lin, Kok Kiong Tan
2018 conf
AIM
Zheng Ma, Geok-Soon Hong, Marcelo H. Ang, Aun Neow Poo, Wei Lin
2018 J jnl
IEEE Trans Autom. Sci. Eng.
Xiong Li, Wenjie Chen, Wei Lin, Kin Huat Low
2017 J jnl
J. Frankl. Inst.
Jun Ma, Si-Lu Chen, Chek Sing Teo, Chun Jeng Kong, Arthur Tay, Wei Lin, Abdullah Al Mamun
2017 conf
AIM
Zheng Ma, Hian-Hian See, Geok-Soon Hong, Marcelo H. Ang, Aun Neow Poo, Wei Lin, Pey Yuen Tao, Joel Stephen Short
2017 A* conf
ICRA
Xiong Li, Wenjie Chen, Wei Lin
2017 conf
CASE
Wei Jing, Joseph Polden, Pey Yuen Tao, Chun Fan Goh, Wei Lin, Kenji Shimada
2017 A conf
IROS
Wei Jing, Joseph Polden, Chun Fan Goh, Mabaran Rajaraman, Wei Lin, Kenji Shimada
2016 C conf
IECON
Jun Ma, Si-Lu Chen, Chek Sing Teo, Chun Jeng Kong, Arthur Tay, Wei Lin, Abdullah Al Mamun
2016 conf
AIM
Ngoc Chi Nam Doan, Pey Yuen Tao, Wei Lin
2016 A conf
IROS
Wei Jing, Joseph Polden, Wei Lin, Kenji Shimada
2016 C conf
ICARCV
Wei Jing, Joseph Polden, Pey Yuen Tao, Wei Lin, Kenji Shimada
2015 conf
AIM
Si-Lu Chen, Jun Ma, Chek Sing Teo, Chun Jeng Kong, Wei Lin, Arthur Tay, Abdullah Al Mamun
2015 A conf
IROS
Wenjie Chen, Xiong Li, Sheng Jie Teo, Wei Lin, Huat Kin Low
2015 conf
CASE
Hong Luo, Qun Han Chen, W. S. Chen, Eng Teo Ong, Wen Jong Lin, Wei Lin
2011 A* conf
ICRA
Guilin Yang, Tat Joo Teo, I-Ming Chen, Wei Lin
2010 C conf
ICARCV
Wenjie Chen, Wei Lin, Guilin Yang
2010 C conf
ICARCV
J. H. Chow, Zhao-Wei Zhong, Wei Lin, Li Pheng Khoo, Wen-Jong Lin, Guilin Yang
2010 C conf
ICARCV
Joo Hoo Nam, Peter C. Y. Chen, Zhe Lu, Hong Luo, Ruowen Ge, Wei Lin
2010 A* conf
ICRA
Tat Joo Teo, I-Ming Chen, Choon Meng Kiew, Guilin Yang, Wei Lin
2010 C conf
ICARCV
Shengfeng Zhou, Peter C. Y. Chen, Zhe Lu, Joo Hoo Nam, Hong Luo, Ruowen Ge, Chong Jin Ong, Wei Lin
2009 conf
ROBIO
Joo Hoo Nam, Peter C. Y. Chen, Zhe Lu, Hong Luo, Ruowen Ge, Wei Lin
2009 A* conf
ICRA
Liang Yan, I-Ming Chen, Chee Kian Lim, Guilin Yang, Wei Lin, Kok-Meng Lee
2008 J jnl
IEEE Trans Autom. Sci. Eng.
Wei Lin, Wenjie Chen
2008 A* conf
ICRA
Mustafa Shabbir Kurbanhusen, Guilin Yang, Song Huat Yeo, Wei Lin
2008 conf
RAM
Liang Yan, I-Ming Chen, Chee Kian Lim, Guilin Yang, Wei Lin, Kok-Meng Lee
2007 A* conf
ICRA
Zhe Lu, Peter C. Y. Chen, Joo Hoo Nam, Ruowen Ge, Wei Lin
2007 A* conf
ICRA
Tat Joo Teo, I-Ming Chen, Guilin Yang, Wei Lin
2007 A* conf
ICRA
Andrew P. Shacklock, Matthew C. Pritchard, Hong Luo, Etienne Burdet, Wei Lin
2007 A* conf
ICRA
Mustafa Shabbir Kurbanhusen, Guilin Yang, Song Huat Yeo, Wei Lin
2006 conf
CASE
Chee Kian Lim, Chun Yong Ang, I-Ming Chen, Guilin Yang, Wei Lin
2006 C conf
ICARCV
Wen-Jong Lin, Jitendra Prasad Khatait, Wei Lin, Huaizhong Li
2006 A conf
IROS
Liang Yan, I-Ming Chen, Chee Kian Lim, Guilin Yang, Wei Lin, Kok-Meng Lee
2006 A* conf
ICRA
Yuan Ping Li, Teresa Zielinska, Marcelo H. Ang Jr., Wei Lin
2005 A conf
IROS
Liang Yan, I-Ming Chen, Chee Kian Lim, Guilin Yang, Wei Lin, Kok-Meng Lee
2005 J jnl
Int. J. Softw. Eng. Knowl. Eng.
Huaizhong Li, Zhiming Gong, Wei Lin, T. Y. Jiang, Xiaoqi Chen
2005 conf
CASE
Zhiming Gong, Edwin Hui Leong Ho, Guilin Yang, Wei Lin
2005 ch.
Innovations in Robot Mobility and Control
Kok Kiong Tan, Sunan Huang, Ser Yong Lim, Wei Lin
2005 B conf
SMC
Shouqian Yu, Weihai Chen, Guilin Yang, Wei Lin
2005 A* conf
ICRA
Liang Yan, I-Ming Chen, Chee Kian Lim, Guilin Yang, Wei Lin, Kok-Meng Lee
2004 conf
RAM
Guilin Yang, Edwin Hui Leong Ho, Weihai Chen, Wei Lin, Song Huat Yeo, Mustafa Shabbir Kurbanhusen
2004 conf
RAM
Liang Yan, Chee Kian Lim, I-Ming Chen, Guilin Yang, Wei Lin
2004 conf
RAM
Wenjie Chen, Wei Lin
2004 conf
RAM
Weihai Chen, Tat Joo Teo, Wei Lin, Guilin Yang, Edwin Hui Leong Ho
2004 J jnl
IEEE Trans. Robotics Autom.
Guilin Yang, I-Ming Chen, Weihai Chen, Wei Lin
2004 conf
RAM
Chee Kian Lim, Liang Yan, I-Ming Chen, Guilin Yang, Wei Lin
2001 A conf
IROS
Wei Lin, Xiaoqi Chen
2001 A* conf
ICRA
Guilin Yang, I-Ming Chen, Wei Lin, Jorge Angeles
2001 J jnl
IEEE Trans. Robotics Autom.
Guilin Yang, I-Ming Chen, Wei Lin, Jorge Angeles
2000 A* conf
ICRA
Marcelo H. Ang, Wei Lin, Ser Yong Lim
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.