Xiaohong W. Gao

56 papers A 1B 3C 4Journal 16Unranked 31
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Xiaohong W. Gao, Chia-Hui Chien, Guan-Lin Liu, Amja Manullang
2026 conf
BIOSTEC (1)
Xiaohong W. Gao, Chia-Hui Chien, Guan-Lin Liu, Amja Manullang
2025 conf
BIOSTEC (1)
Xiaohong W. Gao, Annisa Rahmanti, Barbara Braden
2025 conf
BraTS-Lighthouse/AIMS-TBI@MICCAI (2)
Xiaohong W. Gao, Chia-Hui Chien, Guan-Lin Liu, Jyh-Cheng Chen
2025 conf
AI (2)
Amja Manullang, Xiaohong W. Gao, Christophe Viavattene, Annisa Ristya Rahmanti
2025 conf
AI (2)
Guan-Lin Liu, Sergei G. Kazarian, Fengge Gao, Xiaohong W. Gao
2025 conf
MedInfo
Chia-Hui Chien, Shih-Chuan Chang, Muhammad Solihuddin Muhtar, Xiaohong W. Gao, Yung-Chun Chang, Yu-Chuan Li
2025 conf
AI (2)
Chia-Hui Chien, Yung-Chun Chang, Yu-Chuan Li, Xiaohong W. Gao
2025 J jnl
IEEE Access
Preeti Bissoonauth-Daiboo, Muhammad Muzzammil Auzine, Muhammad I. Khan, Fatima Alshannaq, Tanzila Saba, Xiaohong W. Gao, Maleika Heenaye-Mamode Khan
2023 A conf
DIS
Silviu Tudor Marc, Roman V. Belavkin, David Windridge, Xiaohong W. Gao
2023 conf
ICAAI
Preeti Bissoonauth-Daiboo, Maleika Heenaye-Mamode Khan, Muhammad Muzzammil Auzine, Xiaohong W. Gao, Sunilduth Baichoo, Zaid Heetun
2023 conf
ICAAI
Muhammad Muzzammil Auzine, Maleika Heenaye-Mamode Khan, Sunilduth Baichoo, Preeti Bissoonauth-Daiboo, Zaid Heetun, Xiaohong W. Gao
2023 J jnl
Inf. Fusion
Xiaohong W. Gao, Stephen Taylor, Wei Pang, Rui Hui, Xin Lu, Barbara Braden
2023 J jnl
Artif. Intell. Medicine
Mark Eastwood, Silviu Tudor Marc, Xiaohong W. Gao, Heba Sailem, Judith Offman, Emmanouil Karteris, Angeles Montero Fernandez, Danny Jonigk, William Cookson, Miriam Moffatt, Sanjay Popat, Fayyaz Minhas, Jan Lukas Robertus
2023 J jnl
CoRR
Mark Eastwood, Heba Sailem, Silviu Tudor Marc, Xiaohong W. Gao, Judith Offman, Emmanouil Karteris, Angeles Montero Fernandez, Danny Jonigk, William Cookson, Miriam Moffatt, Sanjay Popat, Fayyaz ul Amir Afsar Minhas, Jan Lukas Robertus
2023 conf
ICCAE
Faten Alzazah, Xiaochun Cheng, Xiaohong W. Gao
2022 conf
NextComp
Xiaohong W. Gao, Maleika Heenaye-Mamode Khan, Rui Hui, Zhengmeng Tian, Yu Qian, Alice Gao, Sunilduth Baichoo
2022 conf
NextComp
Muhammad Muzzammil Auzine, Preeti Bissoonauth-Daiboo, Maleika Heenaye-Mamode Khan, Sunilduth Baichoo, Xiaohong W. Gao, Nuzhah Gooda Sahib
2022 conf
Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaohong W. Gao, Xuesong Wen, Dong Li, Weiping Liu, Jichun Xiong, Xuefeng Liu
2022 conf
Computer-Aided Diagnosis
Xiaohong W. Gao, Stephen Taylor, Wei Pang, Xin Lu, Barbara Braden
2022 B conf
AIME
Mark Eastwood, Silviu Tudor Marc, Xiaohong W. Gao, Heba Sailem, Judith Offman, Emmanouil Karteris, Angeles Montero Fernandez, Danny Jonigk, William Cookson, Miriam Moffatt, Sanjay Popat, Fayyaz A. Minhas, Jan Lukas Robertus
2022 conf
ICSC
Faten Alzazah, Xiaochun Cheng, Xiaohong W. Gao
2021 C conf
ICMLA
Xiaohong W. Gao, Alice Gao
2021 J jnl
Medical Image Anal.
Sharib Ali, Mariia Dmitrieva, Noha M. Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan J. Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Lê Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James E. East, Jens Rittscher
2021 C conf
ICMLA
Xiaohong W. Gao, Xuesong Wen, Dong Li, Weiping Liu, Jichun Xiong, Bin Xu, Juan Liu, Heng Zhang, Xuefeng Liu
2020 J jnl
CoRR
Sharib Ali, Mariia Dmitrieva, Noha M. Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan J. Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Lê Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James E. East, Jens Rittscher
2020 B conf
ICIP
Xiaohong W. Gao, Richard Comley, Maleika Heenaye-Mamode Khan
2020 J jnl
Neurocomputing
Xiaohong W. Gao, Carl James-Reynolds, Edward Currie
2020 conf
EndoCV@ISBI
Xiaohong W. Gao, Barbara Braden
2020 conf
EndoCV@ISBI
Shahadate Rezvy, Tahmina Zebin, Barbara Braden, Wei Pang, Stephen Taylor, Xiaohong W. Gao
2019 C conf
ICMLA
Xiaohong W. Gao, Barbara Braden, Stephen Taylor, Wei Pang
2018 conf
CLEF (Working Notes)
Xiaohong W. Gao, Carl James-Reynolds, Edward Currie
2018 conf
Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaohong W. Gao, Yu Qian
2017 J jnl
Inf. Fusion
Xiaohong W. Gao, Wei Li, Martin J. Loomes, Lianyi Wang
2017 conf
CLEF (Working Notes)
Xiaohong W. Gao, Yu Qian
2017 J jnl
Comput. Methods Programs Biomed.
Xiaohong W. Gao, Rui Hui, Zengmin Tian
2016 conf
Color Imaging: Displaying, Processing, Hardcopy, and Applications
Xiaohong W. Gao, Monica Loomes
2015 conf
MRDM@ECIR
Wei Li, Yu Qian, Martin J. Loomes, Xiaohong W. Gao
2014 conf
SSIAI
Xiaohong W. Gao
2013 J jnl
Signal Process.
Yu Qian, Rui Hui, Xiaohong W. Gao
2012 conf
CGIV
Xiaohong W. Gao, Yu Qian, Yuanlei Wang, Anthony White
2012 conf
MCBR-CDS
Yu Qian, Lianyi Wang, Chunyan Wang, Xiaohong W. Gao
2011 conf
DSP
Xiaohong W. Gao
2008 J jnl
EURASIP J. Image Video Process.
Xiaohong W. Gao, Kunbin Hong, Peter J. Passmore, Lubov Podladchikova, Dmitry Shaposhnikov
2008 J jnl
Comput. Methods Programs Biomed.
Henning Müller, Xiaohong W. Gao, Shuqian Luo
2008 ed.
MIMI
Xiaohong W. Gao, Henning Müller, Martin J. Loomes, Richard Comley, Shuqian Luo
2008 B conf
CBMS
Sergey Anishchenko, Vladislav Osinov, Dmitry Shaposhnikov, Lubov Podladchikova, Richard Comley, Xiaohong W. Gao
2007 conf
MIMI
Xiaohong W. Gao, John Clark
2007 conf
MIMI
Stephen Batty, John Clark, Tim D. Fryer, Xiaohong W. Gao
2006 J jnl
Comput. Medical Imaging Graph.
Henning Müller, Xiaohong W. Gao, Qiang Lin, Thomas Martin Lehmann, Simon A. Thom, Paolo Inchingolo, Jyh-Cheng Chen, John Clark
2006 J jnl
J. Vis. Commun. Image Represent.
Xiaohong W. Gao, Lubov Podladchikova, Dmitry Shaposhnikov, Kunbin Hong, Natalia Shevtsova
2003 C conf
ICANN
Xiaohong W. Gao, Lubov Podladchikova, Dmitry Shaposhnikov
2002 conf
CGIV
Xiaohong W. Gao, Natalia Shevtsova, Kunbin Hong, Stephen Batty, Lubov N. Podladchikova, Alexander V. Golovan, Dmitry Shaposhnikov, Valentina I. Gusakova
2001 conf
ICIP (2)
Xiaohong W. Gao, Anil A. Bharath, Alice V. Stanton, Alun D. Hughes, Neil Chapman, Simon A. Thom
2001 conf
VIIP
Xiaohong W. Gao, Stephen Batty, John Clark, Tim D. Fryer, Ann Blandford
2000 J jnl
Comput. Methods Programs Biomed.
Xiaohong W. Gao, Anil A. Bharath, Alice V. Stanton, Alun D. Hughes, Neil Chapman, Simon A. Thom
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.